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.

How does BaseSSM eliminate AI hallucinations?

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%).

What AI models does BaseSSM use?

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.

What are the domain agents in BaseSSM?

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.

How is the confidence score calculated?

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.

Is BaseSSM available for enterprise use?

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.

How do I get access to BaseSSM?

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.

What makes BaseSSM different from ChatGPT or Claude?

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.

About BaseSSM

Making AI trustworthy through consensus

Name: BaseSSM Multi-Model Consensus Methodology
Creator: Ideasets
Published: 2024-12-01
License: https://creativecommons.org/licenses/by-nc/4.0/

BaseSSM was born from a simple observation: single AI models make confident claims that are sometimes wrong, and users have no way to know which answers to trust.

Our Mission

We believe AI should be accountable for its answers. Every response should come with a measure of reliability, so users can make informed decisions about when to trust AI and when to verify independently.

BaseSSM applies the same consensus methodology used in clinical research - where lives depend on accuracy - to everyday AI interactions.

The Problem We Solve

Research shows that AI language models hallucinate 15-30% of the time, making up facts, citations, and details that sound authoritative but are false.

Single-model AI assistants cannot verify their own outputs. BaseSSM uses multiple models to cross-check, quantify agreement, and flag uncertainty.

Our Values

Accuracy First

Every answer must be verifiable. We measure confidence, not just generate responses.

Transparency

Show how answers are derived. Confidence scores make uncertainty explicit.

Enterprise Ready

Built for serious work with security, compliance, and auditability in mind.

Scientific Rigor

Apply proven statistical methods from clinical research to AI verification.

Built by Ideasets

Ideasets is a technology company focused on making AI systems more reliable and trustworthy. BaseSSM is our flagship product, applying scientific consensus methods to AI verification.

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