Rochon
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About Rochon

Rochon is an independent AI research and engineering laboratory. We investigate, evaluate, and build intelligent systems for organizations where control, data privacy, and physical hardware constraints matter.

The lab exists because most AI advice is vendor advice. We hold no reseller agreements, take no referral fees, and ship no software we have not physically measured. Clients keep the weights, the code, and the direct invoices from their own compute providers.

Two connected missions

01 · Applied engineering

Custom systems in production

We build and deploy private AI systems: air-gapped inference inside your racks, domain-specific small language models, deterministic agent workflows, and low-power embedded computer vision. Client work creates practical value and exposes real edge cases.

02 · Independent research

First-principles investigation

We investigate how neural systems behave under physical constraints: where they hallucinate, how tokenizers can be adapted for industrial vocabularies, and how quantization affects execution. Over time, we publish open papers, benchmarks, datasets, and tools.

Client engineering exposes hard problems. Independent research builds the technical depth to solve them. Each informs the other.

Founder-Led Engineering

Mehdi Namdar

Founder & AI Systems Engineer

Electronics & Instrumentation Engineering, Nirma University

Mehdi is an AI systems engineer with a background in Electronics & Instrumentation Engineering at Nirma University. His work focuses on the full deployment arc: from tokenizer design, dataset curation, and quantized parameter tuning to hardware-level execution on bare-metal accelerators and low-power embedded silicon.

Technical background & selected prototypes
  • TARANG: Edge AI cardiac-monitoring system recognized as a Global Top 10 finalist in the Silicon Labs IoT Challenge.
  • ComplianceAI: Air-gapped local LLM retrieval and document-analysis pipeline operating with zero outbound API telemetry.
  • StoryHack: Multi-agent orchestration pipeline coordinating 13 specialized agents across manuscript extraction, narration, and execution.
  • Robotics & Perception: Computer vision and sensor integration engineering with Team Dyaus.

research.status

Read Lab Notes →

One paper on tokenizer efficiency for industrial vocabularies is currently under review. Preprints, reproducible code, and evaluation datasets are released openly once peer review concludes.

Deploy custom AI on your terms.

Tell us about your target silicon, data residency constraints, or latency requirements. Rochon engineers will provide a clear evaluation of what is viable, with power and latency models and deployment blueprints.