Independent editorial guide, written with AI assistance. Examples are hypothetical; no hands-on product testing or owner interviews were performed. Features and prices may change. Our editorial method.
Evidence note: Features and pricing were checked against the official Nanonets homepage and pricing page on 2 November 2026. Vendor pages change, so confirm details before you commit. ShiftToAGI is an independent publisher and is not affiliated with Nanonets.
Nanonets is a commercial platform that extracts data from business documents and runs it through workflow steps and AI agents built around your business rules (homepage). Each workflow step is called a block, and usage is charged per block run (pricing).
A hypothetical situation. Priya runs operations at a fictional 40-person kitchenware distributor. Supplier invoices arrive as emailed PDFs, phone photos and the occasional scanned fax. One accounts payable coordinator types each invoice into the accounting system and checks it against the purchase order. Last month a supplier billed 120 units against a PO for 100, and nobody caught it before payment. Priya wants the checking automated, but she will not let software pay suppliers on its own, and she cannot yet tell whether per-step pricing costs less than her coordinator's time. Control, effort and unknown cost pull in different directions. This profile is meant to help you weigh them.
What is Nanonets, in plain terms?
It helps to picture three layers:
- Reading documents. AI blocks pull fields and line items out of invoices, POs and similar paperwork.
- Moving data. Simpler blocks format fields, route items and export results. This is ordinary automation, not model judgement.
- Deciding. Agents apply rules to the extracted data and either act or ask a person.
The homepage frames the product around enterprise processes, including accounts payable, order management and supplier onboarding (homepage). For a smaller business, the first two layers are usually where a pilot starts. The third deserves caution wherever money is involved.
Which Nanonets features matter for procurement documents?
Extraction and classification, split by plan
The Starter plan lists data extraction AI. Classification AI, barcode and signature detection, and generative AI blocks appear on the Growth plan (pricing). In practice, automatically sorting a mixed inbox into invoices, POs and credit notes may require Growth, while extracting fields from one known document type may be possible on Starter. Confirm the boundary with the vendor before you design the workflow around it.
AI blocks versus ordinary automation
The pricing page groups blocks into three tiers: simple operations (formatting, routing, export), standard AI (classification, validation) and complex AI (data extraction, generative AI) (pricing). The split is useful beyond cost. Routing a file involves no reading of the document. Extraction does, and a smudged fax is where a misread is most likely, so that step deserves the closest review.
Rules drawn from your own procedures
The homepage describes Trail, a context graph that turns uploaded SOPs and policy documents (PDF or DOCX) into rules traceable to their source, with an example showing extracted rules offered for approval, editing or rejection (homepage). It also describes extracting unwritten rules from Slack, Teams, Zoom and email. Trail is presented as coming from the team behind Nanonets, and the pricing page does not mention it, so ask which plan, if any, includes it.
Confidence scores and approval gates
The vendor says confidence scores determine whether an agent acts alone or asks a person, that human input on exceptions feeds learning, and that approval gates can route edge cases to Slack, Teams or email (homepage). The approval gates appear in the homepage's enterprise controls list, and plan availability is not stated, so confirm this before relying on it for a Starter pilot.
Connections and controls
Starter lists API access, email integration, cloud storage connectors and up to three users. ERP and database integrations and custom Python blocks sit on Growth. SAML SSO, role-based access control and audit logs sit on Enterprise (pricing). The homepage also mentions an MCP server and REST/GraphQL API for connecting existing agent platforms (homepage).
Who does Nanonets suit?
It fits businesses where documents arrive in inconsistent formats and someone already spends hours retyping them: distributors, wholesalers, manufacturers, agencies with many subcontractors and multi-site operators buying from many suppliers. It also suits teams willing to write down their matching rules, because an agent cannot follow a rule nobody has stated. If your rules live in one person's head, plan pilot time for making them explicit.
What can different roles use it for?
These are potential applications inferred from documented capabilities, not tested results.
- Finance or bookkeeping: extract supplier invoice headers and line items, then flag quantity or price differences against the matching PO before the payment run.
- Procurement: compare supplier order confirmations with the PO you sent, looking for substituted products or changed delivery dates.
- Sales operations (B2B sellers): read customer POs that arrive as PDFs or scans and prepare draft sales orders for a person to confirm.
- Operations or compliance: gather supplier onboarding paperwork, such as insurance certificates, and list missing or expiring items for follow-up.
- Founders: use the rule-capture idea to document how exceptions are actually approved today, which has value even if no decision is ever automated.
How could an invoice-to-PO check pilot work?
This workflow is a proposal using fictional data. It is not a product test and does not describe Nanonets screens. Where a step depends on configuration that the sources do not document, it is marked.
- Define the scope. One supplier category, one document type: supplier invoices that should match an existing PO. Exclude credit notes and invoices without a PO number for the first month.
- Prepare inputs. All monetary values in this fictional fixture are GBP. Require a currency field on both records and stop if currencies are missing or differ. Fictional invoice: Harbour Pans Ltd, INV-3307, PO-1182, 120 x 28cm skillet at 14.50, subtotal 1,740.00 before tax. Fictional PO-1182: 100 units at 14.50, subtotal 1,450.00. If you use real samples for setup, remove bank details and personal data first.
- Extract fields. Configure extraction for supplier name, invoice number, PO number, currency, date, line description, quantity, unit price, line total, tax and invoice total.
- Compare against the PO. A comparison step checks quantity and unit price per line against an export of open POs. How the PO list reaches Nanonets (cloud storage file, API or a Growth-plan ERP connection) and which block performs the comparison are configuration unknowns to settle with the vendor. Sample output: INV-3307 / PO-1182: quantity mismatch, invoiced 120, ordered 100, potential overbilling of 20 x 14.50 = 290.00 before tax, subject to checking approved amendments and delivery records. Status: hold for review.
- Handle missing data. If the PO number is absent, unreadable or not in the PO list, the item is marked "needs PO" for a person. The workflow must never guess a PO from the supplier name.
- Require human approval. During the pilot, every invoice, matched or flagged, is reviewed by the AP coordinator. Nothing is posted to accounting or queued for payment without a named person signing off. If built-in approval gates are not available on your plan, keep this step outside the tool.
- Measure. Over four weeks, track: share of invoices with every extracted field correct on review; mismatches caught versus mismatches found later; review minutes per invoice against your manual baseline; and block runs and credit spend per invoice.
- Stop or roll back. Pause if an unflagged field error would have changed a payment amount, if spend per invoice exceeds your agreed ceiling, or if reviewers start approving without reading. Return to the manual process, fix the setup, then restart.
Configuration brief you can copy
Use this as a written brief for your team or a vendor demo. Adapt field names to your documents.
Goal: Extract supplier invoice data and compare it with our open purchase orders.
Documents in scope: Supplier invoices that reference a PO number. Exclude credit notes.
Fields: supplier_name, invoice_number, invoice_date, po_number, currency,
line_items[description, quantity, unit_price, line_total], tax_amount, invoice_total.
PO source: Weekly export of open POs (confirm with vendor how this is loaded).
Matching rules:
- Match on po_number exactly. Never infer a PO from supplier name.
- Flag any line where quantity differs from the PO.
- Flag any line where unit_price differs from the PO at all.
- Flag if invoice_total does not equal sum of line totals plus tax_amount.
Missing data: If a required field is empty or unreadable, send to review with the
reason stated. Do not fill blanks with estimates.
Approval: All outputs need human approval before export. No automatic posting
or payment during the pilot.
Privacy: Do not extract or store supplier bank account details in this workflow.
Report: Weekly count of matched, flagged and missing-data items, plus block runs used.
Questions for vendor: Which plan covers the comparison step, approval routing and Trail?
What does Nanonets cost, and what are the limits?
As checked on 2 November 2026, the Starter plan starts with 50 US dollars in free credits, no card required, then lists 100 US dollars per month for 100 credits, for up to three users (pricing). The page does not state taxes, regional pricing or how much block usage one credit covers.
Block prices are listed at 0.02 US dollars per simple run, 0.10 per standard AI run and 0.30 per complex AI run (pricing). Because the credit-to-block conversion is not stated, estimate cost from your own pilot spend rather than from the vendor's per-invoice estimate. Growth and Enterprise numeric prices were not verified; both point to sales.
Plan around these limits: classification and ERP integrations sit above Starter; SSO, role-based access and audit logs sit on Enterprise; poor scans will still need review; and the vendor's accuracy claims are not evidence about your documents.
Who should skip Nanonets?
Skip it if you handle a few dozen invoices a month, where careful manual entry may cost less than setup and review. Skip it if your accounting software already reads supplier invoices well enough for you. Hold off if you have no PO records, since there is nothing to match against. If you need SSO, audit logs or data residency from day one, start with an Enterprise conversation instead of Starter.
FAQs
Should I let it approve and pay invoices on its own? No, not at first. Keep a person on every approval until your own pilot numbers show reliable extraction and matching on your documents, and keep payment release with a person even after that.
Do I need a developer? Possibly not for a narrow extraction pilot. Loading PO data, connecting an ERP or writing custom logic may need technical help or a higher plan. Ask the vendor which parts they would configure for you.
What should I bring to a demo? Ten to twenty redacted invoices covering clean PDFs, poor scans and one awkward supplier format, the matching POs, and your written matching rules. Ask them to show how a missing PO number is handled.
Next action
This week, export one month of supplier invoices and POs, count how many arrived and how long each took to check, and write your matching rules on one page using the brief above. That baseline tells you whether the free credits are worth spending on a trial.
Methodology
This profile is an AI-assisted draft based only on official Nanonets documentation retrieved on 2 November 2026. The workflow, company and data are illustrative and fictional; no hands-on test was performed. Vendor statistics and testimonials were deliberately excluded. Published by ShiftToAGI, Shifting Founders Beyond AI.