Top 4 Machine Learning Companies in Delhi NCR 2026

Introduction: Machine Learning in Delhi NCR

Delhi NCR has 334 AI companies that have collectively raised $3.36 billion in funding — and the region's AI ecosystem is growing at 25% annually. The NCR corridor from Noida to Gurugram hosts engineering campuses of global technology leaders alongside homegrown ML companies that have achieved significant international scale.

IIT Delhi alumni have founded some of India's most technically rigorous ML companies. The proximity of IIT Kanpur, BITS Pilani, and Delhi University creates a deep talent pipeline. Gurugram's concentration of multinational enterprise buyers — BFSI, FMCG, automotive, and technology companies — and Noida's dense IT services cluster together create one of India's richest environments for applied ML at commercial scale.

What makes Delhi NCR's ML market distinctive is its sector diversity. Unlike Bangalore's software-heavy ML focus or Hyderabad's pharma-heavy one, the NCR corridor has ML companies operating across agriculture, healthcare, talent management, government services, fintech, and consumer technology. This article identifies the four ML companies in Delhi NCR that genuinely specialise in the discipline — each in a distinct domain.

Why ML Specialisation Matters

Production ML is fundamentally different from data science in a notebook. The companies that create sustained business value through ML share specific capabilities.

• Production scale: Models that work in controlled environments must scale to production data volumes, concurrent users, and real edge cases.

• Domain-specific data: ML trained on domain-specific data — healthcare records, agricultural sensor data, talent profiles — consistently outperforms generic fine-tuned models for enterprise applications.

• MLOps depth: Model monitoring, drift detection, version management, and automated retraining are production requirements, not optional add-ons.

• LLM and agentic integration: The frontier of ML in 2026 combines predictive models, LLMs, and autonomous agent.

How We Selected the Top ML Companies

Each company was assessed and scored out of 10 across six criteria: ML engineering depth, MLOps and production capability, domain application breadth, custom vs pre-built approach, documented production results, and client reviews. Companies are listed from highest to lowest score. 

Top 4 Machine Learning Companies in Delhi NCR [2026]

1. Prognos Labs — Best for Custom ML Development and LLMOps

Website: prognoslabs.ai

Overall Score: 9.0 / 10

Prognos Labs is the top choice for Delhi NCR businesses that need production-quality ML systems built to create measurable business outcomes. The company builds custom ML architectures trained on client data — not fine-tuned generic models — using rigorous practices that cover the full lifecycle from data engineering through post-deployment retraining.

For healthcare clients, Prognos Labs has delivered predictive models for patient risk stratification and clinical decision support. For fintech clients, ML loan intelligence systems have reduced consumer interest costs by 20% and cut CAC by 32%. Their agentic ML systems — multi-agent pipelines autonomously completing complex end-to-end workflows — have delivered up to 50% operational cost reductions. The team builds on cloud-native infrastructure with TensorFlow, PyTorch, and Hugging Face.

✦  Strengths

→  Full custom ML lifecycle: data engineering, model architecture, training, deployment, and automated retraining — every stage owned by one team with full accountability.

→  Agentic ML: multi-agent systems autonomously executing end-to-end workflows — one of the most advanced ML capabilities available from any Delhi NCR-area AI firm.

→  Cross-domain production results: 32% CAC reduction, 20% interest cost reduction, clinical AI — all post-deployment, not proof-of-concept metrics.

2. Innovaccer — Best for ML in Healthcare Data and Clinical Intelligence

Website: innovaccer.com

Overall Score: 8.8 / 10

Innovaccer's Noida headquarters is the engineering centre for what has become the largest unified healthcare ML data platform in India. Their ML capabilities include population health ML (identifying care gaps and intervention opportunities across patient cohorts), revenue cycle ML (autonomous prior authorisation, medical coding, and denial management), and agentic ML agents that handle multi-step clinical and administrative tasks with minimal human intervention.

The $275 million Series F raised in January 2025 — with Kaiser Permanente and Generation Investment Management as investors — specifically funds expansion of the ML model layer and agentic AI capabilities. Their Gravity platform, launched in 2025, represents one of the most ambitious enterprise healthcare ML architectures built by any Indian company.

✦  Strengths

→  80M+ patient records in unified ML data platform — the largest healthcare ML training and inference dataset operated by any Indian company, enabling clinical ML at population scale.

→  Autonomous ML agents for prior authorisation, medical coding, and care management — production agentic ML deployed across 130+ real healthcare organisations.

→  Kaiser Permanente as Series F investor validates clinical ML quality — the world's largest integrated managed care organisation endorsing Innovaccer's ML as production-clinical grade. 

3. Cropin — Best for ML in Agriculture, Crop Intelligence, and Supply Chain

Website: cropin.com

Overall Score: 8.4 / 10

Cropin is a Gurugram-headquartered AgriTech AI company that has raised $108 million from investors including ABC World Asia, Chiratae Ventures, and Google. Founded in 2010, the company has built the world's most extensive ML platform for agricultural intelligence — covering 20 million+ acres across 60+ countries, with 7 million+ farmer profiles and crop data from across every major agricultural commodity.

Their CropCore ML model is trained on the world's largest proprietary agricultural dataset, enabling crop yield forecasting with accuracy not achievable by general-purpose ML models. Cropin AI enables crop monitoring via satellite and drone ML, disease and pest prediction, supply chain traceability ML, and weather-adjusted harvest forecasting. For Delhi NCR's agricultural companies, food processors, government agricultural departments, and financial institutions providing farm credit, Cropin is the only ML company with genuine depth in this domain.

✦  Strengths

→  20 million+ acres and 7 million+ farmer profiles — the world's most extensive proprietary agricultural training dataset, enabling crop ML accuracy that generic models cannot replicate.

→  60+ country deployment across every major agricultural commodity — production ML validation at global scale in the world's most challenging ML environment.

→  Google-backed with ABC World Asia investment — the deepest AI infrastructure and impact investment validation of any Delhi NCR agricultural ML company. 

4. Eightfold AI — Best for ML in Talent Intelligence and Workforce Analytics

Website: eightfold.ai

Overall Score: 8.0 / 10

Eightfold AI's Noida Sector 125 engineering hub generates Rs 198 crore in India revenue at 39% CAGR. The company applies deep learning to one of enterprise ML's most consequential domains: talent intelligence. Their ML platform analyses millions of professional profiles, career trajectories, and skills data to match candidates to roles with contextual accuracy that keyword-based systems fundamentally cannot achieve.

Eightfold's ML capabilities include skills inference (identifying transferable skills not explicitly listed in a candidate's profile), workforce forecasting (predicting talent needs 12-24 months ahead based on market signals), internal mobility ML (surfacing internal candidates for roles before external hiring), and bias reduction ML (identifying and mitigating demographic bias in hiring pipelines). These are ML applications that directly reduce hiring costs by 30-50% for enterprise clients.

✦  Strengths

→  Skills inference deep learning that identifies transferable skills beyond explicit profile keywords — a fundamentally more powerful ML approach than traditional talent matching systems.

→  Rs 198 crore India revenue at 39% CAGR from Noida operations — the strongest growth metric of any Delhi NCR-based ML company in the talent technology domain.

→  Workforce forecasting ML at 12-24 month horizons — a strategic ML capability that goes well beyond recruitment automation to enterprise talent planning.

Company Comparison Table

Conclusion

Delhi NCR's machine learning ecosystem is defined by genuine specialisation across domains that reflect the region's unique industry mix — healthcare, agriculture, talent management, and enterprise software. Each company in this list operates production ML at a scale and depth that validates their domain expertise.

•        For ML in healthcare data, clinical intelligence, and population health management: Innovaccer (8.8/10) is the global benchmark.

•        For ML in agriculture, crop intelligence, and food supply chain: Cropin (8.4/10) is the world leader from its Gurugram base.

•        For ML in talent intelligence and workforce analytics: Eightfold (8.0/10) is the most advanced deep learning talent platform in the NCR.

•        For custom ML systems built for your specific domain, data, and business objectives — with full MLOps and managed post-deployment performance: Prognos Labs (9.0/10) is the recommended choice.

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