TrustedRouter
TrustedRouter is a privacy-first AI gateway that gives developers access to 600+ AI models from 90+ providers through one OpenAI-compatible API. It routes requests through an attested gateway that does not log prompt or output content, keeping the production prompt path separate from the dashboard and billing control plane so even its engineers cannot read requests. Developers can keep the OpenAI SDK and migrate by changing a single base URL, while choosing direct model IDs or routing aliases for healthy-provider rollover, zero-retention providers, confidential compute, EU-focused routing, and multi-model synthesis. Provider failover, regional routing, and continuous model health measurements help prevent a single upstream outage from becoming a product outage. TrustedRouter runs across GCP, AWS, and Azure and publishes latency, availability, source code, deployment infrastructure, SDKs, and trust evidence for inspection.
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OrcaRouter
OrcaRouter is an OpenAI-compatible AI model router that sends each prompt to the right model across OpenAI, Anthropic, Gemini, DeepSeek, Qwen, Kimi, and 200+ frontier and open source models. It is built to preserve frontier answer quality while reducing AI inference spend by grading every prompt and routing hard reasoning to frontier models and routine work to lower-cost open source models. The routing is quality-graded, never a blind, cheap-model swap, and each request shows the difficulty grade, selected model, provider, and cost so routes are visible, auditable, and reproducible. Developers can switch by changing the API base URL, while existing SDKs, model names, and streaming behavior continue to work as before. OrcaRouter supports automatic failover, so if a provider goes down mid-stream, traffic can switch transparently, and the application avoids user-facing errors. It also includes API key management with spend caps, model allowlists, rate limits, budget enforcement, and more.
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Router
Router is an LLM gateway built to reduce inference costs by matching each request to the lowest-cost model that still meets performance needs. It provides one endpoint and one API key for accessing multiple closed and open-source AI models from providers such as OpenAI, Anthropic, Grok, Fireworks, and others, helping developers avoid wiring applications to providers one at a time. Requests go through Router first, where usage, model, provider, and cost can be tracked before eligible workloads are routed to a more efficient option when quality will not be affected. Router Strategies let developers define cost and performance priorities for different types of requests or use benchmarked defaults based on real production workloads. It responds to live latency, availability, failures, and rate limits, and eligible requests can be moved to another available model when a provider cannot serve them.
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Pioneer
Pioneer is an inference API built for developers who would rather ship than babysit a GPU cluster. It lets teams point an existing OpenAI, Anthropic, or other client at Pioneer, keep the same API and code, and run inference like normal while Pioneer finds where the current model falls short. It clusters production traffic by use case, surfaces where accuracy, latency, or cost can improve, then builds and routes to small specialist models automatically. Its continuous improvement loop, Adaptive Inference, mines live production failures for high-signal examples, retrains a specialist model, evaluates the new checkpoint, and promotes improvements behind the same endpoint without requiring redeployment. Pioneer supports encoder models for structured extraction tasks such as named entity recognition, text classification, structured JSON extraction, privacy filtering, and safety classification, as well as decoder models for text generation, classification, open-ended prompting, etc.
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