What problem does it solve?
It solves the problem of unreliable technical research by forcing multi-source verification, grounded synthesis, and citation integrity before conclusions are presented.
Core Features & Use Cases
- Multi-source investigation: Pulls evidence from Gemini, Tavily, and Perplexity to cover a query comprehensively rather than relying on a single search result.
- Verified-claim synthesis: Extracts claims, verifies them across sources, measures confidence, and records contradictions when sources disagree.
- Guardrails against hallucinations: Requires citations, validates citation ranges, and returns "insufficient evidence" when sources do not answer the question.
- Safety and cost control: Uses environment-based API keys, rate limiting, and cost tracking expectations to reduce operational risk.
- Use case: When you need to evaluate a new technology decision (e.g., selecting a database for high-write workloads), use it to compare claims across primary and secondary sources, surface disagreements, and produce a defensible recommendation.
Quick Start
Ask your AI to run a deep technical investigation on a specific question, ensuring it cross-verifies claims across multiple sources and produces a grounded, cited synthesis.
