QC team experience

Client Experiences

What QC Engineers and Quality Managers Say

Feedback from QC teams across Penang, Kedah, and the Klang Valley who have worked with Iras Lab on AI reading integration in their quality workflows.

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38+

Engagements completed

4.7

Average satisfaction score

5 yrs

In QC AI integration work

100%

Quarterly Stewardship renewal rate (Y1)

Feedback

From the QC Teams Themselves

FA

Faridah Azizul

QC Manager · Food Processing, Bayan Lepas

"We came in with a lot of scepticism — we'd had two vendors pitch us AI tools that were clearly built for software teams, not for people managing CAPA logs. Iras Lab read our actual records before recommending anything. The brief they delivered was the first document we'd received from any AI advisory that used the right language for our ISO 9001 setup."

April 2025 · Workflow Reading Review

KW

Kelvin Wong

Head of Quality · Medical Devices, Shah Alam

"The Drafting Pilot was more contained than I expected, which I mean as a compliment. The six-week supervised period gave my senior inspector time to build confidence with the AI outputs before I was comfortable stepping back. The usage policy Iras Lab wrote is now sitting in our management review file and has already been referenced in a customer audit. That document alone was worth the engagement."

March 2025 · Inspection Reading & Drafting Pilot

NI

Norzaini Ibrahim

QC Supervisor · Halal Food Mfg, Alor Setar

"My main concern was whether the AI integration would conflict with our JAKIM Halal certification requirements. Iras Lab addressed that directly — the brief specifically noted which record-handling recommendations were Halal Manual-compatible and which we should set aside. I hadn't seen that level of specificity from any other advisory."

April 2025 · Workflow Reading Review

ST

Suresh Thangarajah

Quality Engineer · Precision Components, Penang

"The Quarterly Stewardship is the part I didn't know we needed. We thought once the Pilot was done, we'd be fine managing it ourselves. Having Iras Lab sample outputs quarterly and flag boundary drift before it became a problem has caught two instances where the AI was summarising in ways that didn't match our NCR format. Small things, but they matter in audit context."

January 2025 · Quarterly Stewardship

LH

Lim Hui Shan

QC Manager · Pharmaceutical, Petaling Jaya

"I appreciated that the Reading Review brief was honest about where AI wasn't going to help. Two of the record types we wanted to automate turned out to have too much ambiguity in the language our inspectors use — Iras Lab flagged that clearly rather than trying to make it work anyway. That kind of candour is unusual."

March 2025 · Workflow Reading Review

MA

Muhd Amirul Hafiz

Head of QA · Consumer Goods, Subang Jaya

"We renewed the Quarterly Stewardship for a second year without hesitation. The quarterly brief goes directly into our management review pack. Our head of operations reads it — it's written for him, not for our IT team. That distinction matters more than any technical capability."

February 2025 · Quarterly Stewardship

Case Studies

How Engagements Played Out in Practice

Case 01 Food Manufacturing, Penang · Workflow Reading Review → Drafting Pilot

Challenge

A Bayan Lepas food facility was spending an average of 3.5 hours per week per inspector on CAPA memo drafting from handwritten inspection records. The QC manager was concerned that AI tools would create documentation gaps the facility couldn't defend in a JAKIM audit.

Our Approach

Reading Review identified three record types where AI summarisation was low-risk and two where it was not suitable due to language variation in inspection notes. The Pilot was scoped to the three suitable types only. JAKIM compatibility was confirmed in writing before deployment.

Outcome

Inspector CAPA memo time reduced by approximately 40% for the three record types in scope. Zero audit findings attributable to AI outputs in the six months following the Pilot. The facility is now in the second year of Quarterly Stewardship.

"The fact that the brief told us where not to use AI was actually the most valuable part. We went into the Pilot knowing exactly what the boundaries were." — QC Manager
Case 02 Precision Components, Penang · Drafting Pilot

Challenge

A precision components manufacturer in Bayan Lepas had a backlog of non-conformance reports from a high-volume quarter. Two inspectors were spending significant time summarising batch records before they could begin CAPA analysis. The LIMS data was well-structured but hadn't been configured for any AI access.

Our Approach

Pilot configured a read-only connection to the LIMS batch records. AI was set to produce batch summary drafts and first-pass NCR consolidations across runs. Inspector training focused on recognising when AI summaries were oversimplifying defect patterns in related batches.

Outcome

NCR backlog was cleared within the six-week supervised period. Both inspectors reported being more confident evaluating AI outputs critically by week four. The scope boundary document has been referenced in two customer audit conversations.

"Training our inspectors to question the AI output, not just use it, was something we hadn't thought about before the Pilot. That skill turned out to be as valuable as the tool itself." — Quality Engineer
Case 03 Consumer Goods, Selangor · Quarterly Stewardship (ongoing)

Challenge

A Subang Jaya facility had completed an AI Pilot with a different provider eighteen months prior. The tool was in use, but the QC team had no documentation of scope boundaries, no usage policy, and growing uncertainty about whether AI summaries were being used in ways that would hold up to customer audit scrutiny.

Our Approach

Iras Lab began with a retrospective boundary assessment — reviewing how the AI tool had actually been used versus what it was originally deployed to do. This formed the basis of a usage policy written from current practice rather than original intent. Quarterly Stewardship commenced on this foundation.

Outcome

Two quarterly briefs later, the facility had a documented AI governance trail covering 18 months of prior use and current practice. A customer audit question about AI in QC processes was answered with reference to the Iras Lab quarterly reports. The engagement has been renewed.

"We didn't realise how exposed we were until Iras Lab mapped what we were actually doing with the tool against what we thought we were doing. The retrospective was uncomfortable but necessary." — Head of QA

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