Anuclei builds Multisynapse, the Agent System of Record. It is the trust boundary every agent reports into: the place where agents are evaluated, certified, authorized, and proven, so you can answer the question that matters once agents can act. Is this the agent we approved?
Evaluation tells you an agent performed well in an experiment. It does not tell you the agent running in production is the one you approved. Multisynapse gives every agent one behavioral identity that follows it from evaluation through certification, authorization, execution, and audit.
Four transitions, one identity. Each stage produces evidence the next one can check, and none of it comes from the agent's own account of itself.
Score agents against frozen golden sets with LLM judges, classifiers, matchers, or your own sandboxed code. Rehearse any agent in dry-run mode, with every intended action recorded and nothing executed.
Every agent registers a versioned card, and every change is an immutable snapshot. Promotion flips the active version only after the eval gate passes. No agent approves itself.
Every write, eval run, tool call, and model call flows through default-deny policy. Federated MCP and LLM gateways give you one policy surface, with per-tenant budgets and kill-switches.
Every prompt, tool call, and token of spend lands in a structured trace. The audit log is hash-chained, so who promised what, and what actually happened, is tamper-evident by construction.
Three principles run through everything we build. They are the whole company in miniature.
Anything stated with confidence, by a model, a vendor, or us, earns scrutiny in proportion to that confidence.
A claim about a system is checked against the system before anything is built on top of it. Gates before promotion, rehearsal before execution, evidence before belief.
Resemblance to something that worked is a hypothesis. Traces, evals, and paired statistics are how a hypothesis becomes a decision.
Agents now act on your behalf. A dashboard tells you what happened; a system of record knows what each agent was allowed to do, who approved it, and how you know it worked.
What shipped in Multisynapse this month, and why each piece points the same direction: the unit you certify is getting bigger, and the evidence behind it is getting more specific.
Why AI agent governance requires a chain of identity from evaluation to authorization to execution.
If your organization is moving from experimenting with agents to letting them act, that is the question. Multisynapse is how you answer it.