Governed agents · reliable RAG · digital twins · privacy-first creative tools
I'm Nur Amirah Mohd Kamil (Mia), an AI Systems Engineer and the Founder & CEO of MI4 Inc., based in Kuala Lumpur, Malaysia. I work where applied AI meets systems thinking: designing agent architectures, governance layers, retrieval systems, and human-centered products that are stable, explainable, and genuinely useful.
My projects move between enterprise AI reliability and public-good technology, with one constant: intelligence should be engineered as a dependable system—not added as a decorative feature.
“Code is how stardust remembers it was once a star.”
- 🪞 Building Trueframe, a private, on-device studio that makes AI imagery feel more photographic.
- 🛰️ Developing AI-OS and the AI-OS Framework for measurable deployment stability and multi-agent governance.
- 🇲🇾 Exploring AI for public access through BantuRakyat-AI and simulation-led automation for Malaysian SMEs.
| Project | Domain | What it does |
|---|---|---|
| Trueframe · Live | CREATIVE AI |
Six browser-native tools for skin repair, upscaling, film grading, prompt design, and batch processing—with no uploads |
| AI-OS | AI GOVERNANCE |
Introduces ADSI, a composite stability model for monitoring and governing production AI deployments |
| AI-OS Framework | MULTI-AGENT |
Converts operational telemetry into stability scores, risk tiers, anomaly signals, and governance decisions |
| CCAM for Malaysian SMEs | DIGITAL TWIN |
Validates automation workflows inside a deterministic simulation before they reach real operations |
| BantuRakyat-AI · Live | AI FOR GOOD |
Helps Malaysians discover government assistance programs and understand their eligibility |
| ReadyTensor RAG Assistant | RAG |
A FastAPI, LangChain, and Streamlit assistant for context-aware publication discovery |
Python · TypeScript · JavaScript · FastAPI · React · LangChain · Streamlit · Docker · GitHub Actions · Google Cloud
Multi-agent architectures · RAG pipelines · AI governance · Digital twins · Evaluation · Observability · Privacy-first applications
- Reliability is a product feature. AI systems need measurable behavior, recovery paths, and operational guardrails.
- Validate before reality pays the price. Simulation and deterministic checks belong before deployment.
- Privacy should be architectural. When a task can run locally, user data should stay local.
- Useful beats impressive. The best system solves a real problem clearly and survives contact with its users.
I'm open to conversations about dependable AI systems, agent governance, applied RAG, creative technology, and mission-driven products.
✦ Building useful intelligence from the Orion arm. ✦
📌 This profile is also a live, interactive single-page systems board — rendered from the same design language. Ask for the link.