Sold by: Unstract
LLMWhisperer converts complex documents into clean, layout-preserving text that large language models can read.
Overview
LLMWhisperer is a document parser that prepares documents for large language models.
It takes PDFs, scans, images, and just about any documents. It then returns text that preserves the layout of the source, so your LLMs receive maximum context.
It works in three parts: text extraction, document handling, and integration.
Text Extraction LLMWhisperer reads a document and returns text that preserves its original structure, ready to pass to any model.
- Preserves multi-column layouts, tables, and key-value pairs in place.
- Returns tagged, layout-preserved output rather than a flat block of text.
- Reaches 99.9% accurate raw text extraction across supported document types.
Document Handling LLMWhisperer processes documents across various formats, with no manual pre-processing.
- Reads scans, image PDFs, rotated pages, and handwriting as they come.
- Extracts across 300+ languages, including non-Latin scripts.
Integration LLMWhisperer runs as a REST API you call directly, built to drop into existing deployments or pipelines.
- Extracts in synchronous or asynchronous mode, with Webhooks that signal when a job finishes.
- Ships with Python and Node.js clients to shorten integration.
- Processes pages in parallel to reduce manual work and save time.
Common use cases
- Document pre-processing
- Feeding scanned and image PDFs into LLM workflows
- Converting handwritten forms into machine-readable text
- Preparing invoices, contracts, and statements for downstream extraction
- Building searchable text from scanned archives
- Multilingual document processing across regions
Highlights
- Layout-preserving mode: keeps multi-column text, tables, and forms in their original structure, so models read a document the way a person would.
- 300+ language coverage: extracts mixed-language and non-Latin documents, including Arabic, Chinese, Japanese, and Hindi.
- Highlight API: returns the location of every extracted line in the source document, so you can highlight where a value came from during human review.
Details
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Delivery method
Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
300k pages | $36,000 per year to process 300,000 pages per year. | $36,000.00 |
Dimension | Cost/unit |
|---|---|
Overage @ $0.05 per page. | $0.05 |
Vendor refund policy
This is a contract with usage-based pricing. Once the usage credits included in the contract are exhausted, you will be billed based on your actual usage.
Legal
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
If you need assistance or encounter any issues during use, please contact us at support@unstract.com .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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LLMWhisperer converts complex documents into clean, layout-preserving text that large language models can read.
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