Chat With Your DataSolutions
Give managers a chat box that answers questions from your real business data, shows its working, and refuses when it cannot be sure.
Chat With Your Data Solutions: what the work involves
A manager wants to know which branch slipped last week, and the honest route is a message to the analyst, who is busy, and an answer tomorrow. Dashboards cover the questions someone anticipated; every other question becomes a ticket. Meanwhile staff export CSVs and make their own conclusions, and the company ends up with several versions of the truth.
DevKey builds a conversational layer over a curated slice of your data. We first agree a governed set of tables and metric definitions. The assistant translates a question into a query against that layer, runs it with read-only access, and replies with a table, a chart and a short explanation that lists the filters used. Follow-up questions keep context. Questions outside the governed scope get a clear refusal instead of a confident improvisation, and every exchange is logged for review.
Core features
Governed semantic layer
Metrics such as net sales or active customer are defined once, so the assistant and your dashboards give the same answer to the same question.
Answers with visible logic
Each reply states the date range, filters and tables used, and offers the underlying query for anyone who wants to verify it.
Charts on request
Results can be turned into a bar, line or table view, and exported to a sheet or pinned to a shared board.
Conversation memory
Follow-ups like and for Lahore only reuse the previous context, so exploring a topic feels like talking to an analyst.
Role-based access
Each person sees only the branches, customers or salary fields their role permits, enforced in the database and not just in the prompt.
Question log and feedback
Thumbs-up and corrections are stored, and recurring unanswered questions become a backlog of metrics worth adding.
What we get right before launch
Plausible but wrong answers
A model can pick the wrong table or misread a term and still sound certain. We test with a bank of real questions that have known answers, and constrain the assistant to governed views.
Security of generated queries
Generated queries are executed with read-only credentials, row limits, timeouts and allow-listed tables, so a clever prompt cannot reach payroll or modify records.
Language and vocabulary
Staff ask in English, Urdu or Roman Urdu and use local shorthand for products and branches. We add a glossary of those terms and measure how often each language variant gets a correct answer.
Tools and technology
- OpenAI GPT
- Anthropic Claude
- Python
- FastAPI
- PostgreSQL
- LangChain
- dbt
- Metabase
- Next.js
Common questions, answered
Can it work with our existing database?
Usually yes, through a read replica or a prepared reporting schema. We avoid pointing a model at raw production tables, and instead expose cleaned, documented views that the assistant can query safely.
How do we know the answers are correct?
We build a test set of questions with answers your analysts verified, run it after every change, and log real usage afterwards. Each reply also shows its logic so users can spot a mismatch themselves.
Can it answer from PDFs and documents too?
It can combine structured data with document search, though they use different techniques. We usually start with tables, which are easier to verify, and add document sources once the first stage proves reliable.
Is our data sent to an AI vendor?
Only the question, schema descriptions and result snippets need to reach a hosted model, and we can mask columns. For stricter needs, an open model can run on your own infrastructure.
More AI Agents & Automation services
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Embed a text-to-SQL component that understands your schema, writes read-only queries, and is tested against the questions your users actually ask.
AI Semantic Search Development
Replace keyword-only search with retrieval that finds what people mean, tuned and measured on your own content and your own users.
Automated Report Generation
Have weekly and monthly reports assemble themselves from live data, complete with charts and a plain-language summary ready for a quick review.
Ready to start your Chat With Your Data Solutions project?
Tell us what you need and we will come back with a clear scope, timeline and the questions worth answering before any build starts.