Built for analytics teams who take their work seriously
We are a Kuala Lumpur advisory practice. Our work sits at the edge where AI capability meets the careful, governed world of enterprise data analytics.
← Back to HomeHow Kilauan came about
"The problem was never that analysts couldn't use AI. The problem was that no one had written down how to do it carefully."
Kilauan was founded in Kuala Lumpur by practitioners who had spent years inside data and analytics teams — the kind of teams where a misdrafted stakeholder brief or a poorly constructed SQL query has real downstream consequences.
When AI drafting tools began appearing in analytics workflows, the teams we knew were cautious. Cautious rightly — their data governance frameworks, their PDPA obligations, and their BNM-RMiT responsibilities didn't pause for new technology. But cautious didn't mean closed. What they needed was someone to sit down, read their actual work, and write a sensible brief on where AI drafting could help without creating new risk.
That's what we do. We are not a software vendor. We don't have a platform to sell. We are an advisory practice with a narrow, careful focus: helping analytics teams in Malaysia work alongside AI drafting tools in a way their governance structures can stand behind.
What we are here to do
Make AI integration legible
We write plain-language briefs that your CDO, data governance committee, or risk team can actually read and act on — not vendor slide decks.
Hold governance as a first principle
PDPA alignment, read-only warehouse access, and data classification policy adherence are built into every engagement — not retrofitted at the end.
Keep analysts in the driver's seat
AI should reduce the time analysts spend on first drafts, not replace the judgement they bring. That distinction guides everything we build and recommend.
Who you'll be working with
Zainal Abidin Harun
Principal Advisor
Twelve years across analytics and data engineering roles in Malaysian financial services. Zainal leads client engagements and writes the advisory briefs.
Nurul Farhana Ismail
Data Governance Lead
Farhana has audited data governance frameworks across three sectors. She handles PDPA alignment assessments and writes the data-handling sections of every Pilot engagement.
Rajan Krishnamurthy
Integration Specialist
Rajan works on the technical setup for Pilot deployments — warehouse read connections, contained environments, and analyst training sessions on drafting workflow.
Standards we hold ourselves to
Advisory work is only as useful as the trust behind it. These are the operational standards that underpin every Kilauan engagement.
PDPA Compliance
Every engagement is structured to comply with Malaysia's Personal Data Protection Act 2010. Data handling procedures are documented and shared with clients.
No Data Retention
Client data samples used in Workflow Reviews are anonymised before handling and are not retained. Pilot environments do not persist data between analyst sessions.
Read-Only Warehouse Access
AI drafting environments connect to your warehouse through read-only credentials. We define the access scope with your data infrastructure team before deployment.
Written Briefs, Not Slide Decks
Every engagement produces a written brief you can share with your governance committee or CDO. We write plainly, cite our observations, and flag where uncertainty remains.
BNM-RMiT Awareness
For financial services clients, our Stewardship briefs consider BNM's Risk Management in Technology framework and flag items that may require compliance review.
Advisory Independence
We don't sell software or receive referral fees from AI tool vendors. Our recommendations reflect what we observe in your workflows — not what benefits a platform relationship.
Analytics teams and AI drafting: a measured reading
The discussion around AI in analytics workflows often skips the part where your governance team has to say yes. Kilauan's work begins there — with the actual constraints that data analytics teams in Malaysia operate under, from Personal Data Protection Act obligations to internal data classification policies to, for some clients, BNM-RMiT considerations.
SQL drafting support has a genuine use case in analytics teams managing high volumes of ad-hoc requests. An analyst who can review a well-structured draft query rather than write from an empty editor works faster and catches edge cases more reliably. The AI drafts; the analyst edits. That distinction matters for quality, for governance, and for accountability.
Dashboard interpretation is more nuanced. A senior analyst reading a Power BI or Looker dashboard does more than describe numbers — they apply domain knowledge, question data freshness, and frame findings for specific audiences. AI drafting can produce a starting-point summary; the analyst applies the context that makes it accurate and useful.
Stakeholder brief-drafting is where AI assistance often saves the most time in practice. The structure of a brief — what the data shows, what it might mean, what questions remain — is amenable to a careful first draft from an AI that has read the dashboard context. Senior analysts then apply their knowledge of the organisation, the audience, and the decision at hand.
Kilauan operates across the BigQuery, Snowflake, Power BI, and Looker ecosystems — not because these are the only tools, but because they are where most of our Malaysian enterprise clients work. We integrate alongside your existing stack rather than asking your team to learn a new interface.
Ready to have a careful conversation about AI in your analytics workflow?
We start with a Workflow Review — a short engagement that reads your actual work and produces a written brief. No obligation to go further.
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