OCR.space

Turn images and PDFs into readable text through AI chat instantly

A customer sends a photo of a receipt, and your AI agent extracts every line of text using OCR.space's recognition engine. Scanned documents, screenshots, and camera photos become searchable data within the conversation. No file uploads to separate portals, no waiting for manual processing.

Chosen by 800+ global brands across industries

Text extraction that lives in the conversation

From receipt photos to multi-page PDFs, your AI agent processes images through OCR.space and returns structured text, searchable documents, and table data right inside the chat.

Extract Text from Images

A user shares a screenshot or photo in the chat. The agent sends it to OCR.space via URL or base64 encoding, receives the extracted text in JSON format, and presents the readable content directly in the conversation window.

Process PDF Documents

Someone uploads a multi-page scanned PDF. The agent submits the file to OCR.space, which processes each page and returns the full text content. Multi-page document extraction happens automatically without the user needing to split pages manually.

Generate Searchable PDFs

A compliance team needs searchable versions of scanned contracts. The agent enables the searchable PDF option in OCR.space, processing the original scan and returning a PDF with an invisible text layer. The document becomes searchable and indexable.

Recognize Table Data

A user sends a photo of a spreadsheet printout. The agent activates OCR.space's table recognition mode, which preserves the tabular structure during extraction. Rows and columns are maintained so the extracted data can be used for further analysis.

Multi-Language Text Recognition

A customer submits a document in Spanish or Japanese. The agent specifies the appropriate language code in the OCR.space request, and the recognition engine processes the document with language-specific models for accurate text extraction across 24+ supported languages.

Detect Text Orientation

A user uploads a rotated or skewed scan. The agent enables orientation detection in OCR.space, which automatically identifies the text angle and corrects for rotation before extracting content. Misaligned documents get processed accurately without manual rotation.

OCR.space

Use Cases

Document recognition in real time

See how businesses use AI agents to extract text from customer-submitted photos, receipts, and scanned files during conversations, eliminating manual data entry entirely.

Receipt Processing for Expense Claims

An employee photographs a lunch receipt and sends it to the AI agent via WhatsApp. The agent processes the image through OCR.space, extracts the restaurant name, date, items, and total amount, then presents the structured data for the expense report. The employee submits their claim in a single chat without typing a single number manually.

Instant Document Search from Scanned Archives

A legal assistant needs to find a specific clause in a stack of scanned contracts. They upload each PDF through the AI agent, which runs OCR.space with the searchable PDF option enabled. The agent returns searchable PDFs where the assistant can use Ctrl+F to locate the exact language. Hours of manual reading compressed into minutes of automated processing.

Multilingual Form Processing for Global Support

A multinational company receives customer forms in multiple languages. A French customer submits a scanned application form through chat. The AI agent sets the OCR.space language to French, extracts all text fields accurately, and presents the form data in the conversation. Support agents in any country can review the content without language barriers.

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OCR.space

FAQs

Frequently Asked Questions

How does the AI agent extract text from images sent during a conversation?

The agent sends the image to OCR.space's Parse Image endpoint as a URL, base64-encoded data, or file upload. OCR.space processes the image and returns a JSON response containing the extracted text, word positions, and confidence data. The agent presents the clean text to the user immediately.

Can the agent handle multi-page PDF documents?

Yes. OCR.space processes multi-page PDFs by extracting text from each page sequentially. The agent submits the entire PDF and receives text results for all pages in a single response. You can specify the filetype as PDF to ensure proper handling of the document format.

What is the difference between OCR Engine 1 and Engine 2?

Engine 1 is the standard recognition engine optimized for most documents and images. Engine 2 is an experimental engine that may perform better on certain content types like screenshots or low-contrast text. The agent defaults to Engine 1 but can switch to Engine 2 if you specify it in your configuration.

Does Tars store the images or extracted text from OCR.space?

No. Images are sent to OCR.space for processing, and the extracted text is returned to the conversation in real time. Tars does not cache the original images, PDFs, or extraction results. OCR.space also has its own data handling policy for processed files.

How many languages does OCR.space support for text recognition?

OCR.space supports 24+ languages including English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and more. The agent specifies the appropriate language code in each request, ensuring accurate recognition for the submitted document's language.

How is this different from copying text from a digital PDF?

Digital PDFs already contain embedded text. OCR.space is for scanned documents, photos, and images where text exists only as pixels. Your AI agent handles both scenarios: for scannable images, it runs OCR processing. The user simply sends the file and gets extracted text back regardless of the source format.

Can the agent generate searchable PDFs from scanned images?

Yes. By enabling the isCreateSearchablePdf option, the agent instructs OCR.space to return a searchable PDF with an invisible text layer overlaid on the original image. Users can then search within the PDF using standard find functionality. The text layer can optionally be hidden for a clean visual appearance.

What happens if the image quality is too low for accurate text extraction?

The agent can enable the scale parameter, which tells OCR.space to upscale low-resolution images before processing. If the result quality is still poor, the agent reports the confidence level and suggests retaking the photo with better lighting or resolution. It does not return garbled text without warning.

How to add Tools to your AI Agent

Supercharge your AI Agent with Tool Integrations

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

We’ll never let you lose sleep over privacy and security concerns

At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.

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