We engineer intelligent mobile and desktop experiences through rigorous AI research and native application development. Leveraging on-device inference, Core ML, and generative AI, we build production-grade applications that bring advanced machine learning directly to users across iOS, macOS, and cross-platform environments.
Innovasi Lab Sdn. Bhd. is a Malaysia-based artificial intelligence research and development company dedicated to creating intelligent software that transforms advanced AI research into practical, real-world applications. We specialise in designing, training, and deploying custom machine learning models for mobile platforms, with a strong focus on delivering high-performance, privacy-first AI experiences.
Our expertise spans applied AI research, machine learning engineering, and native iOS development. By combining these disciplines, we develop intelligent applications that leverage Apple's ecosystem, including Core ML, Vision, Natural Language, and Create ML, enabling AI to run efficiently on-device while safeguarding user privacy.
As a research-driven company, we continuously explore emerging AI technologies, foundation models, multimodal intelligence, and edge AI to develop innovative solutions for consumers and enterprises. Our goal is to bridge the gap between cutting-edge research and commercially deployable products that deliver measurable value.
To become a leading AI innovation company in Southeast Asia, empowering businesses and consumers with intelligent, privacy-centric, and accessible AI technologies that improve everyday life.
We build upon the latest advancements in artificial intelligence, drawing inspiration from leading academic research and emerging industry breakthroughs to create practical, future-ready solutions.
We believe users should benefit from AI without compromising their privacy. Whenever possible, our solutions leverage on-device intelligence to minimise data exposure while maximising performance.
From concept to deployment, we focus on building reliable, scalable, and maintainable AI systems using modern software engineering and MLOps best practices.
We embrace fast experimentation and iterative development, enabling ideas to evolve quickly into validated prototypes and production-ready solutions.
As an emerging AI company, we are committed to developing innovative products and strategic partnerships that contribute to the growing AI ecosystem in Malaysia and beyond.
Purpose-built neural network architectures designed for your specific data topology and performance requirements. We handle the full model lifecycle from data pipeline engineering through hyperparameter optimisation to inference deployment.
Accelerated proof-of-concept development to validate AI feasibility before full investment. Our systematic experimentation framework de-risks innovation through iterative hypothesis testing and performance benchmarking.
Enterprise-grade model serving infrastructure with automated retraining pipelines, drift detection, and real-time monitoring. We integrate seamlessly with your existing cloud architecture and CI/CD workflows.
C-suite advisory services for AI transformation initiatives. We conduct comprehensive AI readiness assessments, define technical roadmaps, and provide governance frameworks aligned with responsible AI principles.
Managed experimentation environments with GPU-accelerated compute, pre-configured ML frameworks, and collaborative tooling. Accelerate your team's research velocity without infrastructure overhead.
Native applications powered by on-device machine learning for iOS, macOS, and Windows. We build intelligent user experiences using platform-native frameworks — optimised for local inference with privacy-first, offline-capable AI processing.
We are building the next generation of intelligent applications for mobile and desktop platforms, leveraging on-device machine learning to deliver private, fast, and contextually aware user experiences across iOS, macOS, and Windows.
An intelligent conversational assistant for mobile and desktop that leverages on-device large language model inference for real-time, private AI interactions. Built natively for iOS, macOS, and Windows with offline-capable generative AI.
A computer vision application for document intelligence and real-world object recognition. Utilises on-device ML models for instant visual analysis without cloud dependency — available on iPhone, iPad, and Mac.
A real-time multilingual translation app optimised for Southeast Asian languages (Malay, Indonesian, Thai, Vietnamese) with on-device neural machine translation — for mobile and desktop use.
Native Swift/SwiftUI development with Core ML, Vision, and Natural Language frameworks. On-device inference optimised for Apple Neural Engine across iPhone, iPad, and Mac.
Desktop AI applications built with modern frameworks, leveraging Windows ML, ONNX Runtime, and GPU acceleration for high-performance local inference on PC and workstation environments.
Object detection, image classification, OCR, and document intelligence using hardware-accelerated vision pipelines across mobile and desktop platforms.
AI processing runs on-device wherever possible. No user data leaves the device unnecessarily. Full compliance with App Store guidelines and platform-specific privacy requirements.
Shared AI model architectures deployed across iOS, macOS, and Windows — ensuring consistent intelligent behaviour regardless of the user's device or operating system.
Comprehensive stakeholder interviews, data landscape assessment, and technical feasibility analysis. We define success metrics, identify data dependencies, and establish performance benchmarks for the engagement.
Literature review of state-of-the-art approaches, model architecture selection, and system design documentation. We evaluate trade-offs between accuracy, latency, cost, and maintainability to propose optimal solutions.
Iterative development of minimum viable models with continuous stakeholder feedback loops. We validate hypotheses through systematic experimentation, A/B testing, and quantitative performance evaluation against defined benchmarks.
Full-scale model training, hyperparameter tuning, and inference optimisation (quantisation, distillation, pruning). We engineer robust data pipelines, implement comprehensive test suites, and prepare deployment artifacts.
Zero-downtime deployment with canary releases, real-time performance monitoring, and automated drift detection. We establish retraining schedules and feedback loops to ensure sustained model efficacy in production.
Whether you're exploring AI feasibility for a specific use case or planning a comprehensive enterprise AI strategy, our team is prepared to provide expert technical guidance.
Kuala Lumpur, Malaysia