Precision in Every Model We Build
kalibrena is an AI services company based in Kuala Lumpur, built around the belief that useful AI starts with careful scoping and honest assessment.
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kalibrena was founded in Kuala Lumpur by a small group of data scientists and engineers who had spent years working inside organisations that struggled to move from AI curiosity to AI implementation. The pattern was familiar — ambitious goals, unclear scope, tools chosen before problems were properly defined, and teams left unsure of what they were actually building or why.
We started kalibrena because we believed there was a better way to approach it. Not louder, not faster, but more carefully. The name reflects that intention — calibration is about precision, about getting the measurements right before you commit. In our work, that translates to a disciplined process: we assess before we build, we scope before we code, and we make sure that what we deliver can be understood and maintained by the people who will use it.
Today, kalibrena serves organisations across Malaysia in manufacturing, logistics, retail, and professional services. Our focus areas are supply chain optimization, image recognition model training, and AI project scoping — services chosen because they represent areas where applied AI can deliver tangible, measurable improvements when approached with the right rigour.
We are a small, focused team based in Damansara Heights, and that is intentional. We prefer to work closely with each client rather than scale aggressively. Every engagement gets senior attention, and every deliverable is reviewed against the success criteria we defined together at the start.
What Guides Us
Mission
To help Malaysian organisations apply artificial intelligence thoughtfully — with clear scope, transparent methods, and deliverables that make practical sense for the people who use them.
Principles
We value honesty in assessment over optimism in sales. If a project is not a good fit for AI, we will say so. If the data is not ready, we will help prepare it rather than build on a weak foundation.
Commitment
We commit to producing work that your team can maintain and build upon independently. Knowledge transfer is not an afterthought — it is part of how we define project completion.
Our Team
A deliberately small team of specialists who bring complementary perspectives to every project.
Razif Ahmad
Lead Data Scientist
Specialises in optimization modelling and operational research, with over a decade of experience in logistics and manufacturing analytics across Southeast Asia.
Siew Lin Tan
Computer Vision Engineer
Leads our image recognition practice with a background in deep learning research, previously working in quality assurance automation for semiconductor manufacturing.
Priya Krishnan
Project Director & Workshop Facilitator
Brings a structured approach to AI scoping and stakeholder alignment. Her background spans management consulting and technology implementation across ASEAN markets.
Quality Standards & Protocols
Every engagement follows a structured set of practices that we have developed and refined through years of applied AI work.
Data Security & PDPA Compliance
All client data is handled under strict confidentiality protocols aligned with Malaysia's Personal Data Protection Act. We use encrypted environments and controlled access for all project data.
Reproducible Methodology
Our modelling processes are documented step by step, so results can be reproduced, audited, and iterated upon. We version-control all code and maintain clear experiment logs.
Performance Benchmarking
Every model we deliver comes with defined accuracy benchmarks and test datasets, so you can independently verify performance and track drift over time.
Knowledge Transfer Documentation
Deliverables include comprehensive documentation written for your team's technical level — not just raw code, but explanations, usage guides, and maintenance instructions.
Iterative Review Process
We build in review checkpoints throughout every engagement, so your team has visibility into progress and can provide feedback before we move to the next phase.
Industry Best Practices
Our team follows established ML engineering practices including proper train/test splitting, cross-validation, bias assessment, and responsible AI considerations relevant to Malaysian regulations.
Applied AI Expertise in Malaysia
The artificial intelligence landscape in Malaysia is evolving rapidly, with organisations across sectors exploring how machine learning and data-driven modelling can improve their operations. At kalibrena, we focus on the applied end of this spectrum — taking well-understood techniques in optimization, computer vision, and project facilitation, and applying them carefully to specific business problems.
Our team's combined experience spans supply chain analytics, image classification, deep learning model training, and structured facilitation of technical projects. We have worked with teams that had extensive data infrastructure and teams that were just beginning to centralise their data. In both cases, the approach is the same: understand the problem clearly, assess what is feasible with available resources, and deliver something that works in the real conditions of your operation.
Kuala Lumpur's position as a regional technology hub means access to strong engineering talent and close proximity to diverse industries — from palm oil processing to electronics manufacturing, from logistics hubs to retail chains. kalibrena is embedded in this ecosystem, drawing on local knowledge while applying methods developed and validated internationally.
Whether you are a supply chain team looking for better demand-supply balancing, a quality assurance department interested in visual inspection automation, or a leadership team trying to figure out where AI fits in your roadmap, kalibrena offers a structured starting point. We approach every conversation with the understanding that thoughtful AI adoption is more productive than rushed implementation.
Interested in Working Together?
We welcome conversations with teams who are curious about what AI can do for their operations — even if you are still early in the process.
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