Cortex Engines

Cortex Engines accepts a question, claim set, or document and runs it through a five-stage pipeline the vendor describes as Extract, Compare, Detect, Score, and Synthesize. Claims are pulled from your input, multiple AI models and live sources are queried independently, contradictions between those sources are identified, confidence is scored across models, and the output is a report that states what the evidence supports, where disagreement exists, and whether you are ready to act. Three analysis modes exist: Quick Answer uses a single model for fast responses and is free; Standard Analysis adds multi-model comparison and contradiction detection and is also free; Deep Intelligence adds structured decision-intelligence reports, monitoring, PDF export, and saved reports and is a paid-only feature.

The differentiating capability is contradiction detection. Where a single AI returns one confident answer, Cortex surfaces every point of disagreement between models — severity-rated and explained — alongside a confidence verdict that aggregates reliability signals across sources. The vendor frames this explicitly as verification infrastructure rather than generation: the comparison is positioned against ChatGPT-style single-output tools, not other research platforms.

Cortex fits analysts, founders, and investors who want a second opinion on AI-generated research before acting on it — due diligence on pitch decks, market size sanity checks, regulatory claim verification. It breaks for teams that need programmatic access: there is no API, so the tool cannot be embedded in a data pipeline, triggered by an event, or called from another application. There is also no self-hosted option, meaning data sent for analysis travels to Cortex’s infrastructure — a constraint for teams with strict data residency requirements. Teams that need either capability do not find a workaround here; they switch to a platform that exposes an API.