What analytics leaders say after working with us
Perspectives from CDOs, heads of data, and senior analysts who have gone through a Kilauan engagement.
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Teams reviewed
4.8
Average satisfaction
6
Industries in Malaysia
100%
PDPA-compliant
From the people who worked through the process
"The Workflow Review brief was the first document we could share with our compliance team that actually addressed the right questions. Not vendor claims — specific observations about our query patterns and where drafting support made sense."
Ahmad Zulkifli bin Nasir
Head of Data, Financial Services
Kuala Lumpur · April 2025
"I was sceptical about AI in our analytics workflow — we're in a regulated environment and the risk of getting data handling wrong is real. What I appreciated about the Kilauan team was that they shared that caution. The brief reflected our actual constraints, not a generic capability pitch."
Priya Lakshmanan
Chief Data Officer, Insurance
Petaling Jaya · March 2025
"The Pilot setup was straightforward. Our IT team had questions about the read-only credentials and the contained environment, and the Kilauan team answered them clearly — with documentation, not just reassurances. Training for our two analysts covered the scenarios that actually come up in our day-to-day work."
Rohana Hamid
Senior Data Analyst, Retail
Kuala Lumpur · February 2025
"We brought Kilauan in to help us make the case to our board. The Workflow Review brief gave us something concrete to point at — these specific query categories, this volume of ad-hoc interpretation requests, this kind of brief that takes a senior analyst half a day. The board understood it because it was grounded in our actual numbers."
Krishnan Venugopal
Analytics Director, Logistics
Shah Alam · January 2025
"The monthly Stewardship brief is something I actually look forward to reading. It's not a status report — it's a thoughtful reading of where our analysts' AI-assisted outputs are working well and where the drafts are introducing patterns we should watch. That's genuinely useful for governance."
Siti Norzaharah Osman
CDO, Banking Sector
Kuala Lumpur · April 2025
"I want to be honest: the Review brief told us there were two areas where AI drafting wasn't going to be useful for our team — our query patterns are too domain-specific in those categories. I appreciated that. It made the recommendation for the other areas much more credible."
Wan Ibrahim Wan Mahmood
Head of Analytics, Telecommunications
Cyberjaya · March 2025
Three engagements in detail
Financial Services · Workflow Review
Building the internal case for a structured AI drafting trial
Challenge
A mid-size financial services firm wanted to explore AI drafting tools but needed governance documentation before IT would engage. The data team had no starting point for the brief their risk committee required.
Approach
Kilauan conducted a two-session Workflow Review with the head of data and two senior analysts. We reviewed anonymised samples from their Snowflake-based query queue and their Power BI stakeholder reporting cycle.
Outcome
The brief identified three query categories suitable for AI drafting assist and two where it was not recommended. The risk committee approved a supervised Pilot within six weeks of receiving the brief.
"The brief gave us something specific to take to risk — not a vendor claim, but observations about our own work."
Retail Analytics · Drafting & Reading Pilot
A four-week supervised deployment alongside a BigQuery-based analytics team
Challenge
A retail group's analytics team was handling 60–80 ad-hoc SQL requests per week from three business units. Senior analysts were spending significant time on first-draft queries that required only moderate complexity.
Approach
We set up a read-only connection to their BigQuery environment in a contained deployment. Two analysts were trained on a draft-review workflow. The four-week supervised period included weekly check-ins and output sampling.
Outcome
By week three, analysts reported spending roughly 30% less time on first-draft queries in the supported categories. PDPA-aligned usage policy was completed and shared with the data governance committee.
Banking · Quarterly Stewardship
Ongoing governance oversight for an analytics team already using AI drafting
Challenge
A bank's analytics team had been using AI drafting tools for several months but had no structured process for auditing outputs or maintaining alignment with BNM-RMiT as their usage patterns evolved.
Approach
Monthly Stewardship engagement: output sampling, data handling audit against their classification policy, and a CDO brief each month. BNM-RMiT alignment reviewed quarterly and flagged where usage was approaching areas requiring compliance input.
Outcome
The annual governance committee summary produced at the end of the engagement year gave the committee a structured record of how AI drafting had been used and audited — enabling confident renewal of the activity for the following year.
What we bring to every engagement
PDPA 2010 Framework
Internal governance framework reviewed by external legal counsel
BNM-RMiT Awareness
Applied in financial services Stewardship engagements
Advisory Forum Member
Malaysia Data Governance Forum, contributing since 2024
Responsible AI Pledge
Signed March 2025 — operating principles published
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