AI & Machine Learning
The legal landscape for artificial intelligence is forming in real time. Vectis Law advises companies building, deploying, and integrating AI systems on the emerging regulatory, contractual, and liability frameworks that govern this space. We understand the technical architecture of ML systems – training data pipelines, model development, inference deployment – and translate that understanding into legally sound structures. Our work covers the full AI value chain: from training data rights and model ownership to deployment liability, algorithmic transparency obligations, and the evolving global regulatory patchwork. We help clients build responsibly while moving at the speed their markets demand.
Key Services
- AI governance framework design and policy development
- Training data licensing and rights clearance
- Model ownership, IP assignment, and joint development agreements
- AI-as-a-service terms and deployment agreements
- Algorithmic transparency and explainability compliance
- AI liability and indemnification structuring
- Regulatory monitoring and compliance for AI-specific regulations
- Responsible AI policy drafting and ethical review frameworks
Regulatory Landscape
AI regulation in India is evolving rapidly, shaped by the proposed Digital India Act (AI provisions), the IT Act 2000 (intermediary and automated decision-making provisions), and India AI mission guidelines. For companies with European exposure, the EU AI Act introduces additional compliance obligations. Sector-specific AI guidance from regulators including RBI, SEBI, and IRDAI adds further layers. We help clients stay ahead of this shifting regulatory environment while building products that meet emerging compliance standards.
Who We Serve
Our AI and machine learning practice serves AI/ML startups, enterprises deploying AI systems, AI-as-a-service providers, companies integrating third-party AI into products, foundational model developers, and AI research labs with commercial arms. We work with clients at every stage of the AI lifecycle – from early research and development through commercial deployment and scaling.