Modelflare
Modelflare is a hosted AI API gateway for developers building applications, agents, and workflows that use models from multiple providers, including GPT, Claude, Gemini, Grok, and DeepSeek. It provides a shared API key and console for OpenAI-compatible chat and Responses, Anthropic Messages, and provider-specific image and video interfaces. Developers can compare models and routing groups, configure primary routes and ordered fallback groups, or use Smart API Keys to select among available routes according to a routing strategy. API keys can be separated by project and managed with controls such as quotas, expiration dates, and model or IP restrictions. The service records request-level usage, token counts, routing details, and costs, with pricing based on the selected model, group, and applicable billing unit. Documentation includes setup guides for SDKs, coding agents, plugins, and workflow tools.
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Cloudflare AI Gateway
Cloudflare AI Gateway is an intelligent control plane for AI applications, built to connect to any model, dynamically route requests, and manage usage, billing, and logs from one unified gateway. It gives teams visibility and control over AI apps by connecting applications to AI Gateway, gathering insights on how people are using the application through analytics and logging, and controlling how the application scales with caching, rate limiting, request retries, model fallback, and more. AI Gateway helps reduce cost and latency by caching responses and reducing redundant API calls, so frequent requests can be served directly from Cloudflare’s cache instead of the original model provider. It improves reliability with dynamic controls that configure how and when model provider APIs are called based on attributes, fallbacks, latency, cost, or availability, with routing rules that can be adjusted from the dashboard or API without redeployments or downtime.
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AI Gateway HQ
AI Gateway HQ is a hosted AI gateway and control plane for organizations connecting applications, coding agents, and automations to model providers. It provides OpenAI- and Anthropic-compatible API endpoints and routes requests through centrally managed provider credentials, model aliases, workload keys, and fallback rules. Administrators can apply identity and access policies, monitor request metadata, set organization and workload budgets, rate and concurrency limits, and review routing, usage, cost, and policy evidence. The service supports bring-your-own provider API credentials and a managed Amazon Bedrock option using prepaid credit. A browser-based console and API support configuration and governed requests; documented client setups include Codex CLI, Claude Code, and OpenCode. Teams use it to coordinate AI access, control model usage and spending, and review operational evidence across applications and environments.
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Concentrate AI
Concentrate AI is the LLM gateway for fast-growing teams, one API for every major LLM provider, with routing, spend, logs, and controls in one place. It helps teams securely access, use, and manage AI through a single API, so every request can find the smarter, faster, cheaper model for the workflow or task. Teams can access 130+ models, benchmark speed, quality, and cost, and route each workload to the best fit without wiring separate provider APIs into every environment. Support bots, coding agents, internal tools, chat, and batch jobs do not need the same model or the same route, so Concentrate lets teams pick a model slug, limit allowed providers, sort by live latency, use fallbacks, and reroute traffic when a provider slows down, errors, or hits a rate limit. It also gives engineering, finance, security, and leadership a shared view of AI usage with request-level logs, models, provider, duration, token counts, spend, error rates, alerts, and exports.
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