Mustafa

Dash

A self-learning SQL data agent that grounds answers in schema, business rules and past queries.

Agno
Text-to-SQL
Slack
Railway

I designed Dash's architecture and set up how it runs in production in a team's Slack.

Repository Docs
  1. Question
    • Plain English
    • From Slack
  2. Context layers
    • Table schemas
    • Validated queries
    • Business rules
    • What it has learned
  3. Dash
    • Analyst (read-only)
    • Engineer (read-write)
  4. Answer
    • Grounded SQL
    • Result explained
Every answer feeds back into what Dash has learned, so the next question is easier.
Grounded answers, not guessed SQL.

Dash answers business questions in plain English with grounded SQL. Every answer is grounded in layered context - table schemas, validated queries, business rules and what it has learned - and it runs as an analyst/engineer pair with read-only and read-write access.

Built to run in your cloud. Any model, Postgres for data and learnings, JWT auth, Slack and an eval suite for accuracy, routing and safety.

What I built

  • The architecture: layered context, the analyst/engineer split and the learning loop.
  • The production setup for running Dash in a team’s Slack workspace.
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