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Deploy AI That Actually Works at Scale

7+ years. 3 industries. 0 shelf-ware projects.

Most enterprise AI initiatives spend 12–18 months and significant budget building things that never reach production. Neil has spent 7 years solving exactly that problem — from healthcare ICUs to cricket stadiums to enterprise knowledge systems. If your organisation needs AI that runs in production, not on slides, start here.

Neil Dave Enterprise AI Consultant

Neil Dave

AI Solution Architect · Bangalore, India

How Neil Helps Enterprise Organisations

Your teams are drowning in documents they can't search.

Enterprise knowledge retrieval via LLM/RAG systems — semantic search over internal documents, policies, and knowledge bases that actually returns the right answer.

CricketGPT, built for a global franchise, outperformed SOTA models on inference speed, memory efficiency, and retrieval accuracy.

Manual visual inspection is slowing your operations and missing defects.

Computer vision systems that automate quality control, detect anomalies, and process images at scale — zero added headcount required.

Built thermal imaging AI for medical diagnosis and visual analytics systems for live sports — two very different domains, same production discipline.

Your AI pilot is stuck in a loop and your stakeholders are losing confidence.

AI strategy and roadmap — a structured path from pilot to production in 90 days. Includes ML team structure, build vs buy decisions, and an MLOps foundation that actually holds.

According to McKinsey, organisations deploying AI at scale report a 20–30% reduction in operational costs. The bottleneck is almost never the technology.

Selected Work

Healthcare
Early Sepsis Detection in ICUs

Sepsis kills 270,000+ patients per year in the US alone — largely because it's detected too late. Built an ML model that identifies high-risk patients from ICU sensor data in real time, enabling earlier clinical intervention.

Outcome: Production system with interpretable predictions designed to meet clinical audit requirements.

View case study →
Sports Analytics
CricketGPT — LLM for a Global Franchise

A global cricket franchise needed domain-specific search over player, team, and venue data — and existing models didn't understand cricket terminology. Built an LLM-based search system trained on domain-specific data.

Outcome: Custom LLM with 18× faster inference than SOTA baseline, deployed end-to-end with LLMOps pipeline.

View case study →

Frequently Asked Questions

Most engagements start with a 1-hour strategy call to diagnose the problem and agree on scope. From there, engagements typically run 4–12 weeks depending on complexity — ranging from advisory (weekly calls + async reviews) to hands-on delivery (embedded with your engineering team). Every engagement ends with working software and a handoff document, not a slide deck.

Advisory retainers typically start at ₹1.5L/month (or equivalent in USD) for weekly strategy calls and async support. Hands-on delivery engagements are scoped and quoted based on the problem — most fall in the ₹3L–₹10L range for a defined project. Book a call to discuss your specific situation; there's no point in guessing before understanding the scope.

You do. All custom models, pipelines, and code produced for your engagement are fully transferred to you at project close. Neil retains no rights to your data or trained models. This is clearly stated in every engagement agreement.

Engagements can be structured to work entirely within your cloud environment — no data needs to leave your infrastructure. For healthcare and financial data, Neil has worked with NDA-first, data-minimisation-by-default approaches. Specific security and compliance requirements are addressed during the scoping call.

Yes — and this is often the most valuable engagement. Starting from zero means no legacy decisions to work around. Neil can design and build the MLOps foundation, select the right tools for your team's capability level, and create a path that your engineers can maintain independently after handoff.

Book a Strategy Call

30 minutes. No sales pitch. Walk away with a clear diagnosis of your AI problem and a recommended next step.

If the calendar doesn't load, book directly here →

Or email: hello@theneildave.in