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NanoNets

Automatic Data Extraction

Hiring

About

AI agents break where it matters most: when the details are buried in an invoice, a BoL, or a clinical document. Most agents guess. They hallucinate field values, apply rules inconsistently, and when something goes wrong, you can’t tell why or fix it without redoing the work yourself.

Nanonets is built differently. Every extraction is traceable. You can see exactly what the agent read, what rule it applied, and why it made the call it did. When it’s uncertain, it flags the right thing for human review instead of silently getting it wrong. When you correct it, it learns. When you add business rules, it tracks which rule drove which decision.

Anyone can build agentic workflows, but AI agents are black boxes that struggle with complex files and processes, like POs, invoices, BoLs and clinical documents. Nanonets agents understand key details in files, work through complex processes and act with transparency, making them the most reliable foundation for building workflows where details matter.

Nanonets reduces processing time by 95% by automating messy manual processes and delivering clean data to systems of record like SAP, SFDC and more. That’s why Nanonets is the automation layer global enterprises reach for when accuracy is non-negotiable.

Topics

Developer ToolsSaaSB2BAIProductivity
Location
San Francisco, CA, United States
Team size
102 employees
YC batch
Winter 2017
Status
Active
Stage
Growth stage

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Questions and answers

What does NanoNets do?

Automatic Data Extraction

Where is NanoNets based?

San Francisco, CA, United States

How many people work at NanoNets?

102 employees, according to the company profile.

Has NanoNets raised money?

There are no funding rounds for NanoNets in our data.

What are the alternatives to NanoNets?

Similar startups: Daily, Unlayer, and Inkeep.