Seattle‑based Resect AI raised $25 million to build an accountability layer that captures and reduces hallucinations at runtime, aiming to make enterprise AI more trustworthy.
Seattle‑based Resect AI has secured $25 million in funding to develop technology that detects and mitigates hallucinations in large language models during runtime, aiming to boost enterprise trust in AI deployments.
Funding round and investors
The Series A round was led by Sequoia Capital, with participation from existing backers Accel and 500 Global. The capital will be used to expand the engineering team and accelerate product integration with major cloud providers.
The hallucination problem in AI
Large language models can generate plausible‑sounding but factually incorrect statements, known as hallucinations. These errors pose risks for enterprises that rely on AI for customer support, document analysis, and decision‑making.
Resect’s accountability layer
Resect’s platform adds a runtime monitoring layer that flags outputs that deviate from known data sources, prompting a fallback to verified information or a human review. The company claims the approach can reduce hallucination rates without sacrificing model performance.
- Real‑time detection of inconsistent statements
- Automatic citation of source material
- Seamless integration via API with existing AI pipelines
Market outlook
As enterprises adopt generative AI, demand for safety and compliance tools is rising. Analysts expect the AI governance market to grow rapidly, creating a sizable opportunity for solutions like Resect’s.
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