DataMind AI classifies user intent in milliseconds, routing complex queries to specialized agents. Query databases, automate tasks, and fetch documents through a single stream.

Intent Stream
Real-time classification.
Vector Fetch
Instant context retrieval.
Agent Flow
Smart query orchestration.
Watch how we classify intents and route agents in real-time. No smoke and mirrors, just pure performance.
How it works
Every message is classified, routed, and executed automatically — from question to real-world action in milliseconds.
Understanding your query
The AI router analyses your natural language query in milliseconds, identifying whether you need a database lookup, email automation, spreadsheet analysis, document retrieval, or a multi-step workflow.
Right agent, every time
Based on classified intent, your query is dispatched to the specialised agent — SQL Agent, Email Agent, CSV/Excel Agent, RAG Knowledge Agent, or Workflow Orchestrator. No manual selection needed.
Real actions, not just text
The agent takes real action — queries your live database, reads your spreadsheet, searches through uploaded documents, or sends that email. Results are computed from your actual data sources.
Answer + proof of action
You receive a natural language answer, the intent classification, the action taken, source citations, and latency — all in one structured JSON response through a single API call or the Playground.
Capabilities
Each agent is purpose-built for its domain. You never choose — the system routes automatically.
Ask questions about your database in plain English. The agent generates and executes the SQL, then returns a clean readable answer.
# Natural language → SQL executed automatically
User: "Which customers spent over $5k last month?"
SELECT customer_id, name, SUM(amount) as total
FROM orders
WHERE order_date >= '2024-11-01'
GROUP BY customer_id
HAVING total > 5000
ORDER BY total DESC;Send emails, draft messages, and automate recurring reports — all from chat or the API.
Upload Excel or CSV files. Ask analytical questions and get human-readable answers backed by the actual data.
"Which region had the highest return rate in Q3?" → West (8.4%), vs avg 5.1%
Semantic search over your uploaded documents — PDFs, text, JSON. Returns grounded answers with source citations.
Chain multiple agents together. One query can retrieve data, run SQL, summarise it, and send the result via email — planned and executed automatically.
Playground
Test your agent before shipping. Ask anything — the system shows which agent handled it, the reasoning steps it took, and the sources it cited.
Streaming SSE responses — see it think in real time
Pipeline steps shown inline — router, agent, result
Citations and confidence scores for every RAG answer
Scoped per workspace — isolate projects cleanly
Live demo — pipeline steps
What was our revenue last quarter?
For developers
Send a natural language query and get back a structured response — the intent, the action taken, and the answer. The same endpoint handles RAG, SQL, emails, and workflows. Integrate into your product in minutes.
Streaming SSE for real-time token output
Single REST endpoint — all agents behind one URL
Built-in examples in cURL, JavaScript, Python
JWT auth, workspace-scoped, production-ready
# Ask in plain English — the agent figures out the rest
curl -X POST https://api.datamind.ai/query \\
-H "Authorization: Bearer YOUR_TOKEN" \\
-d '{ "question": "Send the Q3 report to Sarah", "workspaceId": "ws_xyz" }'
# Response — action taken, not just text
{
"intent": "email_workflow",
"action": "email_sent",
"to": "sarah@company.com",
"answer": "Report sent to Sarah with Q3 summary.",
"latency_ms": 61
}Due to high infrastructure costs of Vector DBs and LLMs, this live demo is limited. If you're looking to integrate DataMind AI's intent routing into your systems, let's collaborate.