What Clients Say
About Working with Us
Real feedback from organizations we've partnered with on AI research, emotion recognition, and infrastructure optimization projects.
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Amirah Hassan
Research Lead, Tech Institute
Kuala Lumpur
The research partnership exceeded our expectations. The Inferix team genuinely collaborated rather than just consulting, bringing deep technical expertise while respecting our domain knowledge. The shared infrastructure approach worked brilliantly.
February 3, 2026
Rajesh Chandran
CTO, EdTech Startup
Penang
Their emotion recognition system helped us build more responsive educational software. What impressed me most was the comprehensive ethics review and culturally-aware training approach. They took privacy concerns seriously and designed appropriate safeguards.
January 28, 2026
Lily Wong
Operations Director, FinTech
Kuala Lumpur
The infrastructure audit identified cost savings we hadn't considered and provided clear implementation guidance. Within six weeks of implementing their recommendations, we reduced our AI infrastructure costs by 22%. Well worth the investment.
February 12, 2026
Imran Yusof
Product Manager, Healthcare
Johor Bahru
Working with Inferix felt like extending our team rather than hiring contractors. They explained complex concepts clearly, involved us in decision-making, and ensured we could maintain the systems independently after handoff. The knowledge transfer was exceptional.
January 19, 2026
Sarah Muthu
AI Lead, Retail Analytics
Petaling Jaya
Their honest assessment saved us from pursuing an AI solution that wouldn't have worked for our use case. Instead, they suggested a simpler approach that achieved our goals at lower cost. That kind of integrity is rare in this space.
February 7, 2026
Kumar Tanaka
Engineering Manager, Logistics
Melaka
The documentation they provided was thorough and practical. Six months after project completion, we're still referencing their architecture diagrams and deployment guides. The 90-day support window gave us confidence during the initial rollout phase.
January 31, 2026
Success Stories
Cross-Lingual NLP Research Partnership
Challenge
A research institution needed expertise in Southeast Asian language models to investigate code-switching patterns across Malay, English, Chinese, and Tamil in Malaysian contexts. Existing Western models performed poorly on multilingual text.
Solution
Six-month research partnership involving shared data collection, model architecture exploration, and extensive testing across Malaysian language patterns. Developed custom benchmarks for evaluating code-switching performance.
Results
Co-authored paper accepted at regional AI conference. New model architecture showing 34% improvement over baseline. Research findings inform ongoing product development at the institution.
"The collaborative approach meant we weren't just hiring consultants — we were gaining research partners who cared as much about the work as we did. The publication was a nice bonus, but the real value was building capacity within our team." — Research Director
Customer Experience Emotion Detection
Challenge
A customer service platform wanted to detect frustration in voice interactions to route calls appropriately. Needed culturally-aware system working across Malaysian ethnic groups while maintaining strict privacy standards.
Solution
Ten-week engagement developing multimodal emotion recognition using voice tone and speech patterns. Included extensive bias testing, privacy-preserving architecture design, and comprehensive usage guidelines with ethical constraints.
Results
System deployed with 87% accuracy across demographic groups. Call escalation reduced by 28%. Client received detailed ethics review helping inform internal AI governance policies.
"What distinguished Inferix was their insistence on addressing ethical considerations upfront. The usage guidelines they provided helped us think through scenarios we hadn't considered, ultimately making us more responsible deployers of this technology." — Product Lead
AI Infrastructure Cost Reduction
Challenge
A growing AI company faced rapidly increasing cloud costs as their model serving workload expanded. Infrastructure spending had grown 300% over six months without corresponding revenue growth.
Solution
Three-week infrastructure audit profiling their workloads, analyzing resource utilization, benchmarking costs, and identifying optimization opportunities. Provided detailed implementation roadmap with priorities.
Results
Identified RM 47,000 annual savings through better resource allocation, reserved instances, and model serving improvements. Client implemented recommendations achieving 29% cost reduction in first quarter.
"The audit paid for itself within the first month. The recommendations were specific enough that our team could implement them without constant consultation, though the 30-day support window was helpful for questions." — Engineering Director
By the Numbers
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Location
6 Jalan Laksamana
75000 Melaka, Malaysia
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