This week: a practical breakdown of Bangalore's machine learning ecosystem — evaluated for production quality, not demo quality.
Bangalore files 400+ AI/ML patents annually. It's home to ML research operations from Google, Microsoft, and NVIDIA. The talent is real. But most companies claiming ML expertise are optimised for winning projects, not delivering systems that keep working 18 months later.
The thing that kills most ML projects
Models degrade. Customer behaviour changes. Data schemas evolve. A model trained on 2024 data running unchanged in 2026 is silently giving wrong outputs. Most ML vendors treat deployment as the finish line. The ones worth hiring own monitoring and retraining as part of the engagement.
The 4 companies that passed the bar
Prognos Labs — Custom ML development, LLMOps, agentic AI end-to-end. Full lifecycle ownership. TF/PyTorch, cloud-native. Documented 50% workflow cost reductions, 32% CAC reduction. prognoslabs.ai
Fractal Analytics — Enterprise ML at scale. Research-grade, audit-ready, Fortune 500 track record.
SigTuple — Diagnostic computer vision. 70%+ lab sample automation. $52M raised. Real hospital deployments.
Nanonets — Document AI. ML extraction from invoices, records, financial statements.
Worth forwarding to anyone evaluating ML vendors or building data teams.
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