Feature store with 2 years of point-in-time history. Privacy-preserving clean room. Your model. Your ownership. 500ms inference.
No data pipelining. No feature engineering overhead. No privacy headaches. Just production-grade signals ready to train on.
Access 800+ encrypted ecosystem-signal features via real-time APIs or bulk pulls, inside your own environment.
2 years of as-of-day snapshots. Train on what was actually known on day zero, not today's hindsight.
Every feature versioned. Full lineage from raw signal to derived feature to model input. Audit-ready.
Build and test models on combined LattIQ signals + your labels in a privacy-preserving clean room.
Search 800+ signals. Engineer features on your labels. Train multiple models. Monitor performance in production. All without leaving LattIQ Studio. Lineage and versioning are automatic.
Your training labels plus 800+ ecosystem signals, back-tested on clean as-of-day data, deployed and monitored in production.
Search 800+ ecosystem-signal features across 9 signal families with 2 years of point-in-time history - no pipelines, no feature-engineering overhead.
Pull features via real-time API or bulk export into your own cloud. Versioning and lineage are automatic and audit-ready by design.
Train on combined LattIQ signals + your labels in a privacy-preserving clean room. You own the final model; neither side sees raw data.
Deploy hosted on LattIQ or on-prem at 500ms inference, with automated drift detection and signal-health monitoring in production.
One feature store with 2 years of point-in-time history. Privacy-preserving clean room. Your model. Your ownership. 500ms inference.
Explore the Signal Catalogue →800+ production-ready signals on 500M+ users across 9 signal families - Identity & Persona, Transactions & Commerce, Financial Profile, Device & Apps, Telecom & Calling, Logistics & Location, Offline Footprint, Network Graph, and Business & B2B. All aggregated at source and versioned, with full lineage for audit.
Yes - that's the whole point. You bring your labels, we provide the signals and a privacy-preserving clean room. Build models for acquisition, risk, fraud, propensity, churn - or any outcome worth predicting. You choose which signals to use and how to transform them, you own the model, and all the tooling for an end-to-end ML workflow is built in.
We don't centralize or store this data - every signal is pulled fresh on demand for each request. Refresh cadence varies from partner to partner, but a signal is never more than 3–14 days old from any source.
Yes. 24 months of point-in-time history means every snapshot reflects what was known as of that date. You can backtest on realistic, reproducible data with no look-ahead bias or leakage from the future.
Within a week, you get a one-click-deployable model that delivers incrementality over your current decisioning. Short on bandwidth or expertise? Our AI agents handle the trial-and-error loop, compressing it to <12 hours to deliver a deployable, high-performance model.