Extend Raises $17M to Scale Its AI-Native Platform That Turns Documents Into Actionable Data
Extend, a rising force in AI-native document processing, has raised $17 million in combined seed and Series A funding to expand its breakthrough platform built for the Agentic Era of enterprise AI. Led by Innovation Endeavors with support from Y Combinator, Homebrew, Character, and angel investors like Scott Belsky and Guillermo Rauch, the round will fuel Extend’s product expansion and market push as it reshapes how businesses unlock value from unstructured documents.
What started as a nimble, LLM-powered solution for parsing messy forms and degraded PDFs has now become the go-to platform for tech-forward teams at Brex, Square, Checkr, Flatiron Health, and multiple Fortune 500 companies—businesses that rely on Extend to process millions of documents with near-perfect accuracy.
“We’ve gone cash-flow positive, exceeded our early revenue targets, and are just getting started,” said Kushal Byatnal, co-founder and CEO. “This isn’t just automation. It’s intelligence at ingestion.”
A Full-Stack Rebuild of Document AI
Legacy OCR systems and Frankenstein-like data extraction pipelines have long plagued industries like finance, healthcare, and logistics, where every field matters and regulatory compliance leaves no room for error.
Extend ditches the duct tape. Its LLM-native architecture includes:
- A high-fidelity parsing engine that handles degraded scans, handwritten forms, and complex tables.
- Built-in evaluation tooling to ensure accuracy and traceability.
- Orchestration for deployment, so developers can move from prototype to production in days—not months.
The result? Teams achieve 95%+ accuracy and skip the months-long engineering gauntlet of patching together brittle OCR solutions.
“Extend outperformed everything else we tried—from open source to commercial tools,” said Pedro Franceschi, CEO at Brex. “It’s become a critical part of how we power intelligent document workflows for our 30,000 customers.”
Why It Matters Now
Documents remain the system of record for mission-critical data—from invoices and contracts to patient records and compliance forms. But traditional systems choke on edge cases, require excessive tuning, and often fail to deliver at enterprise scale.
Extend is flipping the script. Its platform makes ingesting and understanding documents as easy as calling an API—no data science PhDs or multi-week onboarding needed.
“With Extend, developers have access to modern APIs, while operations teams get intuitive, reliable tools. It’s a win on both sides of the house,” said Eli Badgio, co-founder and CTO.
And now, with a self-serve version launched, Extend is opening the gates to a broader ecosystem of startups and mid-size teams who want to get started immediately—no sales call required.
Unlocking Competitive Differentiation
Extend’s architecture also enables customers to go beyond efficiency and into competitive differentiation. As noted by Davis Treybig, Partner at Innovation Endeavors:
“It’s not just about automation anymore. Extend’s customers are shipping new product features and workflows that weren’t feasible before—powered by document data they couldn’t access reliably until now.”
In other words, Extend isn’t just taking cost out of document workflows—it’s creating entirely new use cases and revenue levers by making structured, validated data accessible on demand.
What’s Next?
With this new capital, Extend will scale its engineering and go-to-market teams, invest further in R&D, and build out more fine-tuned, industry-specific document agents. As AI-native workflows become the norm across the enterprise, Extend is well-positioned to become the default ingestion layer for documents across sectors.
This also places Extend at the heart of a broader shift—from AI as augmentation to AI as autonomous orchestration, where tools like Extend don’t just extract data, they enable agentic systems to reason and act upon it in real time.
Bottom Line
Extend is no longer just a document parsing tool—it’s an AI-native operating layer that transforms unstructured inputs into reliable, production-ready data pipelines. Backed by a fresh $17 million and growing adoption from some of the most data-intensive teams in tech, it’s building the infrastructure for intelligent, context-aware enterprise automation—one PDF at a time.
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