NEW · REPLAY LIVE: A CISO's Guide to Proving Agentic AI Governance
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Self-Improving Governance
Most teams train an AI the old way: pick some settings, run it overnight, squint at a chart, and hope. When a regulator asks why, there is no answer.
Our governors learn from every mistake they catch, fix their own blind spots, and write down exactly how they got better.
The Old Way
A black box
Nobody can replay a training run from six months ago and get the same model back. The proof simply does not exist.
Forgets as it learns
Every new policy quietly erases skills the model already had. The fix lives on someone’s laptop, not in production.
"It’s a small change"
How much can an update actually move the model? Nobody can say. "The change is small, trust us" is the whole answer.
The Loop
It runs quietly in the background, turning yesterday's near-miss into tomorrow's caught threat.
Self-Improving Loop
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Step 1 — Catch
A new kind of miss is caught
No forgetting
prior skills re-checked
Replayable
bit-for-bit, months later
Bounded change
signed limit on every update
01
It catches a miss
A new kind of bad answer slips through, or you add a new policy. The mistake is captured — not buried in a log nobody reads.
02
It learns the lesson
That miss becomes a teaching example. The governor is re-trained to catch it — and every other case that looks like it.
03
It keeps the old lessons
Most AI forgets old skills when it learns new ones. Ours deliberately reviews what it already knew, so a new policy never wipes out last month’s.
04
It signs the work
Every training run is sealed with a record anyone can re-check — same data, same result, down to the last detail. No black box.
Proof It Compounds
Risk Decay Curve
Decay Score:
0/100
Novel violations
Repeat violations
Declining novel violation rate = governance maturity improving over time
Every Catch
Becomes A Test
No
Forgetting
Replayable
Bit For Bit
Verify
Without A Login
What You Walk Away With
✓
It gets sharper on its own
Every mistake your governor catches becomes a harder test it has to pass next time. The system that protects you literally improves while it runs.
✓
It never forgets
Add a new rule on Friday and your governor still remembers every rule from before. The old "every update breaks something" problem is solved by design.
✓
No black-box training
When a regulator asks "how did this model change, and can you prove it?" — you hand them a signed record they can replay themselves, exactly, months later.
✓
A signed limit on every change
Each update ships with a signed promise that it cannot move the model more than an agreed amount. "It’s a small change, trust us" becomes a number anyone can verify.
See the loop run on a real policy change — the catch, the lesson learned, the old skills kept, and the signed record you can hand to any auditor.
Trinitite
AI governance that catches mistakes, proves compliance, and shows the board what it saved—in dollars.
Product
Solutions
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