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Inferwise
Stop overpaying for AI. Catch expensive model calls before they ship.
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What is Inferwise?
When your application calls an AI model (ChatGPT, Claude, Gemini, Grok), you pay per word processed. A single API call might cost $0.04 — but at 1,000 requests per day, that's $1,200/month. Swap to a cheaper model that handles the same task just as well, and it drops to $180/month. The problem is nobody notices until the invoice arrives.
Inferwise is a cost control tool for AI API bills. It reads your source code, finds every place your app calls an AI model, estimates what those calls will cost, and recommends cheaper models that can do the same job. It runs automatically on every commit and every pull request — if a code change would blow your budget, it blocks the merge before anything reaches production.
Think of it as a linter for your AI spend — the same way ESLint catches code bugs, Inferwise catches expensive AI calls. Whether a human or an AI coding agent wrote the code, nothing ships without cost visibility.
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The $1,800/mo Example
An AI coding agent builds a RAG pipeline and picks Opus for every step — embeddings, retrieval, summarization, response generation. Those calls will run in production, billed per token to your API key.
Without Inferwise: The agent picks the most capable (and expensive) model for every call. The bill shows up after the code ships. $2,400/mo.
With Inferwise MCP: The agent calls suggestmodel for each task — it learns that classification only needs gpt-4o-mini, summarization works fine on claude-sonnet-4, and only the reasoning step needs claude-opus-4. Cost drops to $600/mo before a single line ships.
With Inferwise CI: Even if the agent doesn't use MCP, inferwise diff flags "+$2,400/mo in new API costs" on the PR. The developer swaps models. Same result.
$1,800/mo saved before a single line ships.
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How It Works
Inferwise has seven layers, each building on the last: