# TMLC — The Machine Learning Company

> Enterprise AI/ML consulting and products. TMLC designs, builds, and runs GenAI, LLM, and computer-vision systems that reach production — deployed on-premise or in your cloud, inside regulated environments, governed by your policies, with your data kept in your control.

TMLC ("The Machine Learning Company") works with enterprises in banking and financial services, insurance, logistics, healthcare, retail, and manufacturing. The approach is practitioner-led (the engineers who build the system talk to you directly — no account managers in between), evidence-driven, and organized around a five-stage delivery method where each stage is sealed by a hard quality gate. Track record: 15+ GenAI systems in production across 8 countries, 20+ enterprises served, selected for Stanford Seed, with custom model work led by a Kaggle Grandmaster. Typical path from first meeting to first measured value is 4–6 weeks.

## Services
- [AI Strategy & Consulting](https://www.tmlc.in/services/ai-strategy-consulting): Executive roadmaps that end in a costed build plan — use cases ranked by value, feasibility, and data readiness.
- [GenAI & Agentic AI Development](https://www.tmlc.in/services/genai-agentic-development): Custom LLMs, RAG pipelines, and multi-step agents, built for regulated environments.
- [AI Research & Model Development](https://www.tmlc.in/services/ai-research-model-development): Novel algorithms and custom models where off-the-shelf stops working — vision, forecasting, optimization, at Kaggle Grandmaster depth.
- [Productionization & Scale](https://www.tmlc.in/services/productionization-scale): Deployment, MLOps, monitoring, and retraining in your environment — from pilot to platform.
- [All services](https://www.tmlc.in/services): Overview of the four practices and how they hand off.

## Products
- [Custom & Domain LLMs](https://www.tmlc.in/products/custom-domain-llms): Language models tuned to your domain and corpus, deployed inside your infrastructure — not a call to someone else's API.
- [AI Agents](https://www.tmlc.in/products/ai-agents): Multi-step agents that run scheduling, support, and back-office operations end to end — escalating only what needs a human.
- [Computer Vision Systems](https://www.tmlc.in/products/computer-vision-systems): Detection, inspection, and automation for industrial and regulated settings — built at Kaggle Grandmaster depth.
- [AI & ML Platforms](https://www.tmlc.in/products/ai-ml-platforms): The data-to-decision foundation — pipelines, MLOps, and monitoring that turn models into systems your teams run.
- [All products](https://www.tmlc.in/products): The four packaged systems and the practices that build them.

## Method
- [The Delivery Playbook](https://www.tmlc.in/delivery-playbook): TMLC's five-stage delivery method — Discover, Prototype, Build, Deploy, Scale — each stage sealed by a quality gate with hard exit criteria. Framed on CMMI Level 5 high-maturity practices (a framing, not a certification or appraisal claim).

## Insights
- [Why most enterprise AI pilots never reach production](https://www.tmlc.in/insights/why-enterprise-ai-pilots-never-reach-production): The operating model around the system — not the model itself — is what gets a pilot to production.
- [RAG that survives audit](https://www.tmlc.in/insights/rag-that-survives-audit): Grounding answers so every claim is traceable to a source a compliance reviewer will accept.
- [Human-in-the-loop is a design decision](https://www.tmlc.in/insights/human-in-the-loop-is-a-design-decision): Where you place the human determines whether a system can ship before it is perfect — and whether anyone trusts it.
- [Compliance, automated: a custom LLM for a financial services firm](https://www.tmlc.in/insights/compliance-automated-custom-llm-financial-services): An on-premise domain model that cut risk-assessment turnaround without moving data off-site.
- [MLOps for on-premise GenAI](https://www.tmlc.in/insights/mlops-for-on-premise-genai): Monitoring, retraining, and rollback when the model must run inside your data center and stay there.
- [The build-versus-buy question for enterprise LLMs](https://www.tmlc.in/insights/build-versus-buy-enterprise-llms): When a tuned domain model earns its cost, and when an API is enough.
- [All insights](https://www.tmlc.in/insights): Field notes on building production AI in regulated enterprises.

## Company
- [About TMLC](https://www.tmlc.in/about): Practitioners who build and run production AI for regulated enterprises.
- [Industries](https://www.tmlc.in/industries): Banking & financial services, insurance, logistics & supply chain, healthcare, retail & consumer, manufacturing.
- [Security & Architecture](https://www.tmlc.in/security): How TMLC deploys inside your environment — on-premise, in-VPC, or air-gapped — so data stays in your control.
- [Careers](https://www.tmlc.in/careers): Open roles for engineers and delivery leads who want AI that reaches production.
- [Contact](https://www.tmlc.in/contact): Book a 45-minute working session or send the team a note.

## Optional
- [Resources](https://www.tmlc.in/resources): Practitioner playbooks and field guides.
- [Newsletter](https://www.tmlc.in/newsletter): TMLC perspectives — field notes from production AI, no hype.