A knowledge store for RAG-based document search and AI-assisted answers

DocStore connects enterprise documents to RAG-based search and AI answers. It provides a flow for exploring document-based knowledge and checking relevant context.

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DOCSTORE SUMMARY

A flow from documents to knowledge search

This section introduces the basic flow for organizing document-based knowledge and finding context relevant to a question.
DocStore UI
  1. Upload documents

    Upload enterprise documents used for knowledge search.

  2. Analyze and split

    Analyze documents and split them into meaningful chunks.

  3. Embed and index

    Convert chunks into embeddings and index them for retrieval.

  4. Ask a question

    Users enter questions in natural language.

  5. Retrieve and answer

    Retrieve relevant context and pass it to the answer flow.

CORE CAPABILITIES

DocStore core capabilities

Here is how you can work with the store.

Folder-level document management

Create folders inside a store to classify and manage similar documents together.

Metadata management

Define attribute information per document and use it as a filter condition when searching.

Embedding model selection

Choose and configure from a range of embedding models including OpenAI, VoyageAI and Upstage.

OpenAPI provided

Connect store creation, retrieval, update, deletion and queries through APIs to exchange data with other systems.

Evidence-based answers and source tracking

Source and version information for retrieved documents is managed together, so you can trace and verify which documents an AI answer relied on.

Permission-based search scope control

Limit the range of searchable documents and the information exposed in answers according to user permissions.

Open API based knowledge integration

Integrate with existing ECM, KMS and groupware systems to keep knowledge up to date in real time.

DocStore ADVANTAGE

Personal information inside documents is handled securely.

Automatic personal data detection

During document parsing, information that can identify an individual — such as card numbers and phone numbers — is detected automatically.

Original document masking

Masking is applied not only to extracted data but also to the original PDF document.

Masking rule management

Register and edit domain-level masking rules according to internal policy, and set whether they apply per chatbot.

CASE STUDY

DocStore adoption cases

Turn enterprise documents into searchable knowledge and apply it across a range of work situations.

What is the leave policy?- Internal policy and manual search -

Internal knowledge search

Register internal policies, work manuals and policy documents in DocStore so employees can ask in natural language and find the rule they need right away.

What are the refund conditions for this product?- Terms and FAQ based answers -

Customer service support

Register terms, FAQs and past inquiries so chatbots or agents can immediately provide accurate, document-grounded answers.

Find the company vision section in this 100-page report- Large document exploration -

Long report search

Instead of hunting through long reports or contracts, one question surfaces the relevant pages and key content immediately.

The policy changed — is the AI answering with the latest version?- Document update management -

Responding to policy changes

When a policy or manual changes, reload and re-embed the latest document so the AI always answers against the current standard.

FAQ

FAQ

DocStore is an enterprise knowledge store for RAG-based document search and AI-assisted answers.

CONTACT

Turn scattered documents into searchable knowledge

Build enterprise documents into a knowledge base for RAG search.

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