Interfaze Review (2026): Pricing, Features & Honest Verdict

TLDR

Interfaze is a developer-focused AI model with an OpenAI-compatible API, built to give reliable structured output for OCR, scraping, classification, and document extraction. It aims to replace a stack of separate services with one call. Best for: developers building extraction pipelines. Price: usage-based from $1.50/M input tokens, no free plan. Rating: 6.6/10.

What is Interfaze?

Interfaze is an AI model and API aimed squarely at developers who use language models for real work like data extraction rather than chat. Instead of a single generalist LLM, it merges specialized small vision and language models with a generalist model to produce deterministic, structured output. The target tasks are the unglamorous ones: OCR, web scraping, classification, speech-to-text, and pulling clean structured data out of documents.

It is built by JigsawStack, a San Francisco company in a 2026 Y Combinator batch, and the product is currently in public beta. The team is upfront that you should expect bugs. The core problem it goes after is one every developer who has wired an LLM into an extraction pipeline knows: generic models hallucinate keys, return broken JSON, and spike in latency. We dug into the pitch and it is essentially a model tuned so that the structured output you ask for is the structured output you get.

What Are Interfaze’s Key Features?

OpenAI-compatible API

Interfaze speaks the OpenAI Chat API format, so adopting it means swapping the base URL and the API key in code you already have. It supports a 1M-token context window with up to 32k tokens of output and multimodal inputs across text, images, audio, files, and video. That compatibility is the lowest-friction part of the whole product: you can test it against your current setup without rewriting your integration.

Structured-output reliability

The headline claim is high accuracy on structured extraction, with the team citing figures in the 98 to 99 percent range for OCR and structured output. The point is determinism: when you ask for a specific JSON shape, you get it, rather than a model that occasionally invents a field or returns prose. This is the feature that justifies the product existing rather than just calling a general LLM, though the accuracy numbers are self-reported and not yet independently verified.

Built-in developer tools

Interfaze bundles tools that you would otherwise assemble from several vendors. There is a headless browser with a proxy scraper and a custom anti-bot engine, web search, a secure code sandbox, retrieval, text-to-SQL, speech-to-text with speaker diarization, translation, and object detection. The infrastructure cost of running the sandbox and browser engine is rolled into token usage rather than billed separately, which keeps the pricing model simple.

Usage-based pricing with free caching

Pricing is pure pay-as-you-go: $1.50 per million input tokens and $3.50 per million output tokens, with a 50 requests-per-second rate limit on the default plan. Cached tokens are not billed at all, which can meaningfully cut costs on repeated or templated extraction work. There are no separate infrastructure line items, so the token rate is close to the whole story for most teams. The free caching is more than a footnote for extraction work specifically, because so much of that work involves the same prompt scaffolding applied to thousands of documents; if the static parts of your request are cached, you pay only for the parts that actually change.

Multimodal inputs and specialized tasks

Because Interfaze accepts text, images, audio, files, and video, a single integration can handle inputs that would normally need different tools. You can throw a scanned PDF, an audio recording, and a screenshot at the same API and get structured results back, with speech-to-text including speaker diarization so transcripts label who said what. The sub-5-second response time the team cites on specialized tasks is aimed at the latency spikes that make generic LLMs frustrating in a pipeline. Whether it holds under your real load is something only a trial will tell you, but the design intent is clearly throughput, not chat.

How Much Does Interfaze Cost?

Interfaze costs $1.50 per million input tokens and $3.50 per million output tokens on its default Pay-As-You-Go plan, with a 50 requests-per-second cap. There is no standing free plan; you get a trial-style onboarding to test it on your own documents, but no recurring monthly free allowance. The Custom enterprise plan adds volume discounts, an unlimited rate limit, SLAs, SOC2 and HIPAA compliance, and 24/7 support.

Comparing this to the document-AI field takes a little translation, because rivals price differently. Mindee uses page-and-credit tiers starting around EUR 44/mo. Reducto is usage-based too, with the first 15K credits free and then $0.015 per credit. Against those, Interfaze’s token model is cheap to start and the free caching helps, but the lack of any free monthly allowance makes it harder to trial at zero cost than Reducto.

The honest caveat is predictability. Because infrastructure for the sandbox and browser engine is folded into token usage, the real cost per extraction task can be harder to forecast than a flat per-page price. For variable workloads that is fine; for finance teams that want a fixed line item, it is less comfortable.

Who is Interfaze Best For?

Use Interfaze if you are a developer or a small-to-mid engineering team building production pipelines for data extraction, OCR, document parsing, or web scraping, and you are tired of stitching together a separate vendor for each step. The OpenAI compatibility means you can trial it against your existing code quickly, and the unified toolset is genuinely convenient when one model handles scraping, parsing, and transcription.

Skip Interfaze if you need a proven, stable platform today, because it is in beta and the team says so plainly. Skip it if you require a free tier to evaluate indefinitely, or if you need independently verified accuracy and compliance guarantees before you can ship. For mission-critical workloads with no tolerance for surprises, a more established option is the safer call right now.

The interesting case is the team in the middle: not a giant enterprise with compliance lawyers, but past the weekend-project stage and tired of maintaining glue code between a half-dozen extraction services. That is the buyer Interfaze is really chasing. If you are currently paying for one vendor for OCR, another for scraping, and a third for transcription, and writing brittle code to stitch their outputs together, collapsing all of that into one OpenAI-compatible endpoint is genuinely appealing. The catch is that consolidating onto a beta product also concentrates your risk: if Interfaze has an outage or changes its API, every one of those tasks goes down at once instead of just one. Decide whether the convenience is worth that single point of failure for your specific pipeline.

Best Interfaze Alternatives

Mindee

Mindee is an established OCR and document-parsing API with a Starter plan around EUR 44/mo and a 14-day free trial. It has years of production use and a catalog of pre-built document models for invoices, receipts, and IDs. Mindee is the safer, more proven pick if your needs are squarely document OCR. Interfaze is broader, covering scraping and transcription too, but it trades Mindee’s maturity for newness. Pick Mindee for stability, Interfaze for range.

Reducto

Reducto is an agentic document platform with usage-based pricing: the first 15K credits are free, then $0.015 per credit, with Growth and Enterprise tiers custom. Its free credit allowance makes it easier to evaluate than Interfaze, and it is focused tightly on complex document understanding. Interfaze counters with a wider toolset and OpenAI compatibility. If you want to start free and stay document-focused, Reducto; if you want one API across many task types, Interfaze.

Extend

Extend is a document parsing and extraction toolkit with sales-led custom pricing, positioned for teams that want a managed extraction workflow with human-in-the-loop options. It is more of an end-to-end platform than a raw model API. Interfaze is the more developer-direct, code-first choice and is cheaper to start. Choose Extend if you want a guided platform with support, Interfaze if you want to wire a model into your own pipeline.

Final Verdict: Is Interfaze Worth It?

Interfaze earns a 6.6 because the idea is strong but the maturity is not there yet. A single OpenAI-compatible API that handles OCR, scraping, classification, and transcription with reliable structured output is exactly what extraction-heavy developers want, and the cheap usage-based pricing with free caching makes it tempting to try. The OpenAI compatibility means testing it costs almost nothing in engineering time.

The reasons to hold back are concrete. It is in public beta with the team warning of bugs, there is no real free plan to evaluate it long term, and the impressive accuracy benchmarks are self-reported rather than independently confirmed. If you are experimenting or building a non-critical pipeline, Interfaze is worth a real look. If you need proven reliability and compliance today, lean on Mindee or Reducto and revisit Interfaze once it leaves beta.