Company
Agentic AI infrastructure, building Continuous Production Assurance for enterprise agents.
An agent reasons about a goal, chooses its own path, calls the tools it was granted, and hands work to other agents. What it was designed to do, what it actually did, and what happened in the business as a result stopped being the same thing — and nothing in the stack was built to keep checking that they still are. Silex exists to answer that question, continuously, for the agents now taking real authority inside enterprise workflows.
Correspondence cannot be verified without a model of reality.
In traditional software, design is written down as program logic, execution is largely deterministic, and testing checks that the implementation matches the specification. Those three travelled together, so the industry never had to build anything that kept them together.
Agentic systems break all three at once. Design is scattered across prompts, workflow blueprints, policies, permissions and business intent. Execution is non-deterministic. And the reality finally acted on is moved by permissions, other agents, external systems and business state. Better logs and better traces answer what an agent did — not whether it did what it was supposed to, whether that is still correct under current conditions, or whether the controls around it actually prevent the wrong outcome.
Our mission is to make that correspondence checkable again, and to keep it checked: reconstruct the environment an agent can reach, verify behavior against design, validate outcomes and controls against reality, and prove every change through simulation, shadow, and canary before it touches production — so an enterprise can give its agents more authority with evidence rather than hope.
Verification asks whether execution conformed to what was specified. Validation asks whether the specification is still correct under reality. Running only one half means confidently checking an agent against assumptions that stopped being true.
Certification is a snapshot; assurance has to be continuous. We produce evidence rather than certificates — every finding carrying its grade, stated as of the version of the model that produced it, and re-established when the world changes rather than issued once.
The selected policy deploys through the enforcement surface you already own and have already audited. We are an intelligence layer, not an inline enforcement point — we do not take custody of production traffic, credentials, or the final blocking decision.
The agents that reason about security are themselves held under least privilege, sandboxing, policy integrity, human approval, provenance, runtime monitoring, and rollback. They find gaps and rank hypotheses; validation and measurement decide.
We are onboarding a small group of design partners running AI agents in production, and hiring engineers and researchers who want to build security that proves itself.
Prefer email? Reach us at hello@silexai.com.