Agentic systems and LLM applications
Design and build domain workflows with reliable tool use, retrieval, orchestration, and deployment paths.
Production AI delivery
Nazmi helps teams move serious AI systems beyond the demo stage.
Hands on support for technology partners and operational teams building agentic systems, LLM applications, MLOps, production ML, search, recommender systems, and knowledge graph workflows.
Where Nazmi helps
Architecture, implementation, deployment, and handover in one senior pair of hands.
Nazmi is built for situations where AI work needs technical ownership, not another slide deck. The focus is on systems that have to run in real teams, real data environments, and real delivery constraints.
MLOps and cloud delivery
Move models and AI applications into maintainable environments with deployment, monitoring, and handover in mind.
Search, recommender systems, and knowledge graphs
Build useful data products around discovery, ranking, structured knowledge, and domain specific decision support.
Recent work patterns
The work is practical, technical, and close to delivery.
- ML and cloud workflows in a telecommunications context
- Recommender system and AI agent work in a retail technology context
- Computer vision, robotics, and production ML experience across industrial domains
- Research background in machine learning, robotics, and multi agent decision making
Founder
Nazmi is led by Isaac Kargar.
Isaac is an AI engineer and PhD candidate at Aalto University. He has more than 10 years of experience across machine learning, computer vision, robotics, recommender systems, production ML, and LLM applications.
Build what can be deployed.
Keep the architecture understandable.
Leave teams with ownership, not mystery.
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