Sold by: Synapsoft
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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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Pricing
Free trial
Try this product free according to the free trial terms set by the vendor.
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 |
Plus | 3,000 credits provided per month. 36,000 credits provided per year. | $24.00 |
Dimensions summary
This product sells through a contract with three credit-based plans: Plus, Pro, and Enterprise. You buy a plan and receive a set number of credits each month, with a larger annual allotment. Credits fund document extraction and analysis work. The plans scale by credit volume: Plus provides the fewest credits, Pro provides a middle amount, and Enterprise provides the most. You choose a plan based on how many documents you expect to process. All plans draw from the same credit pool structure, so the difference between them is the quantity of credits included per month and per year.
Top-of-mind questions for buyers
Credits fund document extraction and analysis work. The tool opens formats like word processor files, office documents, PDFs, and images, then analyzes structure such as tables, images, headings, and reading order. It converts the result into structured output like Markdown, JSON, or XML. Each plan draws from the same credit pool.
Each plan provides a set number of credits per month and a larger annual total. Once you exhaust the included credits for a period, you have reached the plan's limit. To process more documents, you would move to a plan with a higher credit volume. The data does not specify automatic overage charges.
They describe the same plan at two time scales. Each plan lists a monthly credit amount and an annual credit total. The annual figure is the larger allotment covering a full contract year, while the monthly figure reflects the per-month share. You choose a plan based on expected document volume across your billing period.
www.synapsoft.co.kr
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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
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Content disclaimer
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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.
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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