DocsFlow AI is an AI-powered document intelligence company founded in 2026 and headquartered in Hosur, Tamil Nadu, India. We help businesses extract, understand, and automate data from documents, PDFs, forms, images, and websites — converting unstructured content into structured, machine-readable data with OCR, web crawling, and workflow automation.
We obsess over extraction accuracy. Every model update is benchmarked against thousands of real documents.
Sub-3-second processing isn't a goal — it's a baseline. We continuously optimize our inference pipeline.
Built by developers, for developers. Clean APIs, great docs, and SDKs that just work.
Infrastructure across 3 continents ensures low latency for teams everywhere.
DocsFlow AI is a document data extraction API and OCR company founded in 2026 and headquartered in Hosur, India. We are on a mission to turn every PDF, invoice, scan, and website into structured, machine-readable data — without templates, without manual data entry, and without sacrificing accuracy or security.
DocsFlow AI is an AI-powered document intelligence company that builds software for turning unstructured documents and websites into structured data. Its platform combines OCR, intelligent document processing (IDP), web crawling, and workflow automation so invoices, contracts, IDs, forms, scans, and web pages become clean JSON that APIs and business systems can consume.
DocsFlow AI is headquartered in Hosur, Tamil Nadu, India, at Avalapalli Road (above ACT Internet Showroom), Hosur 635109. The team operates remote-first, serving customers across the Asia-Pacific region, Europe, and the Americas.
DocsFlow AI was founded in 2026. The company was created to remove the need for manual data entry and brittle, template-based OCR by combining modern AI models with an API-first document extraction platform.
DocsFlow AI is used by accounts payable and finance teams for invoice data extraction, KYC and onboarding teams for identity verification across 180+ countries, legal teams for contract intelligence, healthcare organisations for HIPAA-compliant records processing, and e-commerce operations for catalog ingestion from supplier websites.
Files are uploaded or fetched via URL, normalized, then run through OCR and a multi-model AI pipeline that detects text, tables, fields, signatures, and handwriting. A validation layer checks the extracted values before returning structured JSON. End-to-end processing typically completes in under 3 seconds per document.
You can reach the team at [email protected] or call +91 83003 65605. For partnerships and press, reach out on LinkedIn, X (@docsflowai), YouTube, and Instagram. Job inquiries go to [email protected].
Large language models are the reasoning layer of the platform. After OCR and vision models read the document — text, tables, handwriting, and signatures — an LLM reads that content in context and maps it to your output schema. It identifies which number is the invoice total, which clause is the termination right, and which date is the renewal deadline by understanding meaning rather than matching fixed coordinates. That is what makes extraction template-free and why new vendor layouts are handled without rule maintenance.
Yes. DocsFlow AI combines vision-language models with LLMs in a single pipeline. The vision layer processes pixels and text together, so scanned pages, faxes, and phone photos are read in their original layout — including handwriting and signature blocks. The LLM layer then maps the extracted content to structured fields. Together they let one API call handle a native PDF and its scanned counterpart identically.
Trust is engineered, not assumed. Every extracted field returns a confidence score, a source page reference, and a bounding box so output is traceable to the original document. Configurable thresholds route low-confidence values to human review, and cross-field validation rules reject contradictions such as totals that don't match line items. Structured generation constrains the model to your schema at inference time, which is how the platform maintains 99.2% accuracy in regulated workloads.
Structured output means the AI returns JSON that matches the exact schema your systems expect — field names, data types, and nesting — instead of free text you must parse again. DocsFlow AI applies this across invoices, contracts, IDs, medical records, and crawled web pages, so teams connect validated data directly to databases, ERPs, and workflow automation without building a second parsing layer.
We're a small, remote-first team building something ambitious. If you care about AI, developer tools, and great UX — we'd love to talk.
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