Client Experiences with Our AI Integration Services
Organizations share their experiences working with luminiona on AI pilots, entity extraction development, and operating model design.
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Client Testimonials
Feedback from organizations we've worked with across Malaysia
David Lim
Operations Director, Kuala Lumpur
The pilot program helped us test AI for document processing without committing to a large system. We got clear data on accuracy rates and processing time improvements, which made it straightforward to justify the next phase to our management team.
January 15, 2026
Nur Aisyah Ibrahim
IT Manager, Petaling Jaya
What I valued most was their honesty about what would and wouldn't work within our infrastructure constraints. They designed an extraction system that integrated with our existing database without requiring a complete platform change.
January 8, 2026
Tan Chen Wei
Head of Innovation, Cyberjaya
The operating model they designed gave us a framework for making decisions about AI projects. Instead of each department pursuing separate initiatives, we now have clear governance and a consistent approach to evaluating opportunities.
December 29, 2025
Siti Khairani
Process Manager, Shah Alam
They trained our team thoroughly on the extraction system they built. Six months later, we've been able to expand it to additional document types ourselves without needing to call them back. That independence was exactly what we needed.
January 22, 2026
Ravi Nair
Technical Lead, Subang Jaya
The pilot uncovered some challenges we hadn't anticipated around data quality. Rather than overselling the solution, they helped us understand what needed to be fixed first. That realistic assessment saved us from implementing something that wouldn't have worked properly.
January 5, 2026
Lee Wei Ming
Finance Director, Kuala Lumpur
Their approach to measuring success was helpful for our board reporting. We could show concrete metrics on time savings and accuracy improvements, which made it easy to demonstrate value. The transparency about what was working and what needed adjustment built confidence.
January 18, 2026
Success Stories
Detailed examples of how organizations have implemented AI with our support
Financial Services Firm - Invoice Processing Automation
Initial Challenge
Processing 800+ invoices monthly required significant manual review time. The finance team needed to verify vendor information, amounts, and approval routing for each invoice. This created bottlenecks and delayed payment processing.
Solution Approach
We designed a 10-week pilot testing AI extraction on 200 invoices across different vendor formats. The pilot measured accuracy rates, processing time reduction, and integration feasibility with their existing accounting system before expanding.
Measured Results
Pilot achieved 94% extraction accuracy and reduced average review time from 8 minutes to 2 minutes per invoice. Based on these metrics, the organization approved full implementation with projected annual savings of 420 staff hours.
"The pilot gave us confidence to proceed. We had actual data from our own invoices showing what accuracy we could expect, not vendor marketing materials." - Finance Manager
Healthcare Organization - Patient Record Digitization
Initial Challenge
Thousands of historical patient records stored in scanned documents needed to be searchable in their electronic health record system. Manual data entry would have taken years and been prone to transcription errors.
Solution Approach
We developed extraction models trained on their specific record formats to identify patient demographics, diagnosis codes, medication details, and appointment history. The system integrated directly with their EHR database to populate records automatically.
Measured Results
Processing capacity increased from 50 records per day (manual) to 600 records per day (automated). Extraction accuracy for critical fields reached 96%, with remaining items flagged for human review. Project duration reduced from estimated 4 years to 8 months.
"They trained our team to handle exceptions and refine the model as we encountered new record formats. We're not dependent on them for ongoing operations." - Digital Transformation Lead
Manufacturing Company - AI Governance Framework
Initial Challenge
Multiple departments were pursuing separate AI initiatives without coordination. This led to duplicated efforts, inconsistent vendor relationships, and difficulty measuring overall AI value. No clear accountability for AI outcomes existed.
Solution Approach
We designed an operating model defining team structure, decision rights, funding allocation, and project evaluation criteria. This included governance processes for approving new AI initiatives and measuring their success against business objectives.
Measured Results
The organization established a central AI function coordinating 6 active initiatives. Decision-making time for new projects reduced from weeks to days using the evaluation framework. Overall AI spending visibility increased, enabling better resource allocation.
"The framework gave us structure without slowing things down. Teams still have autonomy but within clear guidelines that prevent wasteful duplication." - Chief Technology Officer
Client Satisfaction Metrics
Quantitative indicators of service quality and client outcomes
Organizations served since 2023
Average client satisfaction rating (out of 5)
Pilots meeting or exceeding success criteria
Documentation transfer completion rate
Get in Touch
Contact us to discuss how we can help with your AI integration needs
Phone
+60 3-2094 6728Office
Level 15, Tower B, Menara Manulife
Damansara Heights, Kuala Lumpur
Typical response time: Within 1 business day