Nanonets
AI agents for enterprise data processing: read, validate and post documents into your systems of record.
By Nanonets · HQ San Francisco, US · 4.2/5 Value-Position score (estimate)
Positioning guardrails
Best for
- Finance and shared-services teams processing high volumes of invoices, POs and remittances who want straight-through posting into SAP, NetSuite or QuickBooks
- Enterprises that need SOPs, policies and tribal knowledge encoded into auditable agents instead of rebuilt in a workflow tool
- Operations teams in logistics, manufacturing and healthcare that must extract data from messy multi-format documents such as faxes, scans and EDI
- Companies already running their own agent stack (Claude, ChatGPT, Bedrock, Vertex) that want governed document context behind it
- Security-conscious buyers needing VPC or on-prem deployment, data residency and SIEM-streamed audit logs
Ideal size: 5–500 person finance and ops teams people · Mid-market to Fortune 500 with a finance or shared-services function and a live ERP
Not for
- Teams looking for a general-purpose LLM platform or chatbot; Nanonets is purpose-built for document-heavy processes
- Very low-volume users, since pricing is per block run and the value comes from volume
- Buyers expecting a fully self-serve rollout with no vendor engineering involvement
- Organisations that need published per-seat list pricing; Growth and Enterprise are quote-based
Value metrics scorecard
Time-to-Value
3–6 weeks (some in days)
~30 days to first production value
Total Cost of Ownership
$12,000/yr
Starts at $1,200 · Usage-based credits, billed per workflow block: $0.02 simple operations, $0.10 standard AI, $0.30 complex AI. No platform fees or seat licences; $50 free credits to start.
Implementation Friction
2/5
Engineering + admin effort required
Value-Position score
out of 5 · model estimate
Full cost breakdown
Mandatory implementation fee
None
Seat tiers
Up to 3 users on Starter; credits shared team-wide on Growth and Enterprise; no per-seat licences.
Add-on costs
- Extra credits: $100 per month for 100 credits on the Starter plan.
- Growth and Enterprise are volume-priced on quote, with discounts up to 40%.
- Private cloud or on-prem deployment and custom connectors are scoped with the vendor (Enterprise).
Company & support
Who is behind Nanonets, and how your team gets help once it is live.
Company
- Founded
- Not recorded
- Headquarters
- San Francisco, US
How you get support
- PhoneNot listed
- EmailNot listed
- Live chatNot listed
- Support portal / ticketsNot listed
- Community forumAll plans
- Help centre / docsNot listed
- Dedicated account managerEnterprise only
- In person / on-siteNot listed
- Hours
- Not recorded
- Response time
- Not stated
Starter (including the free tier) lists community support. Enterprise adds dedicated support with SLAs. No 24/7 or business-hours commitment is published.
“Not listed” means the vendor’s public pages don’t mention that channel, not that it is unavailable. Ask about it during evaluation.
Market position
Where Nanonets sits against its closest alternatives. Pick any two of cost, speed, friction and buyer score, and up to 9 companies to compare.
Quadrant view
Typical annual cost × Time-to-value
The lines cross at the median of the solutions shown, so about half sit on each side of each line. A dashed ring marks an outlier pinned to the edge; hover for its value.
Companies on the chart 6 / 10
- Nanonets
- Datadog
- TrueContext
- Alloy Software
- Budibase
- SysAid
Add or change companies
Up to 10 companies including Nanonets. Listed closest first.
Stack fit signal
Compatibility with standard B2B ecosystems.
No supported MCP path today, so it cannot be driven from an AI client.
AI & MCP readiness
What Nanonets ships in AI, and what it asks of your ecosystem.
AI features shipped
Agents complete document workflows end-to-end and encode business rules into the Trail context graph, with every rule traceable to its source. Nanonets OCR-3 is the vendor's proprietary extraction model. Confidence scores gate autonomy and route exceptions to humans, and every agent run, approval and data access is logged and streamable to a SIEM.
Your data & models
- Trains on your data
- Never trains on your data
- Runs on
- Its own models
- AI pricing
- Billed by usage or credits
In your ecosystem
- AI connection
- Not supported
- Model key
- Not recorded
- AI usage audit
- Full audit trail
Compliance attestations
* IAPP AIGP certifies individuals, not products. It means named staff hold the credential — not that the platform does.
Bottom line
Nanonets turns document-heavy business processes into AI agents. It reads invoices, POs, bills of lading, claims and supplier records, applies encoded business rules through its Trail context graph, and posts validated data into SAP, NetSuite, Salesforce, QuickBooks or a warehouse. Pricing is usage-based per workflow block, with $50 in free credits and no seat or platform fees. 10,000+ customers and 34% of the Fortune 500 use it, with case studies reporting 80–99% reductions in manual processing time.
Frequently asked questions
How is Nanonets priced?
Usage-based. Every workflow step is a block and you pay per run: $0.02 for simple operations, $0.10 for standard AI such as classification and validation, and $0.30 for complex AI such as data extraction and generative AI. There are no platform fees or seat licences. Accounts start with $50 in free credits, then $100 per month for 100 credits on Starter; Growth and Enterprise are quote-based with volume discounts up to 40%. A typical invoice runs 4–6 blocks, which the vendor puts at under $2 per invoice end to end.
How long does it take to get an agent into production?
Weeks rather than quarters. Nanonets says its forward-deployed engineers target production in weeks, and customers report specific deployments in days — Expatrio cites a two-day passport-OCR deployment and Ascend Properties was live in under two weeks, plugged into its existing stack with no rip-and-replace.
What happens when an agent is unsure or hits an edge case?
Confidence scores decide autonomy. Below threshold, the agent routes the item to a person with context, through approval gates in Slack, Teams or email. Every correction feeds back into the rulebook, so the share of work cleared autonomously rises over time, and the system surfaces conflicting rules and proposes fixes for review.
Does Nanonets replace our ERP or our existing agent platform?
No. It writes into the systems you already own — SAP, NetSuite, Oracle, Dynamics, QuickBooks, Salesforce, Snowflake and 25+ other connectors — and your existing agents can call it through an MCP server, native retrievers or REST/GraphQL. The vendor explicitly positions this as no rip-and-replace and no replatforming.
Is our data used to train AI models, and where is it stored?
Nanonets states that data accessed through Google APIs is not retained or used to train generalised or foundational models, and that subprocessors are contractually barred from training on it. Customer-instructed extraction models stay inside that customer's tenant and can be deleted. Deployment options include VPC, single-tenant cloud or on-prem, with data residency pinned to US, EU or APAC.
What evidence is there that this works at enterprise scale?
Nanonets reports 10,000+ customers, 34% of the Fortune 500 and over a billion documents processed. Published case studies include Mondelez (over $3M annual savings, 10x ROI), UniPro Foodservice (93% touchless order processing, 10,000 hours a year saved) and Schneider Electric (90%+ PR-to-quote match rate across 70 countries).