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About — Deepstream AI

About Deepstream AI

Deepstream AI publishes practical, hands-on tutorials for building and deploying real-time AI systems using NVIDIA DeepStream, edge inference, model optimization, and production-ready pipelines. Our guides include code, deployment examples, and troubleshooting notes so engineers and students can ship working systems quickly.

AM

Azan Malik

Founder & maintainer — I publish step-by-step tutorials focused on realtime AI, DeepStream integration, streaming inference, model optimization, and deployment best practices. My goal is to make complex production workflows approachable for engineers and learners.

Location: 13 Benham Road, LONDON, W7 1AQ, United Kingdom

What you’ll find here

  • DeepStream tutorials: pipeline building, GStreamer plugins, and inference adapters
  • Realtime deployment guides for edge and cloud (NVIDIA Jetson, GPUs, Kubernetes)
  • Model optimization: TensorRT conversion, quantization, batching and throughput tuning
  • Monitoring, logging, and production operational tips
  • Code examples, GitHub links, and downloadable assets where available

How we work

Each tutorial follows a reproducible pattern: objective → prerequisites → step-by-step commands/code → validation & testing → troubleshooting notes. Wherever possible we include runnable examples and links to companion GitHub repositories.

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© Deepstream AI. Practical tutorials for realtime AI. Need to reach me? Use the Contact page.

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