Nanonets
Customers send invoices, receipts, and forms. Your Tars AI agent processes them through Nanonets OCR models in real time, extracting line items, totals, and key fields. Documents that used to require manual entry now get parsed automatically within the same chat.
From invoice parsing to model training, your AI agent manages the full Nanonets document processing lifecycle through natural conversation.
Nanonets
See how businesses automate invoice processing, receipt extraction, and document classification through AI agents that talk to Nanonets behind the scenes.
A vendor emails an invoice. Your AI Agent picks it up, sends it to the Nanonets OCR model, and extracts vendor name, line items, due date, and total amount. The structured data flows directly into your accounting system. Your AP team reviews verified numbers instead of typing them manually, cutting processing time by 90%.
An employee submits a blurry receipt photo via chat. Your AI Agent uploads it to Nanonets, which extracts the merchant, amount, and date despite poor image quality. The agent confirms the extracted details with the employee and flags any missing fields before the expense report is finalized. No more back-and-forth emails.
A partner uploads a batch of mixed documents: contracts, purchase orders, and invoices. Your AI Agent sends each through the appropriate Nanonets model based on document type, extracts relevant fields, and routes the structured data to the right department. Finance gets invoices, procurement gets POs, legal gets contracts.
Nanonets
FAQs
The agent can process any document type you have a Nanonets OCR model trained for. Common examples include invoices, receipts, purchase orders, bank statements, ID cards, and medical forms. If your model can extract it, the agent can trigger it.
Nanonets achieves 99%+ accuracy on invoice extraction with no template setup required. The AI-driven OCR handles varying invoice formats, handwritten elements, and low-quality scans. Accuracy improves further as you train models with your specific document layouts.
The agent can create a new model and upload training images via file path or URL. However, the actual model training runs asynchronously on Nanonets servers. The agent can check training status and notify you when the model is ready.
Tars passes documents to the Nanonets API for processing. The documents are stored and managed within your Nanonets account according to their data retention policies. Tars does not maintain a separate copy of your processed documents.
The agent receives the extraction results including confidence scores for each field. Low-confidence or missing fields are flagged in the conversation, and the agent can ask the user to verify or manually provide the missing information before proceeding.
Yes. Nanonets processes multi-page PDFs and images as part of its OCR pipeline. The agent submits the full document and receives extracted data from all pages, organized by the fields your model is configured to capture.
The dashboard requires users to log in, upload files, and navigate interfaces. With Tars, anyone in your organization can submit documents through chat and receive extracted data instantly. It eliminates the training barrier for non-technical team members.
Tars requires your Nanonets API key encoded in Base64 for Basic Auth. This key is stored securely in your Tars dashboard. You can generate the API key from your Nanonets account settings and revoke it anytime.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
Privacy & Security
At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.
Email - sales@hellotars.com
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