Vannus / Catalog / MiroFish

MiroFish

Vannus records that this vendor routes across several model providers — not captured by one. Every finding below is quoted to the vendor’s own document, or marked not disclosed where the vendor publishes nothing.

Open-source AI prediction engine using multi-agent technology and swarm-intelligence simulation to model and forecast complex real-world scenarios by constructing digital worlds populated by thousands of autonomous AI agents

prediction, multi-agent, simulation
What the vendor's own documentation says
LLM API Configuration (supports any LLM API with OpenAI SDK format)
github.com ↗ Vendor-sourcedQuote re-checked 14 Sep 2026

The quote above names one provider. The multi-provider finding rests on the vendor’s full disclosure — Model-agnostic (OpenAI-SDK-compatible APIs) — not on that line alone.

Who controls it
Trains on your dataNo — on the vendor's default plan

Training and retention posture varies by plan. What we publish above describes the vendor’s default plan; enterprise, team and API agreements frequently differ, often materially, and a contract can override the published default entirely. Check your own plan and contract before relying on this row.

This is a separate question from the grade above. The grade measures resilience — whether the tool endures and whether you could leave it. This describes who controls the vendor. A tool can score modestly on one and strongly on the other, and many do.

On U.S. CLOUD Act reach specifically: the statute reaches a provider subject to U.S. jurisdiction over data in its possession, custody or control. Corporate control is a strong indicator of that and it is what we can evidence from published documents — but it is not the whole test. A company founded outside the U.S. can still contract through a U.S. entity or run substantial U.S. operations. Treat this as a starting point for your own review, not a legal determination, and take advice on anything that matters.

How this grade is set

Vannus publishes a nine-dimension trust framework — data sovereignty, training privacy, compliance posture, operational resilience, exit portability, and more. The heaviest criterion asks whether the tool builds its own AI or resells someone else's model; where the vendor discloses it, the grade cites the vendor's own documentation. No paid placements — scoring is walled off from affiliate revenue. See the methodology →

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