Automate document workflows with AI-powered data extraction
Nanonets is an AI document processing platform for teams that need to extract, classify, and automate data from unstructured documents.
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AI Editor ApprovedApproved and published by our AI Editor-in-Chief after full panel analysis.In practice, users upload documents—PDFs, images, emails, or scans—and configure extraction fields they want to capture, such as vendor name, invoice number, or line items. Nanonets processes incoming documents automatically, pulls the specified fields, flags low-confidence extractions for human review, and can push the structured output to downstream tools via integrations or API. The human-in-the-loop review interface allows teams to correct and approve extractions before data moves forward.
The platform includes pre-built models for common document types including invoices, receipts, ID documents, and bank statements, so users can start without training from scratch. For specialized documents, users can label a sample set and fine-tune a custom model. Nanonets also offers an AP automation workflow specifically for accounts payable, covering invoice capture, two- and three-way PO matching, approval routing, and sync to accounting systems like QuickBooks, Xero, NetSuite, and SAP. Additional integrations include Zapier, Google Drive, Dropbox, and email inboxes.
Nanonets targets finance, operations, and logistics teams in mid-market and enterprise companies dealing with high document volumes. Pricing is usage-based, charged per page processed, with a free trial available. Competing products in the intelligent document processing category include Rossum, Hyperscience, AWS Textract, Google Document AI, and ABBYY FlexiCapture.
The platform is delivered as a web application with a REST API for programmatic access. Developers can integrate Nanonets directly into existing applications to submit documents and retrieve extracted data without using the visual interface. Webhooks are supported for event-driven processing pipelines.
AI agents read messy document inputs, apply user-defined business rules, and complete work end-to-end inside systems of record without requiring human intervention by default.
A proprietary document extraction model ranked #1 on the IDP Leaderboard that converts documents into structured Markdown and JSON output with high accuracy, ahead of GPT-5, Gemini, and Claude.
Enforces per-team API budgets and rate limits with real-time cost dashboards to prevent unexpected usage overruns.
Automatically validates invoices against purchase orders and vendor records as part of the accounts payable workflow before routing for approval.
Routes documents and edge cases through configurable approval gates, delivering review requests to Slack, Microsoft Teams, or email for human-in-the-loop decisions.
A document extraction API built for LLM and agent pipelines that outputs structured Markdown and JSON with tables preserved, supporting low latency and open-source integrations with LangChain and LlamaIndex.
Ingests invoices, receipts, and other documents arriving in any format from sources including email inboxes, Google Drive, Dropbox, Box, and Notion.
Agents post validated invoice and payment data directly into connected ERP systems such as SAP, QuickBooks, Xero, and Sage after processing.
Records every agent run, approval, and data access event and streams logs to a SIEM via webhook for compliance and monitoring.
Supports VPC, single-tenant cloud, or on-premises deployment with customer-managed keys (BYOK) and data residency pinned to US, EU, or APAC regions.
Provides fine-grained permissions scoped per workspace, agent, and data source so teams only access what they need.
Supports SAML, OIDC, and SCIM-based user provisioning integrated with Okta, Azure AD, and Google Workspace for enterprise identity management.
Free trial to get started with Nanonets agents and document extraction, no credit card required.
For large organizations running complex processes at scale with full enterprise controls and compliance requirements.
10,000 customers and a #1 IDP ranking make this an easy AP automation pilot.
“Nanonets has real scale — a billion documents processed annually, 34% Fortune 500 penetration. The OCR-3 model beating GPT-5 and Gemini on extraction accuracy is the kind of claim that either holds under scrutiny or collapses fast.”
The vendor viability question is the only soft spot. No public funding data, but 10,000+ customers and Fortune 500 depth suggest they're not burning cash on hope. That's enough for a pilot commitment, not a five-year lock-in. Private deployment with BYOK and SOC 2 Type II removes the usual enterprise objections before legal even asks.
The AP automation workflow is the clearest win — 3-way PO matching, approval routing to Slack or Teams, and direct ERP posting to SAP, QuickBooks, and NetSuite. That's a full loop, not a point solution. Rossum and ABBYY FlexiCapture do pieces of this; Nanonets does the whole workflow without stitching vendors together.
The tradeoff: pricing is usage-based with no published per-page rate, so cost visibility at scale requires a sales conversation. Run a 90-day pilot on a defined invoice volume before committing to enterprise terms.
OCR-3 ranked #1 on the IDP Leaderboard ahead of GPT-5 and Gemini is a defensible differentiator versus Rossum and AWS Textract.
SOC 2 Type II, ISO 27001, HIPAA, and private deployment options give the board nothing to push back on.
Pre-built invoice and receipt models mean teams can process live documents without custom model training from day one.
End-to-end AP automation with ERP posting advances ops maturity — this replaces manual process, not just a tool already in place.
No public funding data, but 10,000+ customers and 34% Fortune 500 penetration signals a real business, not a seed-stage bet.
Mid-market or enterprise finance and ops teams processing high invoice or document volumes who need a full workflow, not just OCR.
You need transparent usage-based pricing before procurement will approve the pilot budget.
OCR-3 accuracy plus full enterprise controls makes this a serious AP automation bet.
“Nanonets has moved past pure extraction into end-to-end process automation with agentic workflows, ERP posting, and enterprise security that can satisfy procurement. At 10,000+ customers including 34% of Fortune 500, this isn't a startup pitch — it's an operational platform with real deployment scale.”
The compliance stack alone tells you who built this for. SOC 2 Type II, ISO 27001, HIPAA BAA, SIEM streaming via webhook, BYOK, data residency across US/EU/APAC — that's not checkbox security, that's a product that's been through enterprise procurement repeatedly. Private deployment options including on-prem mean regulated industries like healthcare and financial services can actually run this without a fight with InfoSec.
The OCR-3 model claiming the #1 IDP Leaderboard ranking ahead of GPT-5, Gemini, and Claude is a bold, specific claim — and if it holds under your document mix, extraction accuracy is the single variable that determines whether your ops team trusts the output or babysits every queue. The 3-way PO matching, approval routing via Slack and Teams, and direct ERP posting to SAP, QuickBooks, and Sage make this a closed-loop AP workflow, not just a data extraction layer.
The real operational risk is pricing opacity — usage-based per page with no published rates means CFO conversations get awkward fast at volume. Against Rossum or Hyperscience, Nanonets wins on integration breadth; where it may lose is in highly complex document schemas where specialist competitors have deeper domain models. If your document volume is predictable and your ERP is on the supported list, the fit is strong.
Sitting above AWS Textract and Google Document AI on workflow depth while offering more accessible deployment than ABBYY FlexiCapture puts Nanonets in strong mid-market-to-enterprise territory.
3-way PO matching, configurable approval routing, and direct ERP posting map exactly to how finance and operations teams actually run AP workflows.
SAP, QuickBooks, Xero, Sage, Salesforce, Stripe, plus LangChain and LlamaIndex for agent pipelines gives this one of the broadest connection surfaces in the category.
Deep ERP integrations and custom model training create real switching costs by year two — valuable lock-in if the vendor executes, a liability if they don't.
OCR-3 extraction model with a claimed #1 IDP Leaderboard ranking plus agentic end-to-end processing shows genuine R&D investment, not just feature assembly.
Mid-market and enterprise finance or ops teams running high invoice or document volumes who need a full AP workflow, not just extraction.
Your document types are highly specialized and fall outside standard invoice, receipt, or ID schemas where out-of-the-box model accuracy will be lower.
OCR-3 ranks #1, but pricing opacity makes 3-year TCO a guess.
“Nanonets processes 1B+ documents annually with a proprietary model that outperforms GPT-5 and Gemini on extraction benchmarks. No published per-page rate means you're budgeting blind until a sales call.”
Usage-based pricing with no published per-page rate. That's the core procurement problem. Free trial exists, no credit card required — that part's clean. But the only real tier is Enterprise at 'contact sales.' Compare to AWS Textract at $0.0015/page (published). Nanonets forces a negotiation before you can model costs. For a team processing 500K pages/year, the delta between $0.001 and $0.003/page is $500–$1,500 annually — and you won't know which side you're on pre-contract.
The feature set is genuinely strong. OCR-3, 3-way PO matching, SCIM provisioning, private deployment with BYOK, SIEM streaming — this is enterprise-grade infrastructure. SSO isn't paywalled into a hidden add-on tier, which saves the typical $8–15/seat tax common in this category.
Tradeoff: 10,000+ customers and 34% of Fortune 500 adoption suggests real volume, but no public contract terms means auto-renewal windows and termination clauses are unknown. Procurement will push back on that. Budget 2–3 weeks for legal review on the MSA.
Usage dashboards and per-team API budgets help post-contract, but pre-contract procurement friction is high with no self-serve paid tier.
No public auto-renewal window, cancellation terms, or termination-for-convenience clause visible in the evidence.
No per-page rate published; only two tiers visible, with the operative one requiring a sales call.
3-way PO matching and AP automation have measurable cycle-time and error-rate benchmarks; human-in-the-loop review adds a trackable accuracy metric.
SSO included (no add-on tax), but usage overages and year-3 volume costs are unmodelable without a contract.
Mid-market or enterprise AP and ops teams processing high document volumes who can tolerate a sales-negotiated contract.
Your team needs predictable per-unit pricing before a sales call or wants a self-serve paid tier.
OCR-3 beats GPT-5 on benchmarks — but pricing opacity is the daily anxiety
“Nanonets has real extraction muscle: OCR-3 claims the #1 IDP Leaderboard spot ahead of GPT-5 and Gemini, and the 3-way PO matching plus ERP posting covers the full AP loop. Usage-based pricing with no public per-page rate means finance teams approve a tool they can't budget without a sales call.”
The approval routing to Slack and Teams is the right instinct. Knowledge workers don't want another tab — they want the exception to find them. Configurable approval gates that land in the tools already open on your screen means the human-in-the-loop review doesn't break the day. That's a real workflow win over ABBYY FlexiCapture, which routes exceptions back into its own UI.
The friction lives in pricing. Usage-based per-page with no published rate means every team using it heavily sits on cost anxiety. The usage dashboards and per-team API budgets help manage it, but a knowledge worker running month-end invoice processing at volume can't estimate exposure without a rep. That's a workflow fight that compounds.
Private deployment, BYOK, SCIM provisioning, and SOC 2 Type II are all present — that's the enterprise security checklist done. The 10,000+ customer base including 34% of Fortune 500 suggests the infrastructure holds at scale. For AP-heavy ops teams, this is genuinely feature-complete.
Pre-built invoice and receipt models reduce cold-start pain, but no-code model labeling still demands upfront document tagging effort before custom extraction stabilizes.
Docs exist and the API supports LangChain and LlamaIndex integrations, suggesting developer-oriented writing, though depth for non-technical ops users is unconfirmed from public evidence.
Usage-based pricing with no public per-page rate creates recurring budget uncertainty; the cost dashboard helps but doesn't eliminate the anxiety.
Agentic Data Extraction API with structured JSON and Markdown output, webhooks, SIEM streaming, and BYOK deployment give technical users a real ceiling to grow into.
Approval routing to Slack, Teams, and email plus direct ERP posting to SAP, QuickBooks, and Xero means extracted data moves downstream without manual re-entry.
Finance and operations teams running high-volume AP or document intake who need ERP sync and enterprise security without building extraction infrastructure from scratch.
You need transparent per-page pricing before committing budget, or your document volume is low enough that the usage-based model won't justify the sales cycle.
OCR-3 is legitimately impressive, but pricing opacity will slow you down
“Nanonets is a serious document processing platform trusted by 34% of Fortune 500 companies, with enterprise security that actually competes with the big players. The no public per-page pricing is a real friction point for anyone trying to budget before a sales call.”
The OCR-3 model ranking above GPT-5 and Gemini on the IDP Leaderboard isn't just marketing copy — that's a meaningful claim in a category where extraction accuracy is everything. Pre-built models for invoices, receipts, and ID documents mean you're not starting from zero. The 3-way PO matching and approval routing into Slack or Teams is the kind of workflow glue that finance teams actually need, not just a nice demo feature.
The enterprise security stack is genuinely thorough: SOC 2 Type II, ISO 27001, HIPAA, private VPC deployment, BYOK, SIEM streaming. For a mid-market AP team worried about document data leaving their perimeter, this clears the IT checklist. Rossum and ABBYY FlexiCapture compete here but rarely hit all these boxes without heavy implementation work.
The tradeoff is the pricing wall. Usage-based per-page with no published rates means you can't self-serve a budget. Web-only platform with zero mobile story is fine for a desktop workflow tool, but worth knowing going in.
Human-in-the-loop review interface and configurable approval gates suggest real thought about the daily correction workflow, though no changelog makes it hard to track how fast rough edges get fixed.
No-code model training and pre-built templates lower the floor, but agentic pipelines, SCIM provisioning, and SIEM streaming assume a technically capable admin within a few months.
Web-only platform with no mentioned mobile app — approval routing to Slack or email softens the pain slightly but it's not a mobile product.
Free trial with no credit card plus pre-built models for common document types means you can process a real invoice without training anything on day one.
Processing over a billion documents annually for 10,000+ customers, with low-confidence flagging and audit logs for every agent run, suggests a platform that's been stress-tested.
Mid-market finance and operations teams processing high invoice or form volumes who need enterprise-grade security without a 12-month implementation.
You need transparent per-page pricing to self-serve a budget without talking to sales.
OCR-3 claims #1 on the leaderboard — that's either real or it ages poorly fast
“Solid IDP platform with genuine enterprise controls, a proprietary extraction model, and AP automation depth that commodity OCR tools can't match. The 'no pricing listed' pattern is a yellow flag, and the leaderboard self-citation needs external verification.”
Three tells upfront. One: 'Trusted by 10,000+ enterprises' in the meta, but no named case studies in the evidence. Two: no changelog listed — can't verify shipping cadence. Three: 'OCR-3 ranked #1 on the IDP Leaderboard' with no third-party source cited. That's the kind of claim that either holds up under scrutiny or doesn't.
What's actually here is substantial. Private deployment with BYOK, SIEM streaming, SCIM provisioning, SOC 2 Type II, ISO 27001, HIPAA BAA — that's a real enterprise stack. Three-way PO matching plus approval routing to Slack and Teams covers the AP automation use case end-to-end. Rossum and Hyperscience charge comparable enterprise rates with fewer deployment options. AWS Textract wins on raw infra but lacks the human-in-the-loop workflow layer.
Exit portability is decent — REST API with JSON/Markdown output means your data isn't locked in a proprietary schema. The tradeoff: usage-based pricing with no public per-page rate makes TCO opaque until you're deep in a contract.
Proprietary OCR-3 model plus end-to-end AP automation in a single platform separates it from AWS Textract (raw OCR, no workflow) and Rossum (workflow, no private deployment depth).
REST API outputs structured JSON and Markdown; LangChain and LlamaIndex integrations mean extraction logic can be rebuilt elsewhere without full vendor lock-in.
No changelog, no public funding data visible — but 10,000+ customers and Fortune 500 penetration claims, if real, suggest enough revenue base to not be a 12-month shutdown risk.
The OCR-3 #1 leaderboard claim is unverified in the evidence, and '34% of Fortune 500' with no named customers is the kind of superlative that ages poorly.
Matches the pattern of IDP vendors that survived — deep vertical workflow (AP automation), enterprise security stack, API-first — not the pattern of ones that didn't.
Mid-market or enterprise finance and ops teams processing high invoice or document volumes who need AP automation plus deployment flexibility.
You need transparent usage pricing before a sales call, or you're a small team running low document volumes where commodity OCR is good enough.
Common questions answered by our AI research team
Nanonets holds SOC 2 Type II, GDPR, ISO 27001, and HIPAA certifications. A BAA is available for enterprise plans.
Nanonets integrates with SAP, QuickBooks, Xero, and Sage for ERP/accounting, plus Salesforce, HubSpot, Stripe, and Zendesk for CRM and payments.
Nanonets OCR-3 is ranked #1 on the IDP Leaderboard, ahead of GPT-5, Gemini, and Claude.
Yes. Nanonets supports VPC, single-tenant cloud, and on-premises deployment, with your own keys, infrastructure, and network policies.
Agents route uncertain or edge-case items to a human via configurable approval gates in Slack, Microsoft Teams, or email for review.
Nanonets is a San Francisco-based document processing platform that uses OCR and machine learning to automate data extraction and document workflows for enterprises.
