There’s a quiet revolution brewing in AI. It isn’t happening through glossy enterprise presentations or top-down mandates. It’s unfolding at developer terminals, where engineers are building the next era of automation, one API call at a time. This bottom-up movement isn’t just changing how AI gets deployed; it’s reshaping what companies expect from their tooling.

At fileAI, we’ve been building for this moment since day one.

From ETL as a service to reinventing data preparation

We began as a financial data automation tool, parsing unstructured data, statements, and documents so businesses could stop matching numbers by hand. Along the way, we solved for layout variation, fuzzy fonts, multiple languages, and handwritten totals. Clean data flowed straight into SAP, NetSuite, and QuickBooks.

Then came the questions: "Can you do this for contracts? For insurance forms? For the 100 namecards I received at a recent event?" Or, "Can you compare, tag, clean, and verify the data?" Each request pointed to a broader challenge: enterprise-wide data preparation.

From IT to finance to legal to operations, disconnected systems and mismatched structures demanded constant manual handling. Valuable information remained trapped, crippling automation flows and limiting the power of existing tooling.

Traditional automation wasn’t enough

Legacy automation depends on rigid templates and brittle rules. Change a layout and it breaks. Switch the context and it loses track. Multilingual fields, handwritten notes, and embedded charts? Total mysteries.

Worse still, these systems forget everything between runs and can't adapt in real time. Teams waste hours patching scripts and handling exceptions.

Introducing Beethoven: multimodal AI OCR that just works

Recognizing that unstructured data processing was only the beginning, we rebuilt our stack. We needed auto-classification, suggested schemas, enrichment, and data fetching, all within a single workflow. To get there, we combined:

• Classical ML: high-precision pattern recognition, anomaly detection, and predictions
• Vision-language models (vLMs): interpret pixels and semantics in one pass, spotting a purchase order number as easily as a handwritten margin note
• AI verification: next-gen validation that exceeds human accuracy, complete with citations, coordinate locations, and reasoning chains
• Data fetch: cross-file, web, MCP, or API, our system retrieves data quickly from wherever it lives
• Real-world scale: a training loop powered by millions of pages across 200+ languages, scripts, and formats

The result is Beethoven, our AI OCR engine that turns unstructured files into structured semantic trees your code can traverse. Each field is cross-validated by secondary models, timestamped, and anchored to its source. If confidence drops, Beethoven flags the uncertainty instead of hallucinating.

AI schemas: declarative data preparation

No more logic trees or brittle templates. With AI schemas, developers simply describe the structure they need, in natural language or JSON, and fileAI handles the rest.

Schemas orchestrate extraction, validation, and citation in a single call, returning business-ready output with zero ambiguity.

Pre-trained on millions of documents, fileAI can recommend optimized schemas the moment a sample hits the system, eliminating setup costs and onboarding delays.

Need to cross-check clauses, reconcile audit fields, or process 800,000 old contracts? AI schemas deduplicate, validate, and return each value with source-level citations. The system verifies data, removing the need for constant manual QA.

This is what sets fileAI apart: you stop worrying about the process and start acting on deterministic, trustworthy data instantly.

Built for developers, priced for momentum

fileAI’s public API is built for velocity in high-governance environments. Pricing is simple and transparent: pay as you go with wallet top-ups for maximum flexibility and ROI.

With our public API, you can:

• Fetch files from object stores or public URLs
• Parse and reconcile cross-document data for compliance and QA
• Modify and clean data without traditional ETL
• Declare AI schemas in one call
• Fetch alternative data (cross-file, online) via schema-based logic
• Query your dataset via the answer engine

Security comes standard: SOC 2 Type II, ISO 27001, GDPR alignment, and data-in-place processing keep even the most regulated teams moving fast.

Proof in production

Since launching the platform in 2025, fileAI has:

• Processed over 400 million files
• Generated 300 million+ AI schemas
• Saved users more than 3.2 million hours and $60 million in processing costs. Explore our customer success stories to see the impact firsthand.

And we’re just getting started.

Try it yourself

The future belongs to developers who don’t wait for permission. They’re shipping automations, building internal tools, and redefining what "manual" even means.‍

We built this API for you. Let’s get to work.
‍

‍Join the waitlist to get early access. Docs and starter repos launch July 2nd.

‍