From good systemsto gold standards.
Iterator is Monarch’s continuous improvement engine. It turns your experts’ feedback into tests, evaluates candidate improvements against them, and ships only what measurably does better, after human approval.
Iterator on your agentsFrom flawed to gold standard.
Each line is an error an agent makes in production, in the trade you choose. Iterator reproduces it, evaluates candidate corrections, and keeps the one that holds on every test. Reliability is measured at every step.
Continuous improvement, measured.
Agents in production meet cases nobody planned for. Experts notice and correct them, and the correction usually stays in one document. Iterator makes each correction count: it joins a test suite that every future version must pass.
- From feedback to tests
- Each remark from a domain expert becomes a test that stays in the suite.
- Candidates in parallel
- Several improvements are prepared side by side, each in an isolated environment.
- Evaluation before release
- A change ships only if it fixes the case at hand without degrading any other.
- Human approval
- An expert reviews the best candidate with its evidence, then approves it.
Robust by design.
Iterator runs inside Monarch, on your infrastructure, under the same controls as the rest of the platform.
- Isolated
- Candidates run apart from production, on a frozen copy of the data.
- An independent judge
- The judging model is never the one under test.
- Measured noise
- Only a gain larger than the measured noise counts.
- Durable
- After a crash, an iteration resumes where it stopped, and no action runs twice.
- Traceable
- Every change carries its evidence and reverts in one step.
- Sovereign
- Data, models and tests stay inside your walls, under a budget you set.
Your agents, held to the gold standard.
A first iteration, on your data, inside your walls.
Iterator on your agentsMichael Maier, Atalanta Fugiens, 1617. Emblem XLV: « The sun and its shadow complete the work ».