SAMI is more than an IDE. It is a multilayer orchestration engine. Integrate our multi-agent consensus workflows directly into your existing CI/CD pipelines or custom AI assistants via a secure integration gateway.
The primary entry point for the SAMI ecosystem. A full-featured desktop IDE configured for repository-aware analysis and structured AI review. It handles local context indexing, secure credential management, and live multi-agent debating.
Semantic parsing happens entirely on-device via the SAMI Vector Core.
Access a curated model catalog through a single managed billing account.
SAMI does not route your request to a single model. Every selected model participates in the same run with equal vote weight, and no model outranks another. Internal coordination and authoring duties move as the work advances; those are jobs, not ranks.
Decisions are a strict binary: each selected model votes Yes or No. A No never ends the run. It loops the council back into deliberation with the objection on the table, the members bring counter-arguments, and the work only advances once it resolves into a genuine Yes.
Every selected model has the same voting weight.
Coordination and authoring are runtime duties, not public roles.
A No must be resolved into a genuine Yes before acceptance.
The same council carries a request through a structured workflow, from framing the problem to validating the result. Each phase scopes what the runtime may do, and the council can run and validate the project at the end, surfacing a fix suggestion and re-voting when something does not hold up.
Public docs stay at the capability level: context, planning, design, drafting, refinement, safety review, and verification. Internal phase labels remain in operator-facing docs and the desktop runtime.
The council reasons over a shared understanding of your project, not a blank prompt. SAMI's context engine blends semantic, keyword, and code-intelligence retrieval into one project-context stream, then feeds it to the pipeline in two layers: a shared baseline context that every stage reads, plus a per-stage context slice scoped to what that stage is doing. Cross-stage recall closes the loop — any model can look back at what any other said earlier in the run, so a later stage builds on the council's own history instead of starting cold.
Hybrid retrieval blends semantic, keyword and code intelligence into one project-context stream the council can draw on.
SAMI can connect approved external workflows to administrative and orchestration capabilities through a controlled integration layer. It speaks the Model Context Protocol (MCP), the open standard for connecting AI assistants to external tools and context — so your own assistants and automation can reach SAMI's orchestration through a single, well-defined interface rather than bespoke glue.
{
"id": "sami-01",
"capability": "workspace_review",
"status": "ready",
"access": {
"scope": "admin"
}
}Enterprise customers with compliance requirements for dedicated infrastructure or their own provider agreements can contact us for specialized controls.
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