Latent
ActiveAI-nativeCatch wrong LLM answers before your customers do
What it does
Latent catches wrong or unsupported LLM answers before they reach your users. Instead of running a second model to check every output, it reads the model's own internal state as it generates, so every request is verified with no added latency, no extra inference cost, and nothing leaving your deployment. Teams running LLMs in production, in finance, legal, healthcare and customer support, get a review queue of the answers most likely to be wrong, calibrated to their own model and traffic, with a plain explanation of why each one was flagged.
Its site says now · captured 2026-10-06
Latent reads your model
Next to it in Agent infrastructure · LLM output verification and evals
- AshrY Combinator W26
Enterprise post-training, monitoring, and continual learning platform
- Rubric AIY Combinator W26
Reasoning and verification infra for AI
- Modaica16z speedrun SR006
Verification & alignment infra for AI decisioning.
- FaradayY Combinator F26
Industrial aOS between humans, agents, and robots
- The Company CompanyY Combinator F26
The last agent your company will ever need.
- Rena LabsPlug and Play PnP 2026
Rena Labs enables secure AI operations on private data with TEE data exchange.
- AliniaPlug and Play PnP 2026
Auditing & compliance of AI Agents at scale.
- ComplyCoPlug and Play PnP 2026
Build-your-own compliance AI workflows for sanctions screening, regulatory monitoring and due diligence, with audit trails built in.