Build private boards of specialized AI personas powered by heterogeneous LLMs. Screen raw expert materials into calibrated personas, moderate debates via formal charters, and preserve durable audit trails across every meeting.
Configure multi-model panels tailored to your exact decision domain. Each persona operates with a distinct cognitive baseline, assigned LLM, and value anchors.
Stress-test corporate pivots, fiduciary risks, and capital allocation before committing real resources.
Transform raw expert archives into calibrated, self-consistent AI personas. Strictly separate the simulated agent from the real person's identity.
Upload documents, interviews, essays, or transcripts representing real or fictional domain experts.
Extract underlying cognitive styles, heuristics, and boundaries into an independent persona baseline.
Categorize the persona's role, define immutable value anchors, and link to a governing room charter.
Assign distinct model APIs (OpenAI, Anthropic Claude, Google Gemini, xAI) to ensure cognitive diversity.
Typical multi-agent chats suffer from sycophancy, echo chambers, and personality erosion. Sim-Board guarantees cognitive independence through four architectural pillars.
Each persona has an immutable prompt and SHA-256 fingerprint protected by database triggers. No conversation can silently overwrite core convictions.
When personas learn from meeting debates, insights are categorized as Facts, Assumptions, or Convictions and must be approved before entering context.
Every single message, model generation latency, token count, and founder decision is recorded in a tamper-proof audit log for compliance and review.
Running different providers (Claude, GPT, Gemini, Grok) side-by-side breaks single-model consensus biases and brings genuine intellectual friction.