TypeSafe AI emerged from stealth on September 15 with a $40 million seed round led by DCVC at a reported valuation of approximately $200 million, launching Jev, a specialized “System One Model” for structured decision-making that abandons generative LLM capabilities for a non-LLM, parallel sampling architecture. Led by CEO Diogo Almeida, an OpenAI veteran and co-inventor of RLHF, alongside co-founders Erik Gafni and Sasha Sheng, Jev processes unstructured state data and typed questions to produce all required answers in a single parallel pass, with strictly type-safe output preventing hallucinations or malformed data and calibrated confidence scores letting developers set thresholds for autonomous action, follow-up, or human intervention. TypeSafe reports Jev is 193.6x faster and 444.6x cheaper than frontier LLMs in peak in-house testing, with a cost per decision of approximately $0.0004 and pricing at $0.042 per million input tokens, while output tokens are priced at zero. Independent testing from Every found Jev roughly 25x faster and 580x cheaper than Claude Fable 5.1 on extraction tasks: 0.35 seconds versus 8.83 seconds per passage. TypeSafe reports approximately 67.8% on its internal four-workflow production benchmark, with latency of 70 to 500 milliseconds end-to-end. Jev cannot generate free-form text, write code, draft documents, or hold conversations