01 - Sources
It listens.
Pull raw, unstructured signal from your business systems. Tickets, internal docs, Slack, Confluence, merge requests, recordings, websites.
Why Train
Content rots. Train fixes that.
Most AI projects fail because the content goes stale. Articles drift, runbooks rot, the agent answers from yesterday. Train solves that. Knowledge stays current on autopilot. Procedures stay ready without anyone writing a script.
How Train works
Two senses. One pipeline.
Living Knowledge. Your knowledge, automated.
A three-step pipeline. Each step does one job.
02 - Content Library
It maintains.
Organizes and deduplicates the result. This is the grounding data the AI uses to answer.
03 - Surfaces
It serves.
Publishes the human-readable version across every surface that needs it - embedded inside the agent, served back to the team, available to every other system on autopilot.
Feedback loop
The support team is your highest-quality signal. Team Assistant captures every accepted draft, every override, every edit, and feeds it back into the Library. The loop learns from the people who already know the answer.
Living Context. Meaningful actions, captured.
Runbooks, but agentic. Defined once, run with permission.
Capture procedures.
Reset a password. Check an order. Trigger a renewal. Fire an in-app notification at the right moment. Same way you would write a runbook.
See it in DeployConnect to your stack.
CRM, billing, ERP, support tools, custom APIs. The agent does not invent actions. It runs the ones you defined.
See all connectorsPermission every step.
What the AI can do alone, what needs human approval, what is off limits.
See the trust architectureInside Train
Sources in. Knowledge out.
Plug in any source. The Library maintains itself on autopilot, and the procedures defined here run across every customer moment in Deploy.
Your AI gets smarter every day. Without anyone editing a single article. Or writing a single script.
The Library
One Library. One source of truth.
Every signal flows into one structured Library - merged, deduplicated, labeled. Your team reviews suggested edits, accepts or rejects them in one click, and audits the full history of every change. When the agent gives an answer, this is where it came from. Non-ambiguous, always current, fully traceable.
Next in the loop
Phase 02
Test
Every role, every skill, before a customer sees it.
See it applied See Train in action on Acquisition
See Train against your knowledge.
Plug in your sources. Watch the Library and the Help Center build themselves. No edits, no scripts.