Everything you need to know about BaseSSM and multi-model AI consensus.
BaseSSM is an AI orchestration platform that queries multiple AI models simultaneously and uses statistical consensus (Inverse Variance Weighting) to deliver verified answers with measurable confidence scores. It eliminates AI hallucinations by cross-verifying responses across 170+ foundation models.
BaseSSM applies scientific meta-analysis methodology to AI responses. When you ask a question, it queries multiple AI models in parallel, then uses DerSimonian-Laird heterogeneity testing to measure agreement. Disagreements are flagged, consensus is quantified, and every response includes a confidence score (0-100%).
BaseSSM orchestrates 170+ foundation models including Claude (Anthropic), GPT-4 (OpenAI), Llama (Meta), Mistral, Amazon Titan, Cohere Command, and AI21 Jamba. The platform automatically selects optimal models based on task requirements.
BaseSSM has 4 specialized domain agents: (1) Supervisor Agent for task routing and coordination, (2) Reasoning Agent for architecture and causal analysis, (3) Creative Agent for design and growth strategy, and (4) Analytics Agent for statistical analysis and forecasting.
Confidence scores use Inverse Variance Weighting (IVW) methodology from clinical meta-analysis. Each model response is weighted by its precision, combined estimates are calculated, and heterogeneity is measured using Cochran's Q and I-squared statistics. Higher consensus = higher confidence.
Yes, BaseSSM is built for enterprise use with SOC-2 compliance, GDPR compliance, private deployment options, and audit trails. Contact us for enterprise pricing and deployment options.
BaseSSM is currently in private beta. Visit www.basessm.com and click "Request Early Access" to join the waitlist. We review applications and grant access to qualified users.
Standard AI assistants use a single model that can hallucinate 15-30% of the time with no verification. BaseSSM uses multiple models with statistical consensus, so every answer comes with a measurable confidence score. You know when to trust the response.