reAPI
Pricing
- Model
- Usage-Based
Summary
Provider outages don't announce themselves — they show up in your error logs at 2am, taking your product down with them. reAPI is an aggregator that sits in front of every major AI provider, rerouting failed requests automatically so your app keeps running when OpenAI, Anthropic, or Google has a bad hour.
The pitch is a single base URL and a single API key that spans chat, image, video, music, and code generation across dozens of models — swap the model name in the request, nothing else changes. The vendor states 99.96% uptime backed by automatic failover across provider routes, and the docs describe full OpenAI-client compatibility, meaning codebases already calling /v1/chat/completions need no SDK changes to get started. Where the model hits a ceiling: reAPI is a router, not a reasoning layer — there is no workflow builder, no memory, no prompt management. Teams that need per-request logging for compliance must route elsewhere, since the vendor explicitly states requests and responses are never stored on their side, which is a privacy feature that doubles as an audit-trail gap.
Bottom line: Pick reAPI when provider redundancy and multi-modal access under one key is the problem — skip it when your compliance team needs a stored request log or your architecture needs anything beyond routing.
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Pros
Sign in to edit- Automatic failover across provider routes, so a single provider outage does not take your application down — your requests reroute without a code change or an on-call page.
- OpenAI-client compatibility at the schema level, which means teams already calling /v1/chat/completions can add access to Anthropic, Google, and a dozen other providers without touching their SDK or auth logic.
- Single key and dashboard across chat, image, video, music, and code generation, so adding a new modality to a product is a model-name change rather than a new vendor contract, new SDK, and new integration test suite.
- Zero request and response logging on the vendor side, so data sent through the API does not accumulate on a third-party server — reducing exposure for products handling sensitive user inputs.
- Provider-agnostic model routing, so when API costs spike on one provider, switching to a cheaper model is a one-line config change rather than an infrastructure project.
Cons
Sign in to edit- No stored request or response logs, by design — teams that need an audit trail for compliance, debugging, or fine-tuning data collection must build their own logging layer before any request reaches reAPI, which adds infrastructure overhead the tool was supposed to eliminate.
- The tool is a passive router with no workflow layer, memory, or prompt management — teams that start with simple model-swap use cases and grow into multi-step agents that branch on prior outputs hit this ceiling fast, at which point they are running reAPI for routing and a separate orchestration system for logic, maintaining two integrations instead of one.
- No self-hosted option is available, so teams in regulated industries or air-gapped environments that cannot route production traffic through a third-party endpoint cannot use reAPI at all — those teams typically evaluate self-hostable aggregators or build internal provider-switching logic instead.
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About
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- 2026-07-16T18:24:34.224Z
Best For
Who it's for
- Teams needing redundancy across AI providers
- Developers using OpenAI-compatible SDKs
- Production workloads requiring high uptime
What it does well
- Access multiple AI models via one endpoint
- Build applications with automatic failover across providers
- Generate images, videos, music, and code without changing client code
Integrations
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Frequently Asked Questions
- Is reAPI free?
- reAPI has a permanent free tier alongside paid upgrades. You can keep using a baseline version indefinitely without paying.
- Is reAPI open source?
- No — reAPI is a closed-source tool. Source code is not publicly available.
- Does reAPI have an API?
- Yes. reAPI exposes a developer API. See the official documentation at https://reapi.ai for details.
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Curated lists that include this category
Switching AI providers mid-incident means rewriting auth headers, swapping SDKs, and praying your abstractions held. reAPI removes that scramble by exposing a single endpoint — OpenAI-compatible — that routes to OpenAI, Anthropic, Google, and a long tail of image, video, and music providers. Change the model name in the request body; the rest of your client code stays unchanged. Automatic failover handles provider degradation without a pager alert reaching your team.
The multi-modal breadth is the differentiating move here. Most API aggregators cover chat and stop. reAPI routes video generation to Veo 3.1, Seedance 2.0, Kling, Runway, and Happyhorse; image generation to Flux Pro, Flux Kontext, GPT Image 2, Nano Banana, and Seedream 5.0; music generation through Suno; and coding tasks across GPT-5.5, Claude, Gemini, DeepSeek, and GLM-4.5 — all under one dashboard and one key. Adding a music track to a product becomes the same operation as adding another chat model.
reAPI fits teams whose core risk is provider downtime or API cost spikes requiring fast model swaps. It fits developers already on OpenAI-compatible SDKs who want access to non-OpenAI models without maintaining separate integrations. It does not fit teams that need stored request/response logs — the vendor states explicitly that no logging occurs on their side, which eliminates reAPI from any compliance workflow that requires an audit trail. It is a passive router, not an agent system, so teams building workflows with memory, branching, or tool-use orchestration will need a separate layer on top or a different tool entirely.
The OpenAI-compatible schema means /v1/chat/completions calls work out of the box. The vendor describes redundant internal routes for OpenAI specifically — four routes covering GPT-5.5, GPT Image 2, Whisper, and Realtime — and three routes for Anthropic covering Claude 4.7 Sonnet and Opus. A browser-accessible playground, image studio, video studio, and music studio are available for model evaluation before committing to integration.