Organisations across Malaysia share their experience of applying AI with Elden — in their own words.
Back to HomeA selection of feedback from clients who have completed engagements with our team.
"We had a backlog of claims that the team simply could not keep pace with. Elden built a processing system that handles the intake and sorting stages, which freed our reviewers to focus on the cases that actually need judgement. The ten-week timeline was realistic and they kept us informed throughout."
"We were sitting on thousands of reader comments and had no structured way to make sense of them. The topic modelling engagement gave us a reliable way to track emerging themes week by week. The labelling work Elden did on the topics was thorough — we could use the output directly without extra interpretation."
"We engaged Elden for the opportunity mapping service before we committed to any larger AI investment. In three weeks, the team produced a clear picture of where AI would be most practical for us. The scoring against effort and impact helped us make a case to the board. It was a measured, well-organised process."
"The claims processing system Elden delivered handles confidence scoring in a way our internal team had been trying to design for over a year. What stood out was how well they integrated the human review workflow — it wasn't purely automated, it was designed to work alongside people, which made adoption much smoother."
"We use topic modelling to monitor policy discourse across a large corpus of public documents. Elden's team handled the preprocessing and temporal tracking carefully, and the topic labels they produced were meaningful rather than generic. The six-week engagement was well-paced and the handover documentation was thorough."
"I was unsure whether AI would be relevant to our business at all. The opportunity mapping engagement helped us see concretely where it could reduce manual effort. The visual map Elden produced was something we could share with our whole leadership team without requiring any technical background to understand."
A closer look at three client journeys — the challenge, what we did, and what changed.
The team was processing over 2,000 claims monthly with a staff of twelve reviewers. Document intake was entirely manual, and routing errors caused average handling time to stretch beyond 14 days. Priority claims were not consistently identified early.
We built an intake pipeline for document classification and information extraction, a confidence scoring layer for initial assessment, and a routing module that directs claims to the appropriate review queue. The entire system was designed to surface uncertainty clearly so reviewers knew when to intervene.
Average handling time dropped to under 6 days for standard claims. Routing accuracy improved and reviewers reported spending more time on complex decisions rather than document sorting. The team handled a 30% volume increase without adding headcount.
"It changed how we think about the review team's role entirely." — Operations Lead
The editorial team had accumulated more than 80,000 reader comments and article annotations across three years. Identifying which topics were growing or declining in audience interest required weeks of manual reading and was prone to individual bias.
We cleaned and preprocessed the corpus, selected and fine-tuned a topic model appropriate to news discourse, labelled the output topics with the editorial team, and built a temporal tracking layer to show how topic prominence changed across weeks and months.
The editorial team gained a weekly topic summary that could be reviewed in under 30 minutes. Trend signals that previously surfaced weeks late were detected earlier, informing assignment decisions. The model runs independently with scheduled updates.
"We use it every Monday morning now." — Research Director
The CTO had a board mandate to assess AI readiness within one quarter but lacked an internal methodology. Vendor proposals were generic and did not reflect the company's specific process mix across procurement, quality control, and logistics.
We ran structured interviews across four departments, mapped their processes, and scored each potential AI application against effort to implement and likely impact. We then assembled the findings into a visual opportunity map with prioritised initiatives and a suggested sequencing for the next 12 months.
The board approved an AI investment plan within three weeks of receiving the map. The top two prioritised initiatives are now in scoping. The CTO noted the map was the clearest strategic document on AI the company had received to date.
"Three weeks of focused work saved us months of uncertainty." — CTO
We are happy to talk through your situation before any commitment. Reach out through any of the channels below or use the contact form on the homepage.
If any of these stories feel familiar, we would welcome the chance to learn about your organisation's situation and see whether we can be useful.
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