Nanonets IC Card OCR
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What is Nanonets IC Card OCR
Nanonets IC Card OCR is an AI-based OCR product focused on extracting structured data from identity cards (for example, national IDs and driver’s licenses) from images or scans. It is used by teams that need to automate onboarding, KYC-style data capture, or back-office data entry into downstream systems. The product typically provides pre-trained ID card extraction and exposes results through an API and configurable workflows for field mapping and validation. It fits organizations that want a vendor-hosted OCR service rather than building and training models from scratch.
ID-card focused extraction
The product is designed around identity card use cases, which can reduce the amount of custom configuration needed compared with general-purpose OCR. It emphasizes structured field extraction (e.g., name, ID number, date of birth) rather than only returning raw text. This focus can simplify integration into onboarding and verification workflows. It is well-aligned to scenarios where consistent fields are required across many documents.
API-first integration options
Nanonets commonly supports programmatic consumption of OCR results via API, which helps engineering teams embed extraction into web and mobile applications. API delivery supports automated processing at scale and easier connection to downstream systems (CRM, ERP, case management). This approach can be more straightforward than desktop-centric capture tools for product-led integrations. It also supports building custom validation and exception handling around the OCR output.
Configurable field mapping
The product typically supports mapping extracted values into a defined schema, which helps standardize outputs for storage and analytics. Configuration can reduce manual post-processing when document layouts vary across issuers or countries. This is useful for teams that need consistent JSON/CSV outputs for multiple ID types. It supports operational workflows where humans review low-confidence fields.
Narrower than full IDV
IC Card OCR focuses on text and field extraction, but end-to-end identity verification often requires additional capabilities (e.g., liveness checks, face match, fraud signals, and document authenticity checks). Buyers may need separate tools or custom development to cover those requirements. This can increase vendor count and integration effort. It is best positioned as a component within a broader verification workflow.
Accuracy depends on image quality
As with most OCR, performance can degrade with glare, blur, low light, compression artifacts, or partial captures common in mobile photos. ID cards with security patterns, holograms, or non-Latin scripts can also increase error rates depending on model coverage. This can lead to higher manual review rates in production. Teams should plan for confidence thresholds and exception queues.
Data residency and compliance fit
Using a hosted OCR service for identity documents can raise data residency, retention, and compliance requirements (e.g., contractual controls, regional processing, auditability). Some organizations require on-premises deployment or strict regional hosting that may not match all vendor offerings. Legal and security reviews can extend procurement timelines. Buyers should confirm encryption, retention controls, and regional processing options.
Plan & Pricing
Pricing model: Pay-as-you-go (credit-based, charged per workflow block run). Free credits on signup: $200 worth of credits when you sign up. Credit / block prices (official docs: "Base price per unit") – values are in credits per run:
- Data Extraction AI – 0.30 credits / run
- Classification AI – 0.10 credits / run
- Checkbox Detection AI – 0.10 credits / run
- Barcode Detection AI – 0.10 credits / run
- Signature Detection AI – 0.10 credits / run
- QR Code Detection AI – 0.10 credits / run
- Import (Email, API, Google Drive, Dropbox, SharePoint, OneDrive) – 0.04 credits / run
- Data Formatting (Date, Numbers, Text, Regex etc.) – 0.02 credits / run
- Data Lookup (Google Sheets, MySQL, MariaDB, PostgreSQL, CSV, MSSQL) – 0.04 credits / run
- Data Export (Databases/Document Management) – 0.04 credits / run
- Human-in-the-Loop (managed services) – 1.00 credit / page (Enterprise)
- Model Versioning – 50 credits / month (Enterprise)
- AI Confidence Scores – 500 credits / month (all plans)
Prepaid Credits / Volume discounts: Prepaid Credits are available (buy credits upfront to receive bonus value/discounts). The "Credits Accelerate" program offers volume-based discounts and other benefits; contact Sales for tiers and enterprise quoting.
Other paid items noted on official site:
- OCR Docker image (on-prem / docker) – prices start at $499 / month (per docs) — requires Pro / Enterprise as specified in docs.
Free tier / trial details:
- The site provides $200 worth of free credits at signup (trial credits). Some product pages (e.g., Invoice OCR) reference first 100 invoices free as an example for that tool.
Notes / caveats:
- Prices on the docs are expressed in "credits"; the public docs list credits-per-run for blocks but do not publish a public per-credit USD conversion or fixed $/scan price for general pay-as-you-go (contact Sales or buy Credits for USD pricing/discounts).
- Pricing page notes an update on January 31, 2025; contact Sales/account manager for existing-customer details.
Seller details
Nanonets, Inc.
San Francisco, CA, USA
2017
Private
https://nanonets.com/
https://x.com/nanonets
https://www.linkedin.com/company/nanonets/
