NanoNets YC Application
NanoNets went through Y Combinator in the Winter 2017 batch as a B2B company. Below: what the company does, who founded it, and its application to YC, reconstructed question by question in the real YC form.
- YC batch
- Winter 2017
- Industry
- B2BProductivity
- Team size
- 102
- Status
- Active
- Launched
- 2016
Founders
Sarthak JainFounder/CEO
What NanoNets does
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.
NanoNets's YC application, reconstructed
Y Combinator application
NanoNets, Winter 2017 batch. The real form questions, answered from public data.
- Founders2
- Company7
- Progress7
- Idea4
- Equity3
- Curious2
- Batch Preference1
Company
NanoNets
Automatic Data Extraction
We build AI-powered data extraction tools that read complex documents like invoices, bills of lading, and clinical records. Our product focuses on delivering highly accurate extracted data with full traceability so users can see exactly what was read and why decisions were made. It flags uncertain fields for human review and learns from corrections to improve over time.
We live in San Francisco, and after YC the company will remain based here.
San Francisco places us close to customers, partners, and talent skilled in AI and enterprise software, which is crucial for building and scaling our product.
21 more answers in the full application
Founders, Progress, Idea, Equity, Curious, Batch Preference are in the full version. Create a free account to open it in YC Insights, next to every other YC batch.
Frequently Asked Questions
Is this the real NanoNets YC application?
No. Y Combinator keeps submitted applications private. This is a reconstruction: the real YC form questions, answered from NanoNets's public data (launch notes, founder backgrounds, product description). It shows how a company like NanoNets would present itself to YC, not the text they submitted.
What YC batch was NanoNets in?
NanoNets was part of the Y Combinator Winter 2017 batch.
Who founded NanoNets?
NanoNets was founded by Sarthak Jain.
What does NanoNets do?
Automatic Data Extraction
How do I read the full reconstructed application?
Create a free Round Funded account. The full 26-answer version of NanoNets's application, and every other YC batch, is in YC Insights.
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