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Automatic Data Extraction
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 provides AI agents and an API to automate enterprise data processing, turning unstructured documents into structured, system-ready data and enabling end-to-end automation across ERP and business tools. It targets large organizations handling complex workflows (AP, order management, claims, etc.).
Nanonets offers two products on a single platform: agents that read messy inputs, apply user-defined rules, and complete work inside customers’ systems of record; and a developer-focused Agentic Data Extraction API designed for LLM and agent pipelines. The agents operate across multiple tools (ERP, CRM, collaboration and storage apps) without replatforming, delivering agent-ready data to systems like SAP, Salesforce, QuickBooks, Xero, and more. Security and governance features include private deployment, SSO, audit logs, data residency, BYOK, encryption, and compliance certifications. The pricing page indicates a credit-based usage model starting with free credits and paid tiers, with emphasis on usage-based costs and scalable volumes.
Who it’s for: Enterprises and mid-to-large teams that process high volumes of unstructured documents (invoices, receipts, contracts, claims) and seek end-to-end automation across ERP, CRM, and collaboration tools.
Customers: UniPro (case study cited)
Active product with case studies and enterprise endorsements; pricing page details free credits and usage-based tiers; ongoing emphasis on security/compliance and private deployments; multiple references to production workflows and customers.
Enjoys being wrong about AI products being mainstream since 2010. 2024 might be different?
Formerly “Deep Belief Networks” · why startups rename →
Self-Driving Customer Care
AI Agents that automate enterprise software processes
