Interfaze
Model built for OCR, extraction and other deterministic tasks, with infrastructure bundled into token pricing
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interfaze.aiAbout Interfaze
Interfaze is a model built specifically for deterministic tasks — the class of work where a general chat model's creativity is a defect rather than a feature. OCR, structured data extraction, audio understanding, web scraping and classification all want the same answer every time from the same input, and Interfaze optimises for accuracy, precision and consistency on exactly those jobs instead of open-ended reasoning. It is chat-completions compatible, so it drops into the Vercel AI SDK, LangChain or any other framework you already use, and there are first-party TypeScript and Python SDKs alongside the raw API. The practical differentiator is that infrastructure is bundled rather than metered separately: sandbox execution, the browser engine and caching are all converted into tokens and billed at the same input/output rates rather than appearing as surprise line items, so a scraping job's cost is a single number you can forecast. The published per-task estimates are unusually concrete for a model vendor — roughly $0.002–$0.004 to OCR a document page, about $0.016 to extract structured fields from an ID or invoice, $0.006 per minute of transcribed audio, and $0.03–$0.08 to scrape and structure a web page. Rate limits are 50 requests per second on the standard tier, with volume discounts, self-hosted and VPC deployment, SOC 2 and HIPAA agreements available on the enterprise plan.
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Key Features
Interfaze Pros & Cons
✅ Pros
- +No separate infrastructure billing removes the usual scraping-cost surprise
- +Per-task cost estimates make it easy to model a pipeline before building it
- +Drop-in compatibility means no rewrite to evaluate it
⚠️ Cons
- −Deliberately narrow — it is not a general reasoning or chat model
- −Still in beta, so consistency claims deserve your own benchmark
- −Observability and logging are listed as coming soon, not shipped
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