Navaneeth K.

I am the Founder and AI Architect of an applied AI consultancy (Vantablan) where we design and deploy production grade machine learning systems that actually run in real environments. I personally lead the technical architecture and delivery, and we have over 4 years of hands on experience building computer vision and generative AI systems across sports analytics, healthcare, e commerce, and SaaS products. Our work is end to end. We take ownership from problem definition to deployment and long term stability. On the computer vision side, we build full pipelines around object detection, instance segmentation, pose estimation, and identity recognition. These systems run on live video streams and real world inputs, not research demos. I design the core model architecture and inference logic, while we optimize pipelines using PyTorch based models, YOLO style detectors, OpenCV, and modular deployment stacks focused on speed and reliability. In generative AI, we work on LLM fine tuning, controlled generation systems, and diffusion based pipelines used for automation, internal tooling, and content workflows. I stay closely involved in prompt design, evaluation logic, and model selection to ensure outputs are predictable and usable in production. We do not build demo chatbots. We build systems that plug directly into products. Beyond modeling, we own the AI infrastructure. I handle system design while we implement training pipelines, CI CD workflows, containerized deployments, and monitoring across AWS, GCP, and Azure so models ship cleanly and remain stable after launch. I also bring a strong research background with published work in deep learning and reinforcement learning, which informs our design decisions when rigor is required. Still, our priority is simple. Build systems that work, scale, and deliver measurable outcomes. Clients work with us when they need a team that can own the AI side of their product, make architectural calls, and deliver without hand holding.