RD. Contact

Expertise

Where I create leverage

Two pillars. One through-line: AI that ships, and AI you own.

I don't sell AI theatre. I help organisations move from experimentation to operating advantage — and I keep the most capable systems on-prem so the data, and the judgement, stay yours.

01 — AI integration for business

Moving AI from pilot to production across enterprises, founders, and government. The work is measured in outcomes, not demos: agentic workflows, RAG, and copilots that plug into real systems and touch real P&L.

  • Agentic workflows & orchestration — autonomous multi-step processes with human checkpoints where it matters.
  • Retrieval-augmented generation — grounded answers over your own documents and data.
  • Copilots & assistants — embedded in the tools your teams already use.
  • Productionisation — evaluation, guardrails, observability, and the boring plumbing that makes AI reliable.

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02 — Local-first & uncensored AI

Privacy-preserving, on-prem inference that escapes cloud quotas and content filters. Your models, your hardware, your rules — capable AI that doesn't phone home with your trade secrets.

  • On-prem model serving — run open-weight models on hardware you control.
  • Privacy & data sovereignty — no third-party training on your inputs, no leakage.
  • Uncensored by design — systems tuned to your domain, not to a platform's policies.
  • Cost control — no per-token cloud bills; capacity scales with your own machines.

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The capability map

The two pillars above are the headline. Underneath is the full range of work I take on — and the demand I actually see in the market right now.

I'm not a lone researcher. I'm a builder who sells and leads AI delivery, so this is what clients ask for in 2025–2026.

AI & GenAI Strategy

Roadmaps, operating models, and ROI that holds up. Most enterprises are early and unsure where the value is — I help them chart it.

LLM & Agentic AI Engineering

RAG, fine-tuning, and autonomous workflows that plug into your real systems. Agents are the next enterprise wave; I build them to be reliable, not demos.

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Applied ML & Computer Vision

Predictive models and multimodal AI for real product features — forecasting, document intelligence, visual inspection.

AI Governance & Responsible AI

Risk, compliance, and evaluation built in from day one. With AI incidents climbing and new laws landing yearly, this isn't optional.

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MLOps / LLMOps & Data Engineering

Production-grade, observable AI. Pipelines, feature stores, and monitoring so models stay up and stay honest.

AI-Augmented Software Delivery

AI-native engineering teams. I use these tools to ship faster, and help clients do the same.

Workforce AI Literacy & Enablement

Workshops and change management so your people use AI well. AI literacy is the fastest-growing skill everywhere — close the gap before your competitors do.

Local-First & Open-Weight AI

Private, no-cloud, cost-efficient inference on hardware you control. Open models have nearly caught up to closed — there's rarely a reason to send your data out.

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How engagement works

From conversation to delivery.

Most engagements start with a conversation about the outcome you need, not the technology. Once we've scoped it, the build routes to the right delivery partner in the network — iotasol for bespoke engineering, and the specialist products where they fit. You engage the thinker; the right team follows.

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Frequently asked

What does Ravijeet Dang do?

Ravijeet is an AI-first business leader who helps enterprises, founders, and governments move AI from pilot to production. He focuses on two pillars: AI integration for business, and local-first, uncensored AI that runs on your own hardware.

What is local-first AI?

Local-first AI means running open-weight models on hardware you control instead of calling a cloud API. It keeps your data on your side of the firewall, avoids per-token cloud bills, and is not subject to a platform's content filters — so the system is tuned to your domain, not someone else's policy.

Do you build AI agents for business?

Yes. Ravijeet builds agentic workflows, retrieval-augmented generation (RAG) over your own documents, and copilots embedded in your existing tools — with evaluation, guardrails, and observability so they are reliable in production.

Does Ravijeet Dang do NDIS or diagnostic report automation?

Yes. For neuroaffirming assessment practices he has built AI pipelines that turn patient documents and interview transcripts into a high-quality diagnostic report draft in about 15 minutes, down from 2–3 weeks of clinician time, with the clinician still in control of the final document.

How do I work with Ravijeet Dang?

Engagements start with a conversation about the outcome you need. The build then routes to the right delivery partner in his network — iotasol for bespoke engineering, and specialist products where they fit. Reach him via the contact page.

Do you help with AI strategy and roadmaps?

Yes. I help enterprises, founders, and government teams chart where AI actually pays off — roadmaps, operating models, and the business case, not just the technology. Most engagements start there.

Can you help my team get AI-literate?

Yes. AI literacy is the fastest-growing skill across every market I track. I run workshops and enablement so your people use AI well and safely, instead of fearing it or abusing it.

Do you build the ML infrastructure too, or just strategy?

Both. I can lead the strategy and route the build to iotasol for engineering, or stand up MLOps, data pipelines, and evaluation harnesses directly. You get the thinking and the delivery.