Edgee
Edgee is an AI gateway that sits between your application and large language model providers, acting as an edge intelligence layer that compresses prompts before they reach the model to reduce token usage, lower costs, and improve latency without changing your existing code. Applications call Edgee through a single OpenAI-compatible API, and Edgee applies edge-level policies such as intelligent token compression, routing, privacy controls, retries, caching, and cost governance before forwarding requests to the selected provider, including OpenAI, Anthropic, Gemini, xAI, and Mistral. Its token compression engine removes redundant input tokens while preserving semantic intent and context, achieving up to 50% input token reduction, which is especially valuable for long contexts, RAG pipelines, and multi-turn agents. Edgee enables tagging requests with custom metadata to track usage and spending by feature, team, project, or environment, and provides cost alerts when spending spikes.
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ZeroGPU
ZeroGPU is a compute efficiency layer for AI inference that helps AI applications reduce inference costs by moving high-volume tasks to specialized models across an edge-powered inference network. It is built around the idea that most production AI workloads do not need frontier-scale reasoning; tasks such as document analysis, content summarization, page classification, signal extraction, PII detection, web content processing, query routing, and message moderation can often run on smaller, task-specific models instead of expensive frontier models. ZeroGPU helps developers identify workloads that do not require deep reasoning, route them to specialized small language models and nano models, execute them across optimized servers, approved edge capacity, and cloud fallback, then measure cost reduction, latency improvement, avoided frontier-model calls, and model performance.
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Steamship
Ship AI faster with managed, cloud-hosted AI packages. Full, built-in support for GPT-4. No API tokens are necessary. Build with our low code framework. Integrations with all major models are built-in. Deploy for an instant API. Scale and share without managing infrastructure. Turn prompts, prompt chains, and basic Python into a managed API. Turn a clever prompt into a published API you can share. Add logic and routing smarts with Python. Steamship connects to your favorite models and services so that you don't have to learn a new API for every provider. Steamship persists in model output in a standardized format. Consolidate training, inference, vector search, and endpoint hosting. Import, transcribe, or generate text. Run all the models you want on it. Query across the results with ShipQL. Packages are full-stack, cloud-hosted AI apps. Each instance you create provides an API and private data workspace.
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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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