Built for the world’s fastest-growing teams. Chalk helps enterprises power cutting-edge AI with fresh, real-time data.
Book DemoFraud detection, Recommendations
MoneyLion uses Chalk’s real-time data platform to unify ML development, accelerate feature delivery, and reduce time-to-production. By centralizing experimentation, serving, and governance, MoneyLion scales AI applications across fraud prevention, budgeting, and personalization.
Case StudyRecommendation Systems
Apartment List leverages Chalk’s real-time feature platform to deliver an individualized and intuitive apartment search experience. By unifying fresh data from SQL, streams, Python UDFs, Expressions, and APIs in real time, Apartment List runs sub-10ms queries for its dynamic recommendations as renters refine their search.
Case StudyChalk has transformed our ML development workflow. We can now build and iterate on ML features faster than ever, with a dramatically better developer experience. Chalk also powers real-time feature transformations for our LLM tools and models — critical for meeting the ultra-high freshness standards we require. Beyond the product, the Chalk team has been a great partner: responsive, deeply knowledgeable, and committed to helping us move faster.
Jay FengML Engineer
Fraud Detection
Verisoul leverages Chalk’s real-time feature platform to combat evolving fake account threats, shipping detection updates 10x faster and using fresh inference-time data for 4x more accurate fraud detection. With complete auditability and reduced engineering overhead, Verisoul maintains speed, accuracy, and transparency—keeping critical platforms secure at scale.
Case StudyWait-Time Predictions
Using advanced AI, Vital transforms complex health record data into easy-to-use, personalized interfaces that inform and engage over one million patients per year. After deploying Chalk, Vital was able to stop wrangling infrastructure and focus on improving its models, launching new products, and delivering a world-class patient experience.
Case StudyWe fully replaced our legacy URL candidate suspiciousness scoring model with a more powerful in-house one, shipped in record time! We're optimistic our feature ideation-to-production cycles will only get faster as we 10x our scale this quarter. Huge thanks to the Chalk team for your amazing support—this wouldn’t have happened so quickly without them!
Justin D'SouzaMachine Learning Engineering