Sold by: Synapsoft
Turn PDF, Office (DOCX/PPTX/XLSX), HWP, and image files into AI-ready JSON, XML, or Markdown. Cut LLM token costs and skip months of building your own document extraction pipeline.
Overview
AI Data Foundry
Feeding raw files to an LLM means paying for the same tokens on every question, and generic models flatten the tables, charts, and layout that carry the meaning. AI Data Foundry converts your documents once into clean, structure-preserving data that your applications and models can reuse: 0.146 seconds per page, 99.3% certified OCR accuracy (TTA), 14+ input formats in, and JSON / XML / Markdown out.
Business users work in a point-and-click web console, developers call the REST API, and AI agents connect over MCP. However a job runs, you can inspect and review it on the web.
Key Features
Any format in, one consistent structure out
- 14+ input formats including PDF, MS-Office (DOCX, PPTX, XLSX), Hangul (HWP), images, ODT, and TXT
- PowerPoint and Excel handled natively, with no separate extractor to build per format
- Output as JSON, XML, or Markdown: JSON and XML for enterprise data pipelines and databases, Markdown for LLM and RAG ingestion
Document structure preserved, not flattened
- Recognizes headings, paragraphs, headers, footers, page numbers, captions, and lists
- Extracts tables, charts, images, and formulas with reading order intact
- Preserves document hierarchy and the relationships between elements, so answers stay consistent from run to run
No-code automation pipeline
- Chain analysis, classification, transformation, review, and delivery with clicks; new documents re-run the flow automatically
- Ingest from Amazon S3, Google Drive, email (IMAP), the API, or direct upload
- Sensitive data masking and LLM post-processing available as pipeline steps
Human-in-the-loop review for documents that must be right
- Refine structure and tags, then have owners give critical documents a final review in the browser
- Assign reviewers by member or group; review history compounds into quality data tuned to your organization
Built for AI agents
- Connect over MCP and any MCP-enabled assistant can convert and analyze documents mid-conversation, like a native tool
Use Cases
- Conversational AI (RAG): ground Q&A systems in documents that include tables and images, with far fewer tokens per query
- LLM model training: build training and fine-tuning datasets from the documents your organization already owns
- Business automation (RPA): extract only the fields you need from complex forms and route them downstream
- Digital archive: structure legacy and unstructured documents into a large-scale, searchable, citable corpus
Why AI Data Foundry
Building this capability in-house typically means 3 to 12 months of development and a team of 2 to 5 AI engineers, a separate extractor for every file format, and a quality process you maintain forever. With AI Data Foundry, one business user is productive on day one, with native Office support, built-in web review, and API, webhook, and MCP extensibility included.
Getting Started
- Subscribe and get your API key. It is issued the moment you sign up, along with 300 welcome credits.
- Send your first document: curl -X POST https://synapfoundry.ai/api/v1/parse -H "Authorization: Bearer {YOUR_KEY}" -F "file=@sample.pdf"
- Automate it. Build a no-code workflow in the web console, or add the MCP server at https://synapfoundry.ai/mcp to your AI assistant.
Try it with your own documents at https://synapfoundry.ai , or read the full guide at https://synapfoundry.ai/apiReference/intro .
Highlights
- 14+ formats in, JSON / XML / Markdown out. PDF, Word, PowerPoint, Excel, Hangul (HWP), and images are handled natively, with tables, formulas, headings, and reading order preserved instead of flattened, so your LLM and RAG pipelines get consistent structured input every time.
- 0.146 seconds per page and 99.3% certified OCR accuracy (TTA), plus built-in human-in-the-loop review in the browser for documents that have to be right. Reviewers can be assigned by member or group, and review history compounds into quality data tuned to your organization.
- Use it the way you already work: web console, REST API, or MCP, with ingestion from Amazon S3, Google Drive, and email. Chain analysis, classification, transformation, review, and delivery into no-code workflows that re-run automatically, instead of spending 3 to 12 months and 2 to 5 AI engineers building your own pipeline.
Details
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Deployed on AWS
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Features and programs
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Pro | 12,000 credits provided per month. 135,000 credits provided per year. | $72.00 |
Enterprise | 50,000 credits provided per month. 560,000 credits provided per year. | $215.00 |
Dimensions summary
This listing sells document extraction and analysis through a contract with two plans: Pro and Enterprise. You buy access based on credits, which the product consumes as it analyzes documents. Both plans grant a monthly credit allowance and an annual credit allowance. Pro provides a lower credit volume, while Enterprise provides a higher credit volume for heavier processing needs. You choose the plan that matches your expected document volume. The plans differ by the amount of credits included, so pricing scales with how many documents you process during the term.
Top-of-mind questions for buyers
The listing defines your allowance in credits, which the tool consumes as it analyzes documents and extracts structure. The exact number of credits per document depends on document type, size, and whether image analysis is involved. For a precise credit-per-document rate, contact the vendor.
Each plan lists both a monthly credit amount and an annual credit amount. The monthly figure reflects credits available each month. The annual figure reflects the total credits provided across the full year term. You draw down credits as documents are processed against these allowances.
Both plans provide a fixed credit volume for the period. Once credits are consumed, further processing depends on your remaining allowance. Enterprise includes a higher credit volume than Pro for heavier processing needs. To confirm how additional credits or overages are handled, contact the vendor.
www.synapsoft.co.kr
Helpful?
Vendor refund policy
Technical and billing support for AI Data Foundry is provided by Synapsoft.
Support request form (English): https://form.synapoffice.com/r/a3aotM Support request form (Korean): https://form.synapoffice.com/r/efa_61 For refund requests, please use the same contact channels.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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.
Support
Vendor support
Technical and billing support for AI Data Foundry is provided by Synapsoft.
- Support request form (English): https://form.synapoffice.com/r/a3aotM
- Support request form (Korean): https://form.synapoffice.com/r/efa_61
For refund requests, please use the same contact channels.
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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