Way to win 02 / Agent Foundry
Build AI from your best work.
Give agents your knowledge, memory, and real corrections. Test the whole job. Ship the version that wins.
The Guardian joins the build line, so every miss becomes a test and every release gets stronger.
The level today
Generic AI does not know your business.
A base model can write. It does not know how your best people solve a refund, review a claim, or recover when a tool fails.
Context gets lost
Useful knowledge sits across docs, systems, and people.
Tests stop at chat
A good answer does not prove the whole agent can finish the job.
Lessons disappear
Real corrections rarely make it back into the next release.
Play the path
Watch Emu turn the hard part into a clear win.
Pick a step or let the level run. The Guardian stays in the loop from the first move to the proof.
AGENT FOUNDRY
Emu is on the move.
release candidate
Refund Agent v7
42 tests passed · Guardian checked
Choose a stage
Three easy moves
Start small. Get the win. Keep moving.
Feed the real work
Bring approved knowledge, memory, traces, corrections, and hard cases into one build line.
Train and try
Build candidates, test the full agent, and let the Guardian explain every miss.
Ship the winner
Release only when the new version beats the old one without breaking what already works.
The prize you can hold
See the product, not just the promise.
Every path ends in a useful record your team can open, share, and act on.
RELEASE CANDIDATE
Refund Agent / RC-007
- Whole-agent trials
- 94 / 100
- Policy checks
- 100%
- Explanation score
- 96%
- Old wins kept
- 318 / 318
›42 real corrections learned
›7 recovery paths tested
›Guardian release gate passed
What your team gets
Less friction. More AI moving forward.
Real
Work in
Build from the jobs your company actually does.
Whole
Agent tests
Test tools, memory, policy, and outcomes together.
Best
Version out
Compare candidates and ship only the winner.
Why Trinitite
The Guardian makes this more than a nice dashboard.
One closed loop
Knowledge, memory, training, evals, explanations, and release control stay connected.
Guardian-built lessons
The same Guard that catches a miss helps turn it into the next test and training case.
Better without forgetting
New releases must keep old wins while learning the new fix.
Keep exploring
Use the full platform. Go deeper where you need it.
Focused playbooks
Straight answers
Build Better Agents, explained.
Do we have to build a model from scratch?
No. Start with the model you like, then add your knowledge, corrections, tests, and focused training.
Can it test more than the final answer?
Yes. Test context, memory, tool calls, recovery, policy results, and the final business outcome.
What keeps a new version from getting worse?
Release gates compare new and old behavior. A candidate that loses old wins does not ship.
Your turn
Bring us one job your AI should master.
We will show how real work becomes knowledge, tests, training, and a release you can trust.