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Six algorithms, four places to enforce them, one status code and a draft standard for telling clients how much quota is left. A working reference for rate limiting HTTP APIs, with the request and token limits that OpenAI, Anthropic and Google apply to model traffic.
Claude now runs on Amazon Bedrock, Google Cloud and Microsoft Foundry, and GPT models run on both OpenAI and Azure. That makes cross-cloud failover practical, but each cloud throttles, authenticates and names models differently. Five gateways, measured against seven published criteria.
Most production teams now call at least two of the three big model providers. Five gateways that put OpenAI, Anthropic and Gemini behind one endpoint, measured on native SDK formats, cross-provider failover, spend control and where the proxy runs.
TypeSafe's Jev returns typed answers with probabilities instead of text. Its documentation, the first developer reports and early independent papers show where it fits in a pipeline, what the published price works out to, and why its probabilities need checking on your own data.
Model APIs fail in documented, predictable ways. The status pages, error codes and rate-limit rules published by OpenAI and Anthropic show which failures a retry fixes, which need a different provider, and which no amount of rerouting will solve.
TypeSafe's Jev returns typed answers with probabilities instead of text. The idea borrows Kahneman's System 1, a calibration objective called RLCD, and a strong claim about hallucination. The concepts, the evidence behind them, and where each one stops.
Routing, gating, judging and choosing an agent's next step are decisions, not writing. Splitting decision from generation is the right architecture, and TypeSafe's Jev is the first product built for it. Trust will come from independently measured calibration, not a promise that it cannot hallucinate.
The word implies a glitch in an otherwise reliable mind. The published evidence says something plainer: models are trained and graded to guess, and the remedy depends on saying so.