Top Machine Learning Startups 2023

December 2023

Browse 100 of the top Machine Learning startups funded by Y Combinator.

We also have a Startup Directory where you can search through over 4,000 companies.

  • Cruise
    Cruise (W14)Acquired • 3,000 employees • San Francisco
    Cruise is building the world’s most advanced, all-electric, self-driving car technology to safely connect people with the places, things, and experiences they care about. Self-driving cars will help save lives, reimagine cities, redefine time in transit, and restore freedom of movement for individuals who live in dense urban settings. Acquired by GM in 2016.
    autonomous-delivery
    machine-learning
    climate
    ai
    self-driving-vehicles
  • Scale AI
    Scale AI (S16)Active • 500 employees • San Francisco
    Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.
    artificial-intelligence
    machine-learning
  • Relativity Space
    Relativity Space (W16)Active • 1,000 employees • Los Angeles, CA
    Relativity is building humanity’s multiplanetary future. We invented a new approach to design, build, and fly our own rockets, starting with Terran 1 – the world’s first entirely 3D printed rocket, and Terran R, our next generation medium-heavy lift fully reusable launch vehicle. As a vertically integrated technology platform, Relativity is at the forefront of an inevitable shift toward software-defined manufacturing. By fusing 3D printing, artificial intelligence, and autonomous robotics, we are pioneering the factory of the future. Disrupting 60 years of aerospace, Relativity offers a radically simplified supply chain, building a rocket with 100x fewer parts in less than 60 days. We believe in a future where interplanetary life fundamentally expands the possibilities for human experience. Our long-term vision is to upgrade humanity’s industrial base on Earth and on Mars.
    machine-learning
    space-exploration
    rocketry
    3d-printing
    manufacturing
  • Flock Safety
    Flock Safety (S17)Active • 800 employees • Atlanta, GA
    Flock Safety provides the first public safety operating system that empowers private communities and law enforcement to work together to eliminate crime. We are committed to protecting human privacy and mitigating bias in policing with the development of best-in-class technology rooted in ethical design, which unites civilians and public servants in pursuit of a safer, more equitable society. Our Safety-as-a-Service approach includes affordable devices powered by LTE and solar that can be installed anywhere. Our technology detects and captures objective details, decodes evidence in real-time and delivers investigative leads into the hands of those who matter. While safety is a serious business, we are a supportive team that is optimizing the remote experience to create strong and fun relationships even when we are physically apart. Our flock of hard-working employees thrive in a positive and inclusive environment, where a bias towards action is rewarded. Flock Safety is headquartered in Atlanta and operates nationwide. We have raised $150M in our Series E led by Tiger Global at a $3.5B valuation.
    hardware
    machine-learning
    saas
  • Sift
    Sift (S11)Active • San Francisco
    Sift is the leader in Digital Trust & Safety, empowering digital disruptors to Fortune 500 companies to unlock new revenue without risk. Sift dynamically prevents fraud and abuse through industry-leading technology and expertise, an unrivaled global data network of 70 billion events per month, and a commitment to long-term customer partnerships. Global brands such as DoorDash, Twitter, and Wayfair rely on Sift to gain a competitive advantage in their markets.
    fintech
    machine-learning
    saas
    b2b
  • Tempo
    Tempo (W15)Active • 158 employees • San Francisco
    SmartSpot is a post Series-A stealth startup backed by Founders Fund and Khosla Ventures that uses computer vision to deliver an unparalleled fitness training experience to your home. Our unique hardware solution gives amazing trainers the ability to see their class participants in real time and deliver detailed advice that was previously only possible in person.
    machine-learning
    consumer-health-services
  • TRM Labs
    TRM Labs (S19)Active • 180 employees • San Francisco
    At TRM, we're on a mission to build trust in digital assets, because the promise of crypto is too valuable to be impeded by bad actors. We provide a blockchain intelligence platform to law enforcement, financial institutions, and crypto firms to assist in the detection and prevention of cryptocurrency fraud and financial crime. Our vision is to build a company that can sustainably deliver on our mission for decades to come, enabling consumers to transact safely and securely on the blockchain. Join our mission ➔ www.trmlabs.com/careers
    fintech
    machine-learning
    crypto-web3
    data-engineering
  • PicnicHealth
    PicnicHealth (S14)Active • 100 employees • San Francisco
    Healthcare needs good data. At PicnicHealth, we are building deep real-world datasets fueling cutting-edge research while giving patients control of their own medical record data. These complete, clinically-rich datasets produce unique insights — across dozens of diseases — to ultimately get the right treatments into patients’ hands faster. We work directly with patients and leverage state of the art machine learning to transform messy medical records into structured, research-ready datasets. To date we’ve helped tens of thousands of patients securely access their records and proactively contribute to advancing research in diseases that impacts their lives.
    machine-learning
    health-tech
    digital-health
    healthcare
    nlp
  • Pachama
    Pachama (W19)Active • 85 employees • San Francisco
    Pachama is a leading climate-tech company harnessing cutting-edge technologies such as computer vision and satellites to drive funding to effective reforestation and conservation projects that sequester carbon, enhance biodiversity and enrich local communities around the world. Through a tech-verified marketplace that counts as customer the likes of Amazon, Airbnb, Netflix and Nespresso, the company drives capital to forests in Brazil, Mexico, India, the USA and beyond. The company is backed by top investors such as Bill Gates' BEV, Chis Sacca's LowerCarbon, Amazon Climate Pledge among others. The company is fully remote and driven by a strong sense of purpose.
    carbon-capture-and-removal
    machine-learning
    climate
  • Delphia
    Delphia (W18)Active • 35 employees • Toronto, Canada
    [Delphia](https://delphia.com/) is building a new kind of asset manager that rethinks the value of data and how it can be used to gain an edge in forecasting markets. We believe that actively managing people’s data can unlock new forms of wealth creation for individual and institutional investors alike. To create the next [Millennium](https://www.mlp.com/) (and eventually, [Blackstone](https://www.blackstone.com/)), you need each of the following; 1. A captivating reason for people to connect their data ([in beta](https://abr.ge/k4xqep)) 2. A way to automate data extraction from aggregators ([acquired](https://www.prnewswire.com/news-releases/delphia-strengthens-data-rights-with-acquisition-of-fathom-privacy-301696745.html)) 3. A cooperative way to ensure "fair trade" compensation for data ([built](https://www.supersetdao.com/)) 4. A way to reward data contributors transparently and irreversibly ([on pause](https://www.coindesk.com/business/2022/09/28/algorithmic-stock-platform-delphia-debuts-digital-asset-component/)) 5. A way to discover investment managers with uncorrelated alpha ([open sourced](https://github.com/charliereese/investos)) 6. A way to help investment managers make use of our data advantage ([partnered](https://covariance.ai/)) 7. A way to access to stock order flow that has net benefit to retail investors (coming soon) 8. Capacity rights in investment strategies whose returns improve with data ([first of many](http://www.oraclealpha.com/)), and 9. A secure training environment for third-party ML models (the goal of our next venture round) If our thesis bears out, the $7 billion alternative data industry ([$135 billion by 2030](https://explodingtopics.com/blog/alternative-data-market)) may be in for a Cambrian explosion that has yet to be priced in. Being able to acquire ground truth cost-effectively using first-party data, and thus being able to forecast fundamentals more accurately, is the key to attracting the world's best investment ideas to a platform. People at Delphia are socially-minded creatives at heart. Our teams are continually researching, iterating, and solving hard problems in order to generate new forms of economic returns. Our multi-disciplinary team was founded in 2018 and is a graduate of [Y Combinator](https://ycombinator.com/) and the [Creative Destruction Lab](https://creativedestructionlab.com/). We’ve raised three rounds of funding ([~$80 million](https://www.crunchbase.com/organization/delphia)) to date.
    artificial-intelligence
    fintech
    machine-learning
    dao
  • 64x Bio
    64x Bio (S18)Active • 25 employees • San Francisco
    64x Bio is building a platform that radically increases the speed and scale of mammalian cell line discovery. Using a novel high throughput discovery and screening platform and an integrated computational design loop, we are developing new ways of generating highly optimized and otherwise unattainable cell lines for the manufacturing of viral vectors, with a specific focus on those used for cell and gene therapies. Our platform technology enables pharmaceutical and biotechnology companies to bring cell and gene therapies to patients more effectively, providing purpose-built genetically engineered cell lines to increase the efficiency of viral vector production and reduce the cost of manufacturing.
    gene-therapy
    machine-learning
  • Shelf Engine
    Shelf Engine (S18)Active • 40 employees • Seattle, WA
    Shelf Engine helps businesses increase sales by accurately predicting the perfect amount of perishable goods to order, thus reducing food waste.
    machine-learning
  • Roboflow
    Roboflow (S20)Active • 35 employees • Des Moines, IA
    Roboflow enables developers to make the world programmable. Use our tools to build better datasets (collect image, video / annotate), models (foundation and fine tuned small models), and deployments (self hosted, edge, APIs, SDKs) for computer vision. Over 250k developers, including those from over half the Fortune 100, build with our open source and hosted tools. Build with us: https://app.roboflow.com Hack with us: https://roboflow.slab.com/public/posts/roboflow-hackathons-external-u478m1iz Work with us: roboflow.com/careers
    developer-tools
    machine-learning
    saas
    computer-vision
    api
  • Coverage Cat
    Coverage Cat (S22)Active • 4 employees • New York
    Coverage Cat (https://www.coveragecat.com) is the best way for people to optimally insure against their risks for homeowners, auto, renters, and general liability insurance. Millions of wealthy but insurance-unfamiliar Americans have purchased policies that leave them vulnerable to million-dollar lawsuits and bankruptcy. Coverage Cat fixes their coverage and offers them cheaper premiums with a focus on the central question of insurance: "how much can you afford to lose?" This risk-first approach allows for policies with higher deductibles that no other insurer will sell you, and enables us to find the multi-million dollar coverage, for truly catastrophic events, that our users need.
    fintech
    machine-learning
    insurance
  • CAPSULE
    CAPSULE (S22)Active • 2 employees • San Francisco
    CAPSULE is a mobile app that makes it easy to save and buy the things you find on any social media platform. Just snap a screenshot of anything you like, from any platform, and we search the entire internet to instantly give you shoppable links. Instead of searching hundreds of websites and sifting through thousands of products on your own, CAPSULE lets you find inspiration from anywhere and uses advanced machine learning to return results that feel like magic.
    machine-learning
    e-commerce
  • Delfino AI
    Delfino AI (S22)Active • 2 employees • San Francisco
    Delfino AI helps automate the repetitive phone calls that providers' offices make to payors
    artificial-intelligence
    generative-ai
    machine-learning
    health-tech
  • Lavo Life Sciences
    Lavo Life Sciences (W23)Active • 3 employees
    Lavo Life Sciences runs simulations of drug molecules on computers. Pharma companies use these simulations to guide their experiments and ultimately save time and money in the lab. This will de-risk and expedite clinical trials and FDA approval.
    ai-powered-drug-discovery
    machine-learning
    biotech
    drug-discovery
  • Knowtex
    Knowtex (S22)Active • San Francisco
    We’re on a mission to leverage AI and voice technology to solve inefficiencies and revenue leakage in our healthcare system. With the rise of EHRs, the manual documentation burden on doctors has never been higher, leading to burnout and fatigue and high attrition rates. Assigning the correct diagnosis and billing codes is crucial for proper reimbursement and patient care, but medical coding is becoming more and more complex each year with growing numbers of codes (over 145,000 now), and doctors are unsupported by current technology to keep up with its ever increasing requirements. $125 billion is left on the table each year by healthcare organizations due to improper documentation and coding. Knowtex creates visit notes with up-to-date and accurate reimbursement codes from doctor-patient conversations, allowing the doctor to focus on patient care and preventing revenue leakage for hospital systems through standardized, transparent, and accurate documentation.
    machine-learning
    health-tech
    b2b
    productivity
    digital-health
  • Delight
    Delight (S22)Active • 2 employees • San Francisco
    Delight changes the traditional dating app paradigms by encouraging users to focus solely on one person at a time. This intentional focus has created a dating community that fosters deeper connections and filters out casual daters. At Delight, users express their heart's desires in free form text, as if they're talking to a human matchmaker. Our AI-powered MatchMaker understands their preferences and selects potential partners who best align with them, no matter how complex and detailed their preferences are. Each potential partner is then presented with a MatchMaker note, expressing why they'd be a good fit. This intelligent matchmaking process saves our singles from browsing thousands of profiles. Once two users like each other, they can only talk to one another. This "one person at a time" philosophy helps to filter out the noise prevalent in modern online dating, allowing users to dedicate their time and attention to exploring a single prospective relationship at a time. If a match doesn't work out, our users can terminate that conversation, and explore other singles, until they find The One.
    generative-ai
    machine-learning
    consumer
    dating
    ai
  • HOMLI
    HOMLI (S22)Active • 20 employees • New York
    Launched in 2022, HOMLI is a modern, scalable real estate brokerage that helps European consumers sell, rent, and buy real estate. We are building Europe's first 'Zestimate' platform to finally bring transparency around property prices and neighborhood dynamics to all consumers across Europe. We couple that with an in-house brokerage team that is more effective, more productive, and more pleasant to work with. We combine the most advanced technological innovations with a holistically new approach to operations to re-invent a brokerage industry that hasn't evolved in decades, and introduce a brand new real estate experience for European consumers.
    machine-learning
    real-estate
    consumer
    proptech
    ai
  • Lamin
    Lamin (S22)Active • 4 employees • Munich, Germany
    Manage data & analyses with an open-source Python framework. Collaborate across dry and wetlab in a distributed data hub. Get started on your laptop and deploy anywhere.
    developer-tools
    machine-learning
    biotech
    open-source
    data-engineering
  • Fini
    Fini (S22)Active • 5 employees • Amsterdam, Netherlands
    Fini helps companies retain users by proactively resolving user issues. We do this by connecting with our customers inbound systems (eg: Zendesk, Segment, custom API etc.), and running ML models in order to analyze, segment and prevent user problems through proactive interventions.
    artificial-intelligence
    machine-learning
    robotic-process-automation
    saas
    b2b
  • Provision
    Provision (S22)Active • 3 employees • Toronto, Canada
    Provision is building the contract analysis platform for construction. Instead of manually reading through thousands of pages of documents and revisions, Provision organizes and extracts information so constructors can save time and reduce the cost of future mistakes.
    documents
    machine-learning
    construction
    productivity
    nlp
  • Typewise
    Typewise (S22)Active • 12 employees • Zürich, Switzerland
    Typewise develops text prediction software for customer service and sales teams. Our enterprise clients such as DPD (a Fortune 500 logistics company) use Typewise to communicate with their customers faster and more effectively.
    artificial-intelligence
    machine-learning
    b2b
    productivity
    api
  • Apply Design
    Apply Design (S22)Active • 4 employees • Tel Aviv-Yafo, Israel
    Apply Design helps homeowners sell their property 30% faster with a 5% higher price. We do this through our custom website creator that showcases your home's potential in a way that is personalized to the buyer. For example, when a young married couple with a baby visits the website we host, instead of seeing a dull property listing on Zillow with empty pictures or old furniture, the family sees realistic and personalized virtual interior designs – such as a home office and a baby room – which we automatically generate for them. They can then play with those designs and see how that home fits their needs and tastes. This is a $10B market opportunity, given the 50M properties sold or rented annually in North America and Europe alone.
    machine-learning
    saas
    computer-vision
    real-estate
    proptech
  • IvyCheck
    IvyCheck (S22)Active • 2 employees • Berlin, Germany
    IvyCheck provides tools for developing LLM-based apps. Start testing, versioning, and monitoring your AI apps.
    generative-ai
    machine-learning
    b2b
    analytics
    ai
  • NuMind
    NuMind (S22)Active • 6 employees • Cambridge, MA
    NuMind is a tool for data scientists, data analysts, but also software engineers to create custom NLP models. For example, a recruiting company uses NuMind to find which job offers best match a given resume. Etienne (CEO) was head of Machine Learning at Wolfram Research, and Samuel (CTO) co-founded Make.org (8M users). NuMind originated from our own frustration when developing NLP models. Leveraging large language models similar to GPT-3, NuMind allows to complete NLP projects at least 10x faster than before. We launched a private beta August 2 and had 9 paying customers one month later.
    aiops
    artificial-intelligence
    machine-learning
    nlp
  • Sematic
    Sematic (S22)Active • 5 employees • San Francisco
    Sematic helps Machine Learning and Data Science developers transition from Jupyter Notebook prototypes to continuous learning pipelines in days not weeks. Sematic is a lightweight open-source ML/DS pipeline development and execution framework based on learnings from working at Cruise. With easy-as-pie onboarding, simply use native Python to develop and run arbitrary end-to-end pipelines that track and version all your assets and artifacts (models, datasets, plots, metrics, etc.), and visualize them in a slick UI. Collaborate with your team in Sematic to keep the conversation close to the data context. Soon, you will be able to automate, schedule, and clone pipelines at will with no-code; to scale yourself and your team out and focus on new models instead of babysitting old ones forever.
    aiops
    developer-tools
    machine-learning
    saas
    open-source
  • Flike
    Flike (W22)Active • 8 employees • San Francisco
    Flike trains AI models on your product marketing knowledge, enabling your sales team to generate relevant&hyper-personalized emails that are aligned with your brand voice throughout the entire sales funnel (from cold outbound to upselling). And we're already partnering with some of the largest YC companies.
    machine-learning
    ai
  • Koko
    Koko (W22)Active • 2 employees • San Francisco
    We provide free digital mental health technologies for millions of people struggling online — particularly young people. For example, we partner with online communities to help find and treat at-risk individuals directly on their platform using our online interventions.
    machine-learning
    mental-health-tech
    nonprofit
    social
    nlp
  • GoJom
    GoJom (W22)Active • 140 employees • Lima, Peru
    GoJom is a One Stop Shop for Real Estate Solutions. It’s technology creates a faster and easier way to buy, sell and rent properties in LaTam.
    fintech
    machine-learning
    proptech
  • Ploomber
    Ploomber (W22)Active • 7 employees • New York
    We are building a cloud platform to help data scientists and engineers develop and scale AI/ML applications. We raised a 4.5M seed round in 2022 and have thousands of active users.
    artificial-intelligence
    developer-tools
    machine-learning
    analytics
  • Spade
    Spade (W22)Active • 13 employees • New York
    Spade is the next generation of fintech infrastructure. We’re building a financial data enrichment API purpose built to empower our customers to uncover the truth hidden within their transaction data. We use our vast, ground-truth merchant data set to decipher cryptic transactions, helping customers underwrite, detect fraud, build better banking infrastructure and get a unique understanding of their users’ spending habits.
    developer-tools
    fintech
    machine-learning
  • IoTFlows Inc
    IoTFlows Inc (W22)Active • 2 employees • Atlanta, GA
    IoTFlows provides comprehensive visibility and valuable insights into manufacturing shop floors. Leveraging artificial intelligence to monitor and analyze the performance of machines based on their vibration and acoustics data, we help manufacturers to identify issues and inefficiencies in the production process and make data-driven decisions to improve performance.
    artificial-intelligence
    deep-learning
    machine-learning
    iot
    manufacturing
  • PINA
    PINA (W22)Active • 25 employees • Jakarta, Indonesia
    At PINA, we are designing and building the future of personal finance with a mission to help everyone achieve financial freedom by providing products and advice that make complicated financial decisions simple and relevant. We seamlessly integrate money management and investing into one app to allow people to manage their finances holistically. Users can see their net worth, monthly cash flow and how their budget has changed over the past several months. All of this is automated and designed to help them achieve the savings goal which they have set . In addition to money management, we focus on making investing easy with pre-built portfolios and automatic rebalancing. When you sign up for an account, it offers the option to pick an expertly built portfolio, or you can choose to build your own.
    fintech
    machine-learning
  • Lifecast
    Lifecast (W22)Active • 2 employees • Palo Alto
    We make tools for state-of-the-art 3D VR video, which fix motion sickness for a more comfortable and immersive experience. Our team's experience includes building VR cameras at Facebook, and robot perception systems at Lyft and Google X.
    machine-learning
    robotics
    virtual-reality
  • Axis
    Axis (W22)Active • 15 employees • New York
    Axis is a knowledge base of government regulations and officials that helps large companies do business in foreign markets. For example, if you want to operate in Saudi Arabia - our software tells you which laws you need to comply with and which officials you need approvals from. We currently cover major markets in Europe, Middle East, and Africa
    machine-learning
    b2b
    subscriptions
    regtech
  • Dart
    Dart (W22)Active • 5 employees • San Francisco
    Dart is project management powered by AI. Built in partnership with thousands of founders and their startups, Dart typically saves teams a third of their project management time through AI-based automation, intuitive shortcuts, and integrations. It's used by growing teams that are iterating quickly across a diverse set of tasks in engineering, design, sales, and more.
    developer-tools
    generative-ai
    machine-learning
    productivity
    ai
  • Beam
    Beam (W22)Active • 4 employees • New York
    Instantly run code on GPUs, deploy scalable web APIs, mount storage volumes, and schedule cron jobs. Beam is your swiss army knife for running code on the cloud.
    artificial-intelligence
    developer-tools
    machine-learning
  • Armilla AI
    Armilla AI (W22)Active • 7 employees • Toronto, Canada
    Armilla AI is a Quality Assurance platform for models allowing enterprises to govern, validate, test, and monitor any and all models across the enterprise in a reliable, consistent, and repeatable manner. We make Responsible and Trustworthy AI a reality.
    machine-learning
    regtech
    ai
  • LanceDB
    LanceDB (W22)Active • 4 employees • San Francisco
    LanceDB is a new open-source vector database that can support low-latency billion-scale vector search on a single node. Built around a new columnar data format, LanceDB makes it incredibly easy to build applications for generative AI, recsys, search engines, content moderation, and more.
    aiops
    machine-learning
    data-engineering
  • Lexter.ai
    Lexter.ai (W22)Active • 18 employees • São Paulo, Brazil
    Lexter is the first legal LLM company in Brazil, already working with 3 out of the top 5 law firms in the Country
    machine-learning
    legaltech
  • Bobidi
    Bobidi (W22)Active • 15 employees • Los Gatos, CA
    Bobidi helps AI companies validate the AI models very fast and improve them 10x more efficiently. It is critical because AI companies are having hard times predicting the unknown-unknowns and thus how the model will perform in the real world. Our underlying magic is that we run a global gamified community that is incentivized to test and find the edge cases that the model missed. The whole process would be 10x more efficient than the industry norm that takes as long as a couple of months. This is the mashup between the community and AI, the areas we (the co-founders) are the experts of, bringing experiences from Facebook and Google & Niantic, respectively. Both have exited before as CEO (Social Commerce Startup in Korea) and CTO (AR Startup acquired by Niantic), respectively.
    aiops
    generative-ai
    machine-learning
    nlp
    ai
  • Sribuu
    Sribuu (W22)Active • 20 employees • Jakarta, Indonesia
    Sribuu is an AI-powered personal financial advisor that has helped >250k Indonesians double their monthly savings in their first month of using the app. We help our users make better money decisions with our wealth management tools and give a personalized saving advice based on their financial habits. We launched in January 2021, and grew by around 50% MoM.
    fintech
    machine-learning
    consumer
  • HypaHub
    HypaHub (W22)Active • 6 employees • Sunnyvale, CA
    HypaHub is a Cloud-Based Bioinformatics and AI Platform. It is the first HIPAA-compliant Bioinformatics SaaS that runs natively on users' clouds, providing both operation- and price-transparency. Our product is a one-stop shop to access complex technologies designed for scientists building data applications or performing data analytics to extract insights. It automates the creation and manages the operation of computing resources, eliminating the need for enterprises to set up and maintain a high-end R&D cloud infrastructure.
    machine-learning
    biotech
    analytics
  • Cerebrium
    Cerebrium (W22)Active • 4 employees • New York
    Cerebrium is a platform to deploy machine learning models to serverless GPUs with sub-5 second cold-start times. Customers typically experience 40% in cost savings when compared to using traditional cloud providers and can scale models to more than 10K requests per minute with minimal engineering overhead. Simply write your code in Python and Cerebrium takes care of all infrastructure and scaling. Cerebrium is being used by companies and engineers from Twilio, Rudderstack, Matterport and many more.
    machine-learning
    infrastructure
    ai
  • DynamoFL
    DynamoFL (W22)Active • 20 employees • San Francisco
    DynamoFL is the most private solution for enterprise AI. Achieve best-in-class and compliant AI at the fraction of the time and cost.
    machine-learning
    privacy
    data-engineering
  • Nyckel
    Nyckel (W22)Active • 3 employees • CA
    Use Nyckel to train and integrate state of the art machine learning into your application. Our ML platform can be used by anyone and it only takes minutes to train your first model. Once trained, your functions is immediately deployed to production grade infrastructure.
    artificial-intelligence
    machine-learning
    api
  • Momento
    Momento (W22)Active • 18 employees • Mexico City, Mexico
    In Momento we are going through a challenging regulatory process to become a fully-licensed insurance carrier. By doing so, we will be able to underwrite risk, set prices and, ultimately, become owners of the product. Once approved, around summer 22, we will be in a great position to size the $13bn untapped opportunity of +30 Mn uninsured vehicles – just in Mexico! As we will be able to attack the main pain points in the market: i) antiquated underwriting models and ii) payment conditions only adapted for the affluent. To succeed, we have assembled an elite team with both innovative and experienced profiles. We are three cofounders, two ex-McKinsey and one ex-P&G, and we managed to attract two heavyweights of the Mexican insurance industry: the previous CUO of Zurich Mexico and the previous CFO and VP of Finance of ING and AXA Mexico.
    fintech
    machine-learning
    consumer
    insurance
  • Starling
    Starling (W22)Active • 5 employees • Houston, TX
    Starling is building a urine diagnostic remote patient monitoring platform that seamlessly integrates into anyone's bathroom routine. By detecting early changes in a patient's urine using our toilet indwelling mass spectroscopy device, our platform is aiming to prevent hospitalizations from numerous conditions like recurrent UTIs, BPH exacerbations, or diabetes. We do this while creating significant new annual revenues for our clinician partners from remote patient monitoring reimbursements without requiring any significant changes in a staff's day to day schedule.
    machine-learning
    medical-devices
    digital-health
  • Rosebud Biosciences
    Rosebud Biosciences (W22)Active • 3 employees • San Francisco
    Rosebud Biosciences accelerates drug development by screening drugs against organoids (micro-organs) that have the same gene mutations as the patients. We partner with therapeutics companies to screen their drugs, and we perform our own drug discovery for rare diseases that have no existing treatments. Our organoids are also fetal-like and enable discovery of novel drug targets for pediatric diseases. This technology was validated at Stanford, published in a prestigious journal, and has already led to the discovery of a drug target in a pediatric heart disease that could not have been found using traditional disease models.
    machine-learning
    pediatrics
    therapeutics
  • Paces
    Paces (S22)Active • 11 employees • New York
    Paces is software for renewable developers to identify the best places to build their projects. Renewable development is growing quickly but 80% of US renewable projects fail because they are built in the wrong places, costing $17B per year. Paces solves this by modeling grid, permitting, and environmental due diligence risks to identify the best places for renewable projects. Paces even integrates location based incentives, like those in the recently passed $370B US Climate Bill.
    machine-learning
    saas
    proptech
    climate
    energy
  • Safer Management
    Safer Management (S21)Active • 5 employees • Dallas, TX
    Safer Management sells attendance software to public school districts and colleges. Public schools receive federal funding based on their average daily attendance, and our software ensures they get the money they need. We started Safer Mgmt. 12 months ago after I dropped off my twin boys and experienced inefficiencies with the sign-in process. We are now in 75 public schools and two colleges with annual reoccurring revenue of $621,000. We have 82% margins and are profitable. At scale, we will charge $15 per student per year. There are 70 million public school students in America which is a $1.4 billion dollar market opportunity.
    artificial-intelligence
    education
    machine-learning
  • Lightly
    Lightly (S21)Active • 5 employees • Zürich, Switzerland
    When ML teams send their data to companies like Scale.ai for labeling, most can only afford to label 1% or less of their datasets. But today they don’t have a good way to pick which 1% to label. We help them pick the best 1% of their data to label. By labeling the most representative data, they significantly improve model accuracy at the same cost.
    machine-learning
    data-labeling
  • Medium Biosciences
    Medium Biosciences (S21)Active • 6 employees • Boston
    Our product is a software platform that makes it really easy for industrial biotechnology companies to interface with machine learning models for enzyme engineering. Enzymes power most chemical reactions in nature but usually need engineering to work at industrial scale. Our models can be used to suggest high performing sequences that would have typically taken months of wet lab work to identify.
    machine-learning
    saas
    climate
  • Spoken
    Spoken (S21)Active • 2 employees • New York
    Spoken is a website where users compare buying options for the exact same product across multiple stores. We help our users never overpay online. Dane is a two-time technical YC founder; he sold his previous company, Parklet, to Greenhouse where he was VP of Platform for 4.5 years. Geoff is a Stanford MBA grad and sold his previous company Cabrio Taxi.
    machine-learning
    marketplace
    consumer
    e-commerce
  • CellChorus
    CellChorus (S21)Active • 3 employees • Houston, TX
    At CellChorus, we apply artificial intelligence to evaluate thousands of microscopy videos in parallel to evaluate how immune cells move, interact and perform over time. This allows our customers to discover, develop, manufacture and deliver cell therapies, antibodies, vaccines and other novel therapies faster, at lower expense, and with higher rates of success. Our customers include top-25 biopharma companies and seed-stage biotechs that are developing cell therapies, antibody therapeutics and vaccines (including one of the few companies with an approved CAR T cell therapy). Hear from the team at https://www.youtube.com/watch?v=IE9x_tm0XnI
    ai-powered-drug-discovery
    machine-learning
  • Baubap
    Baubap (S21)Active • 15 employees • Mexico City, Mexico
    Building the first digital bank for the economically vulnerable starting with a mobile lending app for Mexico
    machine-learning
    lending
  • bloop
    bloop (S21)Active • 8 employees • London, United Kingdom
    We've developed an AI chat assistant that can answer any question an engineer might have about a codebase. It turns out most engineers spend more time reading code than writing it, and our tool helps engineers easily navigate and understand unfamiliar codebases.
    machine-learning
    open-source
    ai
  • outloud.ai
    outloud.ai (S21)Active • 5 employees • Miami, FL
    We record conversations that customers have when they are placing orders in drive-thru restaurants, automatically analyze them, and help operators to upsell better or alert them when they are out of stock.
    machine-learning
    saas
    b2b
  • Evidently AI
    Evidently AI (S21)Active • 2 employees • San Francisco
    We are building an open-source standard to monitor ML models in production. The tool is used by enterprise data science teams to operate their models reliably and detect and resolve issues.
    developer-tools
    machine-learning
    b2b
    open-source
  • Protex AI
    Protex AI (S21)Active • 5 employees • Limerick, Ireland
    Tl;dr: We’re building software that monitors existing cameras in the port, logistics, and manufacturing industries to ensure compliance and identify safety issues. At Protex AI, we’re on a mission to protect the industrial workforce! We’re building a proactive computer vision tool for workplace safety - empowering industrial Health and Safety (HS) teams to identify risk and danger before it becomes a problem. 🤕 The Problem: Keeping people safe at work is extremely hard. In the U.S. alone, there were over 5,000 deaths in the workplace in 2019, mainly in the heavy industry space. Serious workplace injuries cost U.S. businesses circa $62 Billion annually. Until now, safety has been reactive, someone has to get injured, and in some cases fatally before something is done about it. ✅ Problem Solved: Protex AI’s platform uses privacy-preserving camera monitoring software to provide companies with an always-on guardian angel, protecting their workforce. The platform plugs into existing CCTV infrastructure and enables HS teams to flexibly translate their document-based safety rules into the real world. Protex AI takes these rules and autonomously audits the customer’s facility to identify areas of high risk and non-compliance. HS teams can access this data via a reporting engine and use it in weekly safety meetings, external safety audits, insurance discussions, and legal claims. The tool integrates seamlessly with existing safety workflows to augment data produced by any manual incident logging system in place.
    industrial-workplace-safety
    machine-learning
    b2b
  • Malloc
    Malloc (S21)Active • 7 employees • Nicosia, Cyprus
    Malloc is a mobile app that monitors and prevents any app from recording you or transmitting your data without you knowing. We sell our app to individuals, enterprises and governments who care about their privacy.
    machine-learning
    saas
    security
  • Cero
    Cero (S21)Active • 10 employees • Santiago, Chile
    At Cero, we solve specific coordination tasks between hospitals and patients, such as appointment confirmations and last minute cancellations, by automatically communicating with patients over WhatsApp. For example, a patient can confirm and reschedule their appointment without needing to call anyone. Almost half of the medical appointments in Latin America are missed because patients simply do not show up. This ranges from missing a regular dentist check to missing an expensive MRI scan. With increasing pressure to improve access to care in developing countries, optimizing communication and coordination with patients is a key task to achieve. This is a massive problem especially in places where most people don't know how to effectively use self-service mediums (or are too busy to use them). We bootstrapped the company and we are profitable. As of August 2021 we have $97K in monthly revenue from 15 clients with a CMRG of 20% in the last year. We have 100% logo retention and we grow with our clients. We are currently coordinating over 600,000 medical appointments every month, just in Chile. This problem represents a $3.5B market opportunity in Latin America only. Latin America has 650M people, each one having an average of 3 medical consultations per year. We charge for every time we effectively communicate with a patient. We plan to handle several coordination interactions with every patient for each consultation, which considers a roadmap of scheduling, confirming, booking, reimbursements, payments, among others. We are a team mixing strong knowledge about the healthcare industry with deep technical skills. Felipe (CEO) is a former dentist that has led deep changes in healthcare payments in Chile. Mauricio (CTO) and Jorge (R&D), both PhD in Computer Science, led the creation of the most advanced Spanish Language Neural Network used daily by scientists and practitioners in LatAm (BETO: Spanish BERT). In a weekend project, Mauricio and Jorge automated the communication with students attending a summer school obtaining impressive engagement. Felipe was struggling with contacting his patients to coordinate appointments, and saw a big opportunity in this technology. The three together have designed and run a solution that as of 2021 is coordinating over 600,000 patients per month in their home country, Chile.
    machine-learning
    consumer-health-services
    b2b
    nlp
  • Jovian
    Jovian (S21)Active • 6 employees • Bengaluru, India
    Jovian is an online university for software development and data science. We offer practical and industry-focused programs that help professionals learn technical skills, build real-world projects, and advance their careers. Students learn practical skills, build real-world portfolio projects, and undergo job readiness training. Our tutors offer 24x7 guidance & mentorship over Slack & Zoom. Students also get access to jobs with 200+ hiring partners.
    ai-enhanced-learning
    developer-tools
    education
    machine-learning
  • Lariat Data
    Lariat Data (S21)Active • 2 employees • New York
    Lariat is a Continuous Data Quality monitoring platform to discover data bugs before your consumers do. Ensure data products don’t break even as business logic, input data and infrastructure change. Use Lariat to define and then automatically extract, store and visualize data quality metrics on raw event-level data through to delivered data products.
    machine-learning
    big-data
    data-engineering
  • Sleek
    Sleek (S21)Active • 5 employees • Toronto, Canada
    Sleek provides B2C businesses with a custom browser extension that works on both mobile and desktop. With the extension, you can: - Auto-complete checkout for users with an Apple-pay-like experience tied specifically to your brand. - Offer Honey-like couponing to help your users save money. - Grant users extra cashback at 1000's of online stores, funded by Sleek. Your users spend time and money in the browser. With Sleek, you can be there for them.
    fintech
    machine-learning
    e-commerce
  • Concord Materials
    Concord Materials (S21)Active • 7 employees • New York
    SaaS automation tools, financing and marketplace for bulk construction materials
    fintech
    machine-learning
    marketplace
    insurance
    enterprise
  • Mindstate Design Labs
    Mindstate Design Labs (S21)Active • 7 employees • San Francisco
    Developing the next generation of psychedelic therapeutics for mental health indications. We design novel altered states of consciousness using machine learning, human experiential data, and molecular pharmacology.
    artificial-intelligence
    machine-learning
    mental-health-tech
    biotech
    therapeutics
  • Openlayer
    Openlayer (S21)Active • 6 employees • San Francisco
    Track prompts and models. Test edge cases. Catch errors in production. Evaluate your AI with one-line of code.
    aiops
    artificial-intelligence
    developer-tools
    generative-ai
    machine-learning
  • PipeBio
    PipeBio (W21)Active • 3 employees • Aarhus, Denmark
    Pipe|bio is the bioinformatics cloud for antibody / peptide screening & drug development. We enable scientists to analyze and manage massive amounts of DNA sequencing data themselves without the need for bioinformaticians or programmers. The software is highly visual and enables you to overlay and filter information from different sources across your organization; be it assay data, sequence data or other process metadata. Insights from past results can be used to guide new experiments and they get better as you upload more and more data. Team leads get oversight and these capabilities combined empower organizations to find better drugs, faster. We believe that science moves faster when scientists can curate and analyse their own data.
    ai-powered-drug-discovery
    machine-learning
    saas
  • MindFi
    MindFi (S21)Active • 25 employees • Singapore, Singapore
    MindFi is an app that reduces burnout and improves mental health for employees. We sell to companies in Asia such as Deutsche Bank, KPMG, PatSnap, Visa. Our annual revenue is US $150k to date and we’re growing 53% month on month. The team is headquartered in Singapore and consists of Bjorn, (ex-Zendesk product manager), psychologist Anita Sadasivan (UMich alum, ex-Raffles Hospital), Leon 2X startup founder with 2 exits and Gangeshwar, an award-winning AI engineer.
    machine-learning
    mental-health-tech
    b2b
  • Polymath Robotics
    Polymath Robotics (S22)Active • 9 employees • San Francisco
    Polymath is building a general autonomy stack for cautious vehicles. Our software allows any industrial vehicle - whether it's a tractor in a field or a bulldozer in a mine, drive itself. We bundle together AI, ML, Controls, ROS, Safety and best-in-class deployment practices to enable our customers to tell automated vehicles to do via a REST API. We're on more robots than we have engineers, are seeing our revenue (and robotic fleet) grow rapidly, and are looking for folks who want to help automate the world.
    hard-tech
    machine-learning
    robotics
    unmanned-vehicle
    ai
  • Toko
    Toko (W22)Active • 4 employees • New York
    Toko helps English learners in East Asia achieve speaking fluency. Through our mobile app, learners engage in short, realistic conversations with an AI and receive feedback on their grammar. With over 150 topics, learners can practice real-world scenarios ranging from small talk to workplace discussions. Toko offers a low-pressure environment to help learners build up their confidence. We make language fluency accessible to everyone - not just those with the means to meet 1:1 with a tutor. In Taiwan (our first market), Toko is ranked #3 in the App Store for Education!
    ai-enhanced-learning
    education
    generative-ai
    machine-learning
    consumer
  • Metal
    Metal (W23)Active • 5 employees • New York
    Metal does machine learning embeddings as a service. Embeddings are what AI models use to represent meaning. They capture the relationship between concepts, and they’re at the heart of every generative AI application, like ChatGPT and DALL-E. As the data format of machine learning, embeddings are critical to every AI application. But there are no existing tools that help developers use them. Metal is a fully managed service for developers to build applications with embeddings. We handle all of the infrastructure, provide out of the box operations, and simple APIs. Skip the complexity, ship faster with Metal 🤘
    artificial-intelligence
    machine-learning
    b2b
    ai
    ml
  • Unify
    Unify (W23)Active • 10 employees • London, United Kingdom
    We're on a mission to unify all ML frameworks, and enable automatic code conversions between frameworks.
    developer-tools
    machine-learning
    open-source
    api
    ai
  • Luca
    Luca (W23)Active • 4 employees • San Francisco
    Pricing Strategy is one of the most powerful levers that retailers have at their disposal to create growth, yet it is underleveraged. Most retail pricing teams settle for making decisions in spreadsheets, shooting in the dark, and working backward from a cost-plus margin target, leaving a LOT of money on the table. Our founders experienced these problems at scale when they built pricing tech at Uber that made Uber a billion dollars in profit a year. They realized that retail was lacking the same quality and sophistication of price tooling. So, they built Luca. Luca is an AI-powered co-pilot for retail operators, which constantly identifies revenue and profit headroom, makes recommendations for price adjustments and saves countless work hours along the way. Luca is backed by Y Combinator, Menlo Ventures, and others.
    machine-learning
    saas
    e-commerce
    retail
  • Persist AI
    Persist AI (W23)Active • 6 employees • Woodland, CA
    It takes 5 years for pharma to develop long lasting drug injections for chronic diseases like cancer and diabetes. Persist uses AI-driven automation to reduce formulation development time down to 2 years, a ~50% reduction.
    machine-learning
    robotics
    microfluidics
    nanotechnology
    therapeutics
  • RedBrick AI
    RedBrick AI (W22)Active • 13 employees • Claymont, DE
    RedBrick AI's mission is to accelerate the adoption of artificial intelligence in radiology by building world-class software infrastructure. Currently, we are focused on helping radiology AI teams prepare high-quality datasets to train their algorithms. Radiology data, such as CT and X-ray scans, is an incredibly important source of truth in healthcare delivery. In fact, over 90% of all healthcare data is medical imagery! However, the global radiology workforce is overburdened. In the UK, for example, only 2% of radiology departments are able to fulfill their reporting requirements, and this trend is reflected worldwide. The acute state of radiology, coupled with the abundance of data, makes the use of AI in radiology a prime candidate. In 2022, $5.6 billion was invested in the development of AI in healthcare! However, a key hindrance to further adoption is the lack of sophisticated tools to build and deploy AI algorithms in clinical environments. This is the problem we’re focused on at RedBrick AI. We're a remote team based out of USA, Europe, and India, and are backed by leading institutional investors like Y Combinator, and Sequoia Capital.
    aiops
    machine-learning
    healthcare
  • DAGWorks Inc.
    DAGWorks Inc. (W23)Active • 2 employees • San Francisco
    At DAGWorks Inc. our goal is to change how data + ML + LLM teams are staffed and operate. We’re building an open core SaaS platform to streamline development and operation of data, ML, & LLM pipelines in a collaborative, self-service manner, utilizing a company's existing MLOps and data infrastructure. We believe self-service for Data Practitioners is the future because it enables domain modeling experts the velocity to iterate on pipelines & models without hand-off, which is key for businesses using ML/AI to differentiate themselves. Unless you’re a big tech company or someone like Stitch Fix that can afford a platform team, staffing teams with high ratios of engineers, or finding unicorn data scientists that can build pipelines is your only option; it not only slows time to value, it makes operating ML/AI expensive. We’re here to change that. Think simple python that enables a low software engineering bar to describe what should happen, and then with some extra metadata, generates the workflow code, and that also consolidates several MLOps tools into a single platform, all in a self-service manner. It’s functional and usable by junior and senior folks alike.
    developer-tools
    machine-learning
    b2b
    open-source
    data-engineering
  • HomeRoom
    HomeRoom (W22)Active • 25 employees • San Jose, CA
    Homeroom helps investors provide affordable housing while making a 22% ROI. We do this by sourcing properties, arranging capital, managing construction, vetting tenants and collecting rent by the room. To date, Homeroom has brought on 85 property investors, growing 6X annually, are bringing in 420K in annualized net-revenue How it works: We help investors buy homes in cities that are attractive to young people, but lack affordable housing options. We then renovate and after about 20 days, the home is ready and we find qualified renters by the room. We launched in 2018 in Kansas City with 1 home. We now have 105 homes in 31 cities. In 2021, we grew rental GMV to $1.8M (300% YoY growth). Our average rent across every property is $458, which is about 50% lower than market comps, and our investors see returns up to 50% higher. We are HomeRoom. Johnny is the financial analyst/domain expert. Thomas is a cereal entrepreneur with a PHD in ML, and Mike hacked growth for Airbnb and Facebook.
    machine-learning
    real-estate
    proptech
    nlp
    data-engineering
  • CatX
    CatX (S23)Active • 2 employees
    CatX is a digital marketplace connecting insurance carriers with institutional investors to trade and transfer insurance risk efficiently. We help to make insurance risk models understandable and accessible for asset managers so they can unlock new sources of returns. In addition, we streamline and digitalize the entire risk transfer process, so insurers can get faster, cheaper access to capital from our partner funds.
    machine-learning
    finance
    analytics
    insurance
    investing
  • Mach9
    Mach9 (S21)Active • 12 employees • Pittsburgh, PA
    Mach9’s geospatial production software helps surveyors transform complex 3D geospatial data into 2D and 3D engineering models 30x faster and at half the cost. We use leading computer vision software to generate engineering-grade maps for entire utility and transportation networks needed to build and maintain infrastructure globally.
    artificial-intelligence
    machine-learning
    computer-vision
    infrastructure
  • Meter Feeder
    Meter Feeder (W16)Active • 4 employees • Pittsburgh, PA
    Cities are losing billions of dollars trying to price the curb for shared vehicles (Car2Go, Scoot, FedEx). Meter Feeder enables traditional and autonomous vehicles to pay for parking with no human interaction, so cities can make money, and fleets can remain compliant.
    machine-learning
    govtech
    unmanned-vehicle
  • Waterplan
    Waterplan (S21)Active • 30 employees • San Francisco
    Waterplan is the world’s leading climate platform to measure, respond, report, and monitor companies increasingly changing climate water risk. Customers include multinational companies like Coca-Cola, Diageo, Colgate & Ab InBev. The platform combines companies’ operational data with local water satellite imagery to provide a continuously updated financial assessment of water risk. Based on that, it offers tailored mitigation and adaptation opportunities, from conventional infrastructure to nature-based solutions. The company was founded by a team of tech and water 2nd-time entrepreneurs with two exits and almost ten years of experience working for Fortune 500 companies in water projects. Early investors include YCombinator, Giant Ventures, David Helgason, Leonardo DiCaprio, Richard Branson's family, Manu Ginobili, among others waterplan.com
    machine-learning
    saas
    b2b
    climate
    climatetech
  • UpTrain AI
    UpTrain AI (W23)Active • 4 employees • Bengaluru, India
    UpTrain is an open-source LLM evaluation tool that quantifies the performance of LLM applications on aspects like factual accuracy, relevancy, guideline adherence, tonality, summarization quality, etc. We provide a single-line integration to seamlessly run these evaluations and provide real-time dashboards to analyze the results along with insights for cohorts of low model performance.
    developer-tools
    generative-ai
    machine-learning
    open-source
    ai
  • Slingshot
    Slingshot (S23)Active • 4 employees • San Francisco
    Slingshot is building the next generation of video games with characters and mechanics powered by generative AI. Our intelligent NPCs will be more fun to play with than real people. Created by Stanford CS graduates with a lifelong passion for gaming, our approach sets the stage for a new genre of video games. We have research experience at Stanford on multi-modal LLMs, and at big tech such as TikTok and Amazon. We're now super excited to be creating this next generation of video games!
    generative-ai
    machine-learning
    entertainment
    gaming
    ai
  • Defog.ai
    Defog.ai (W23)Active • 5 employees • Mountain View
    Defog lets your business users query data in seconds, using everyday language. We are powered by SQLCoder – our state of the art open-source model that can search and visualise structured data (like SQL databases or Data Warehouses), and can be further fine-tuned and and deployed on-prem on your servers.
    developer-tools
    generative-ai
    machine-learning
    open-source
    enterprise
  • Boundary
    Boundary (W23)Active • 2 employees • Seattle, WA
    We build tools to make building, testing, and analyzing LLM apps easier Reach out at founders@boundaryml.com to learn more.
    generative-ai
    machine-learning
    api
    search
    ai
  • FiddleCube
    FiddleCube (W23)Active • 2 employees • San Francisco
    FiddleCube helps developers fine-tune & deploy LLMs with synthetic data. We use AI to generate private, high-quality datasets for customers who want custom LLMs but don’t have the resources to create annotated training datasets for fine-tuning & reinforcement learning.
    artificial-intelligence
    developer-tools
    generative-ai
    machine-learning
    data-science
  • 222
    222 (W23)Active • 6 employees • Los Angeles, CA
    222 is a full-stack social experiences platform to generate real-life experiences at curated hyperlocal venues where we can reliably predict you will like both the people & place.
    artificial-intelligence
    machine-learning
    marketplace
    consumer
    social
  • 1stCollab
    1stCollab (W23)Active • 5 employees • San Francisco
    1stCollab is an AI-powered influencer marketing platform for helping brands optimize performance. We are the first platform that leverages ML to accurately predict a creator's performance and use those predictions to recruit the most relevant, best-performing creators for a brand’s upcoming influencer campaigns. Our founding team collectively spent 30 years at Pinterest building up most of its Discovery systems, so are experts at finding the perfect set of creators for optimizing engagement. Let us know if we can help you run an influencer marketing campaign and see how our brands have reduced their CAC by over 70%!
    machine-learning
    marketplace
    social-media
    marketing
    creator-economy
  • Strong Compute
    Strong Compute (W22)Active • 8 employees • Sydney, Australia
    Strong Compute is building the future of Cloud Computing, priced by performance not consumption. Our software and hardware optimizations speed up neural network development 10x-1000x, file transfer 1000x, instance start time 10x. We're starting with AI and are aimed at the $500B cloud market.
    artificial-intelligence
    machine-learning
    cloud-computing
  • Slope
    Slope (S21)Active • 16 employees • San Francisco
    Accept and reconcile B2B payments seamlessly.
    fintech
    machine-learning
    payments
    fraud-detection
  • Trident Bioscience
    Trident Bioscience (S20)Active • 1 employees • Mountain View
    Trident Bioscience builds tools to expedite the discovery and optimization of useful proteins. Our technology first applies predictive models of protein structure and function to generate sets of potentially active protein sequences. We then apply our state-of-the-art sequence optimization algorithm to design gene libraries capable of testing these candidates extremely quickly and affordably. By combining these technologies, we're closing the design-build-test loop of protein optimization and cutting the total cycle time to help bring synthetic proteins to market faster than ever before.
    hard-tech
    machine-learning
  • Abalone Bio
    Abalone Bio (W20)Active • 12 employees • Emeryville, CA
    Abalone Bio developed a technology to find antibody drugs that activate and modulate cell surface receptors, the “antennae” on cells that help convert chemical signals into cellular responses, like growth. Antibodies are a growing class of drugs that have tremendous safety and efficacy advantages over small molecules; 7 of the top 10 selling drugs are antibodies, earning an average of $7B in revenue. However, antibodies- especially ones that activate and modulate cell surface receptors- are hard to find. Abalone Bio expands the playing field for antibody therapeutics and enables us to previously access treatments for untreated diseases. We have already discovered a novel antibody that activates a non-opioid receptor that produces analgesia. We are developing this antibody into a treatment for neuropathic pain – a medical condition that currently is treated with drugs like addictive opiates. The same molecule is also a potential treatment for inflammatory and fibrotic diseases, all 1B+ markets.
    machine-learning
    synthetic-biology
    drug-discovery
  • Promoted.ai
    Promoted.ai (W21)Active • 10 employees • San Francisco
    Promoted optimizes top online marketplaces. For example, on Airbnb, we would sort search and promote the best listings at the top to increase revenue. We are building a first-party-everywhere ad network. We are all ex-Facebook and Google ads engineers, and we have built this before together.
    machine-learning
    marketplace
    b2b
    e-commerce
  • PredictLeads
    PredictLeads (S19)Active • 12 employees • Ljubljana, Slovenia
    PredictLeads provides structured data on companies. Using our data Sales teams can discover companies in their buy mode, Quant funds know when to perform trades and VCs can predict when a startup will be raising a new round. PredictLeads cuts down their market research time. Our goal is to structure the sea of public information on companies.
    machine-learning
  • Shiru
    Shiru (S19)Active • 4 employees • Emeryville, CA
    ai-powered-drug-discovery
    cellular-agriculture
    machine-learning