The AI-native context layer for enterprise data.
Turn fragmented enterprise data into Chrons — chronological, entity-centric event streams. The long-term memory for enterprise AI and agents.
Enterprise AI is starving for context
Your data is scattered across warehouses, lakes, and dozens of SaaS apps. Transformers and agents reason over sequences in time — but enterprise data lives in disconnected tables and snapshots.
So AI/ML teams rebuild the same brittle, incomplete, leak-prone timelines by hand — inconsistent, slow, and impossible to reuse. The bottleneck to AI value isn't the model. It's getting the data AI-ready.
One universe. Any lens. Time as a first-class axis.
A Chron is a chronologically ordered, timestamped event stream centered on any entity — customer, rep, shipment, SKU, machine, agent. Store the event universe once; project it per entity. Two serving surfaces: real-time context for inference, and leakage-free, point-in-time exports for training.
Entity-lens projection
The entity is a variable. The same universe re-centers on whichever entity you choose — Chrons stay consistent, with no copies to drift.
Cadence is signal
The gaps and acceleration between events are captured natively, not discarded. Shrinking deltas are a “vibe shift” that AI transformers can attend to.
Leakage-free truth
Every attribute as it was, when it was. No future facts bleed into training or inference — reproducible, audit-ready serving.
As-of-correct history
Best-effort backfill, as-of-correct from connection forward. We mark unknown rather than fabricate the past — and Chrons sharpen as we accumulate.
See the timeline a transformer sees
The Entity Lens viewer is an interactive product feature, live. Pick an entity and watch one event universe re-center as that entity's Chron — then view the same Chron three ways:
- Timeline — the cross-system event stream, for humans.
- JSON — the canonical Chron, for models.
- Text — the LLM-ready context, for AI.
Drop in your email + AI context needs and it opens in a new view — no demo call required.
One Chron, every serialization.
The churn you can't see coming
Customers don't churn overnight — they degrade across systems. A usage dip here, a support ticket there, sentiment slipping, billing slowing. No single tool sees it at once. It's the boiling-frog problem.
The Chron makes the whole cross-system timeline legible to a transformer — surfacing subtle vibe shifts well before the cancel point.
A thin, use-case oriented, churn-risk endpoint and app built on general-purpose Chron primitive for the technology-light enterprise buyer.
The value is net revenue retention — hard dollars saved, CFO-legible. By a founder who has built for such use cases multiple times before.
Agents arrived. The data structure didn't.
Data warehouses and lakes were built for BI and dashboards — dimensional databases were never for feeding attention-based models. The open Chron spec is designed for this and adoption is the goal. Here's what compounds underneath it:
Bitemporal & append-only
As-of-correct entity resolution across every source — more accurate and more valuable with every event ingested.
Your connected data is the asset
Leakage-free point-in-time truth only accumulates by being there as it happened. Every day a customer is connected widens this gap.
The context primitive
The Chron is what your RAG and agent stack retrieves for context. We make RAG better, not obsolete. Own the unit, own the workflow.
Open spec. Commercial engine.
The Chron spec and a reference SDK go open — every integration is a new seed. The accumulating identity graph, connected data and entity-Chrons stay in the engine.
Built this very thing before
- Built Shopify's first at-scale GenAI CS agent for a 2,000-person support org — the beachhead use case, shipped.
- At Wayfair, built ML stack behind $800M ad spend; lead scoring for a 400-person sales org and churn prevention for an 2000-person CS team.
- 0→1 build of Home Depot's in-sourced ad-server; doubled Home Depot's ad-network revenue to $150M; tripled ad margin.
- Multiple patents in data & ML/AI space. Technical founder with investment-banking & finance background.
“I know this buyer, this pain, and how to ship this.”
If your AI roadmap is moving slower than your ambition — let's talk.
Explore Chrons for your data
Build the context substrate your enterprise AI workflow will need. Let us walk you through the demo and explore next steps.
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