NanoNets GTM brain

category

market profile

• text: Enterprise workflows depend on unstructured invoices, purchase orders, bills of lading and clinical documents, with manual handoffs to systems of record.
• text: Document automation purchases require accuracy on edge cases, business rules and review workflows, not extraction alone.

personas

• title: Accounts payable or shared services director
  pains:

  • Invoice volumes and supplier layout variation consume staff time
  • Exceptions and PO matching delay posting and approvals
• title: Order management or logistics operations leader
  pains:

  • Purchase orders and freight documents arrive in inconsistent formats
  • Manually matching rate cards, order details and ERP records creates delays
• title: Enterprise automation or IT leader
  pains:

  • Needs reliable ERP integration and auditability
  • Sensitive documents require security, residency and deployment controls
• title: Healthcare revenue cycle manager
  pains:

  • Clinical and billing documents require manual data entry
  • Ambiguous cases need human review with relevant context

icp

• text: Document-heavy enterprises and scale-ups in finance, logistics, manufacturing and healthcare; site references global Fortune 500 customers.
• text: Organizations processing high volumes of invoices, POs or other variable-format documents and maintaining ERP systems such as SAP or Dynamics 365.
• text: Smaller teams can start with a self-serve credit allowance, while larger regulated buyers can evaluate enterprise deployment and security options.

message pillars

• text: Automate document-led work through to action.
• text: Handle changing business rules and difficult exceptions.
• text: Escalate ambiguous decisions to people with context.
• text: Start with free credits and pay based on workflow activity.

objections

• objection: Our documents and exceptions are too messy for AI.
  response: Pilot on a representative sample with acceptance thresholds, exception routing and business rules measured against the current process.
• objection: How much will a workflow actually cost?
  response: Map block runs per document, estimate volume and account for the plan and volume discount before comparing costs.
• objection: We cannot send sensitive documents to an uncontrolled environment.
  response: Review enterprise residency, private cloud or on-premise options and confirm contractual security controls.

competitors

• name: Rossum
  why: Competes in enterprise invoice and purchase order automation.
• name: Google Document AI
  why: Offers document extraction and parsing for automation workflows.
• name: Microsoft Power Automate
  why: Combines workflow automation with AI document processing.
• name: ABBYY
  why: Competes in intelligent document processing.

keywords

• AI invoice processing
• accounts payable automation
• intelligent document processing
• purchase order data extraction
• bill of lading OCR
• SAP invoice automation
• AI document workflow

voice

• Direct and pragmatic
• Outcome-oriented
• Technical without excessive jargon

signals

• text: A finance team is hiring to handle rising invoice volume or centralizing AP across many suppliers.
• text: An enterprise is migrating to SAP or another ERP and still relies on manual document entry and reconciliation.
• text: A logistics or healthcare operation is actively automating high-volume unstructured documents with human review requirements.

stack

• SAP
• Salesforce
• Oracle
• Microsoft Dynamics 365
• QuickBooks

pricing

motion

channels

• SEO
• company blog
• LinkedIn
• X
• GitHub
• self-serve
• sales

confidence

Founders

• name: Sarthak Jain
  title: Founder/CEO
  role: CEO
  bio: Enjoys being wrong about AI products being mainstream since 2010. 2024 might be different?
• name: Prathamesh Juvatkar
  title: Founder/CTO
  role: CTO
  bio: Would love to discuss tech, specifically deep learning, software architecture, and building software processes. Overseeing tech and marketing. Have worked with golang, django, cassandra, tensorflow, pytorch, react.