
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 canβt 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 itβs 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 mat
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