Answer the hard questions. AI handles the quick ones.
Report narratives, SQL drafts and stakeholder updates handled, so analysis time goes to actual analysis.
Where the hours actually go.
Quick questions are never quick
Every stakeholder has one small ask that takes forty minutes of SQL and a chart. Ten of those is your whole week.
The same report, every month
Pulling, cleaning, charting and narrating the monthly deck is days of repeated work you could do in your sleep.
Cleaning is the actual job
Eighty percent of every analysis is fixing formats, joining sources and handling nulls before a single insight appears.
Explaining numbers to non-data people
Every finding needs a narrative a sales director can act on, written carefully, rewritten when they misread it.
Your toolkit inside kiap.ai
Live today inside the super app, or being built on the same API. Everything AI drafts, you approve.
SQL draft assistant
Describe the question, get a draft query in your schema's conventions. You check the joins and run it yourself.
Report narrative writer
Turns your charts into plain-English findings and recommendations for the monthly deck.
Self-serve metrics portal
Stakeholders pull routine numbers from a curated dashboard instead of queueing at your desk.
Scheduled report sends
Weekly and monthly reports reach the right lists automatically, with your commentary attached.
Data dictionary drafts
In the worksGenerates field definitions and metric documentation from your warehouse tables, ending the what-does-this-column-mean messages.
Request intake board
Stakeholders file analysis requests with context and priority instead of drive-by Slack messages.
A day with AI doing the busywork.
The routine what-were-sales questions already answered by the self-serve dashboard overnight.
A real analysis request: draft the SQL with AI, fix the join logic, run it. Findings by lunch.
Monthly deck narrative drafted from your charts. You rewrite the punchline, not the paragraphs.
The intake board has two new asks with proper context. No archaeology through Slack required.
Questions data analysts actually ask.
Will AI replace data analysts?
No. Framing the right question, knowing which number matters and catching the wrong join stay human. AI drafts queries and prose; the judgement about what the data means is yours.
Does it connect to our warehouse?
The drafting layer works from your schema definitions and the analytics dashboards work from exported data. Your warehouse setup stays untouched.
Can non-technical stakeholders really self-serve?
Yes, for routine metrics. Curated dashboards with fixed definitions and plain labels cover the repeat questions, while anything new still comes to you through the intake board.
Is our data PDPA-safe on this?
The platform is built with PDPA-aligned controls. You work with aggregated views and choose what data enters your workspace.
Is this for solo analysts at SMEs?
Very much so. When you are the entire data function, deflecting routine questions and automating the reporting layer is the only way to do real analysis.
Keep the craft. Drop the admin.
See your toolkit running inside kiap.ai. One call, a real walkthrough, no pressure.