Is Agenomic's replay deterministic?

No. Replay is statistical: it compares output distributions and behavior-contract outcomes across re-runs rather than asserting bit-identical results.

Does Agenomic help with EU AI Act compliance?

Yes. Each release can produce an EU AI Act Articles 9–15 mapping plus signed evidence you can attach to technical documentation and record-keeping. Agenomic provides evidence; it is not a legal certification.

Do I need an account or the cloud to use Agenomic?

No. The CLI and SDKs run fully offline with no account. Cloud is optional — for sharing signed bundles, reviews, and replay.

What does an agent genome capture?

Prompts, models and configuration, tools, permissions, policies, dependencies, memory contracts, execution traces, behavioral fingerprints, and compliance evidence.

How is this different from observability or AgentOps?

Observability tells you what your agent did; Agenomic tells you what your agent is — a signed, versioned, replayable record reviewers can diff before promotion.

Are Agenomic's audit artifacts tamper-evident?

Yes. Genomes are signed and produce tamper-evident attestations (ATEP) suitable for compliance review and post-incident analysis.

Concepts - Agenomic

Concepts

Agents, workflows, runs, bundles, locks, and replay distributions.

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Agents and workflows

An agent is the behavior boundary you release. A workflow is the reproducible execution plan used to produce run evidence.

Runs and replay

A run captures traces and outputs. Replay compares distributions and contract outcomes instead of pretending LLM behavior is perfectly deterministic.