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Ask Questions, Get Answers From Your Files

Toggle indexing on a Storage container or Database table. Natural language queries return results filtered by user permissions.

Data indexing

Make your data queryable by AI without ETL pipelines

Toggle indexing on Storage containers or Database tables. Documents and records become queryable through natural language with embeddings generated and maintained automatically.

Capabilities

Everything you need for data indexing

Container indexing

Enable indexing on Storage containers. PDFs, documents, and text files parse and embed automatically for AI queries.

Database indexing

Index Database tables and specific columns. Query structured data through natural language without SQL.

Automatic sync

Indexes update when files change or records update. No manual re-indexing or stale data.

Permission-aware retrieval

Query results respect Storage and Database access controls. Users only see content they have permission to access.

Natural language queries

Ask questions in plain English. Context retrieves relevant documents and records to answer questions.

Source attribution

Responses include source documents and records. Verify answers by checking the original content.

0
ETL pipelines

No data movement required

< 30s
Index time

New content queryable

100%
Permission sync

Access controls enforced

Why it matters

Make your data queryable by AI

Queryable data without embeddings infrastructure

Building RAG systems requires embedding generation, vector storage, and retrieval logic. Conjoin AI Context handles embeddings and retrieval automatically when you enable indexing.
In practice

Enable indexing on a Storage container with 10,000 documents. Within minutes, users can ask questions about document content. No embedding pipelines, no vector database configuration, no retrieval code.

AI that respects your security model

Vector databases return matching content regardless of who is asking. Conjoin AI Context filters results based on the requesting user's access to source documents.
In practice

An employee asks about salary information. Context returns results only from documents they can access. Their manager asks the same question and sees broader data. Same query, different results based on permissions.

Always-current indexes

Indexes become stale as content changes. Conjoin AI Context updates embeddings when files are modified or records change, keeping query results current.
In practice

A policy document updates with new procedures. The index refreshes within minutes. Queries about that policy return the updated information without manual re-indexing.

Built for Your Workflow

Ship faster with solutions designed for real-world needs

How Conjoin solves this

Enable indexing on a Storage container or Database table. Conjoin parses documents, generates embeddings, and maintains indexes as files change, making content queryable through natural language.

Impact

Make thousands of documents AI-queryable in minutes without embedding pipelines.

How Conjoin solves this

Pass user identity with every query. Conjoin filters results based on the user's access to source documents and records, enforcing your existing Storage and Database permissions.

Impact

Deploy AI features knowing your security model extends to AI queries.

How Conjoin solves this

Automatic sync updates embeddings when files are modified or records change. Query results reflect the current state of your data without manual re-indexing.

Impact

Keep AI answers accurate as content evolves without monitoring index freshness.

How Conjoin solves this

Index Database tables and query them with natural language. Conjoin translates questions into appropriate queries and returns results with the data that answered the question.

Impact

Let non-technical users query databases without learning SQL.

Ship your application today

Start building with Conjoin today. Free tier includes everything you need to prototype and launch. Scale when you're ready.