Canonical: https://instain.ru/en/ai/nanonets/ Language: en Nanonets Platform # Nanonets. Document data extraction and workflow agents 4.38 / 5 [Directory score](https://instain.ru/en/ai/nanonets/#editorial-rating) [Official website ](https://nanonets.com/) Nanonets extracts information from documents and supports data-processing workflows. ![The official Nanonets page with a description of the product features.](https://instain.ru/assets/images/nanonets-screen-669aad8ce350-1200.webp) Nanonets official product page. [Open the source ](https://nanonets.com/) ## From document to verifiable record Nanonets helps transform documents and other incoming data into structured records and workflows. The current platform covers not only recognition, but also AI agents acting according to the rules of the organization. The document remains the basis on which the extracted information is checked. Define the fields and processing rules first. An organization name, amount or document number may occur in several places with different meanings. Clear rules matter more than expecting the system to understand every unusual form. ## Build a sample register from a small batch Use your own anonymized documents with different layouts. Configure field extraction and preserve the link to each source file. Test an ordinary example, then a blurry image, a missing field and a duplicate upload. Review amounts and dates manually. A decimal separator, currency or minus sign can substantially change a record's meaning. Send an uncertain field for review rather than fill it with a similar-looking value. Separate recognition from decision-making before enabling external actions. Reading an amount correctly does not mean a document is approved or a payment is authorized. An accounting-system connection needs its own access controls and exception rules. ## Prepare examples of exceptions Include realistic exceptions in the test batch: a rotated page, unreadable passage, several totals or a resubmitted file. Define the correct action for each in advance. This lets you test rule changes without relying on the overall impression from a few successful examples. ## Resources and cost of the work process The official offering uses credits and provides a starting allowance for evaluation. This is not permanent free document processing. Later costs depend on operations and volume; enterprise implementation has separate terms. A whole chain should be evaluated: obtaining a document, extracting, checking, transferring data and correcting errors. For regular work, save the test set and return to it after changing the template. Even a successful process does not guarantee the correct processing of all future documents. ## Suitable tasks - Extract fields from documents - Build a sample register - Configure exception checks Features ## Strengths - Extraction is connected to workflows - There is processing and control of exceptions Things to consider ## Limitations - Complicated documents need to be verified - Starting credits are not permanent free access ## Selection and conditions Free access Not confirmed Trial period Yes No sign-up required Not confirmed Russian interface Not confirmed Local installation Not confirmed API Yes “Not confirmed” means there is not enough information. The feature may still be available; check the developer’s terms. Input formats Document, Image, Data Result Table, Data, Text ### Terms Documents follow configured fields and rules. Starting credits are limited; costs depend on operations. Review uncertain extractions and external actions separately. From task to first result ## Practical example Task Extract fields from documents What to prepare Several original anonymized files containing practice requests, plus a table of allowed categories. ### Task brief or prompt Compile one request register, flag duplicates, and list unclear rows separately. Retain the source filename for each record. Do not invent missing dates, delete source files, or send the result. Return an editable spreadsheet for manual review. ### Expected result A draft register file with traceable row provenance; tool execution does not guarantee data accuracy. ### How to check the result - Check blank fields, duplicates, multiline records, and totals. - Open the returned file in the target program and check the formulas. - Limit the agent’s access to the necessary materials and check external actions separately. An editorial teaching example of a task brief, not the result of hands-on testing of the service. Check that the required mode is available, that you have rights to the source material and that the intended use of the result is permitted. Check details ## Official sources - [Official features of Nanonets ](https://nanonets.com/) - [Nanonets Help and Terms ](https://nanonets.com/pricing) This description is based on the developer’s material. Features, prices and availability may change; check the primary source before use. About the tool Developer Nanonets Category [Work and study](https://instain.ru/en/category/productivity/) Access Account and configuration of document processing or corporate process. Payment There are start-up credits; further processing and implementation are paid under the terms of the offer. API Yes, from the developer [Developer terms ](https://nanonets.com/pricing) Directory score 4.38 / 5 Features 4.50 / 5 Workflows 4.30 / 5 Ecosystem 4.40 / 5 Documentation 4.30 / 5 Scores are an editorial guide to the directory. They are not user reviews or the results of personal testing. [See the methodology ](https://instain.ru/en/methodology/) Keep exploring ## For similar tasks [Full category ](https://instain.ru/en/category/productivity/) Work and study ### [Parseur](https://instain.ru/en/ai/parseur/) Extracting structured data from emails and files 4.38 / 5 service Free access confirmed Assistants ### [Manus](https://instain.ru/en/ai/manus/) An AI agent for research, files, and multi-step work in a browser and task environment 4.43 / 5 service Free access confirmed