End-to-end workflow execution
Nanonets Agents read messy inputs, apply business rules, and complete work inside systems of record instead of stopping at extraction.
Nanonets
Nanonets is an AI platform for automating enterprise document and data workflows, including accounts payable, claims, order management, and document extraction. It connects to systems such as SAP, Salesforce, and Oracle, and offers a starter plan with $200 in credits.
Overview
Nanonets is an AI-powered enterprise data processing platform that combines managed agents with document extraction APIs. It is designed to handle manual business workflows such as accounts payable, order management, claims processing, contract analysis, and invoice or rate-card reconciliation.
The platform reads documents and other inputs, validates them against business rules, and posts results into connected systems such as SAP, Salesforce, Oracle, and other business tools. Nanonets also offers an extraction API for teams that need structured output from complex documents for LLM pipelines, RAG systems, and automation workflows.
Core capabilities
System integrations across work tools
The platform integrates with enterprise tools including SAP, Oracle, Salesforce, Google Drive, Slack, Microsoft Teams, Gmail, Jira, Asana, Snowflake, and common finance apps.
Runbook-driven onboarding
The agents can ingest SOPs and runbooks written in natural language, then use them to guide task execution.
Human-in-the-loop review gates
When the agent is unsure, it can route cases to Slack, Teams, or email for human review and approval.
Auditability and traceability
Every extracted field can link back to its source, with side-by-side citations, context-aware viewing, and discrepancy detection.
Structured output for document pipelines
The extraction product returns clean markdown and structured JSON, and is built for parsing, splitting, chunking, and extraction workflows.
Common use cases
Accounts payable automation
Automate invoice intake, 3-way matching, approval routing, and ERP posting for accounts payable teams.
Rate card reconciliation
Validate freight invoices or similar charges against rate cards, reconcile discrepancies, and flag exceptions for review.
Order management
Process orders across inboxes and approval chains, then route clean data into systems of record.
Claims and reimbursement processing
Handle claims or reimbursement workflows where documents, validation rules, and human review are part of the process.
Document parsing for AI pipelines
Extract structured data from complex documents for RAG pipelines, LLM applications, and downstream automation.
Pros and Cons
Pros
- Covers both managed agents and a document extraction API in one platform.
- Supports end-to-end workflows rather than only reading or classifying documents.
- Connects with many common enterprise systems, including ERP, CRM, storage, chat, and ticketing tools.
- Provides human review options, audit logs, and source-linked outputs for controlled workflows.
- Offers a starter option with $200 in credits and no platform fees on the entry plan.
Cons
- The source does not show a detailed public implementation timeline or setup effort for every workflow.
- Pricing is usage-based and tied to block runs, so end cost depends on workflow design and volume.
- Some capabilities such as private deployment, custom integrations, and enterprise controls are positioned primarily for higher-tier plans.
FAQ
How are Nanonets agents different from a chatbot or copilot?
Nanonets Agents complete workflows end to end by reading inputs, applying business rules, and posting results into systems of record. The source material contrasts this with chatbots and copilots, which assist a person rather than finish the process.
What systems can Nanonets connect to?
The source says agents can run across ERP, inbox, storage, and collaboration tools, and lists systems such as SAP, Oracle, Salesforce, Google Drive, Slack, Microsoft Teams, Gmail, Jira, Asana, Snowflake, QuickBooks, Xero, Sage, Stripe, HubSpot, Zendesk, Dropbox, Box, and Notion.
Is there a free trial or starter option?
The pricing page says every account starts with $200 in credits, with no platform fees on the Starter plan and no credit card required to start. It also says paid usage is measured by block runs.
How do you get started?
For the agent product, the source says you can upload existing runbooks and SOPs, and the agent reads those instructions to start executing. For the extraction API, the quick-start flow is to upload a document and get structured data back.
Can humans review or approve work before it is finalized?
The source describes configurable approval gates, human review through Slack, Teams, or email, and audit logs for each run. It also says the platform supports private deployment, data residency options, and enterprise controls.
Quick Facts
- Category
- AI agents for enterprise data processing
- Website
- nanonets.com
- Primary use
- Automating document-heavy business workflows and extraction pipelines
- Deployment options
- Cloud, private VPC, single-tenant cloud, and on-prem
- Pricing model
- Pay per block run with a free Starter plan
- Start option
- $200 in credits included on the Starter plan
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