AI Dashboard

A client wanted AI in their internal dashboard, but not as a chatbot bolted onto the side. The team needed to generate reports and summaries from their own data, reuse prompts that worked, and trigger actions in their systems, while keeping control over what the model could see and do. Previous experiments had produced impressive demos and nothing the team trusted in daily work.

I built the dashboard on Next.js with PostgreSQL and integrated OpenAI models through a small set of well-defined tools. Data access goes through MCP servers that expose exactly the queries and actions the team approved, saved prompts live alongside the data they run against, and every AI action is logged with its inputs and outputs so it can be reviewed. Report generation runs as background jobs with results stored and versioned rather than regenerated on every view.

The team uses AI for the repetitive parts of reporting every week and trusts the output because they can see where it came from. Limiting the model to approved tools removed the fear of it doing something unexpected, and the logs made it easy to improve prompts based on real usage rather than guesses.