AI & Data Governance Consulting

Inferred Personal Data

AI models don't just process the data you give them — they infer new personal data from it. A model can infer health conditions from purchase history, political views from browsing patterns, or financial stress from location data. Inferred data is personal data under the DPDP Act — and users never consented to its creation.

Automated Decision-Making

Loan approvals, hiring decisions, insurance pricing, and credit scoring driven by AI algorithms make significant decisions about individuals without human review. DPDP Act and emerging AI frameworks require explainability, contest rights, and human oversight for high-stakes automated decisions.

Unlawful Profiling

Building detailed behavioural, psychological, or demographic profiles of users for advertising targeting or content personalisation without explicit consent is a direct DPDP violation. Profiling requires specific consent and disclosure — most current implementations have neither.

Training Data Liability

AI models trained on personal data without valid consent, proper anonymisation, or documented legal basis create permanent compliance liability. Every prediction a non-compliant model makes is based on unlawfully processed personal data — and the liability compounds with every use.

AI Privacy Risk Assessment

Structured assessment of your AI systems' data privacy risk profile — identifying personal data inputs, inferred outputs, training data practices, automated decision points, and data retention — mapped against DPDP Act requirements and global AI governance standards.

AI Governance Framework Design

Design of a comprehensive AI governance framework for your organisation — covering model development policies, data sourcing standards, bias testing requirements, explainability obligations, human oversight protocols, and an AI ethics charter aligned with your business values.

Privacy-by-Design for AI Products

Embedding privacy protection into your AI product development lifecycle from the earliest design stage — data minimisation in model architecture, purpose-bound training datasets, privacy-preserving techniques, and consent-first data pipeline design before a single line of model code is written.

Data Governance Strategy

Enterprise-wide data governance strategy covering data classification, data quality standards, data ownership and stewardship, lineage tracking, access control architecture, and data lifecycle management — creating the foundation that makes both AI performance and DPDP compliance possible.

AI-Specific DPIA

Data Protection Impact Assessments specifically designed for AI systems — addressing the unique risks of inference, profiling, automated decisions, model drift, and emergent behaviours that standard DPIA templates do not capture. Required before deploying high-risk AI systems.

AI Policy & Legal Documentation

Drafting of AI-specific legal documents — AI usage policy, automated decision-making notice, algorithmic transparency disclosure, model card documentation, AI procurement standards, and third-party AI vendor due diligence frameworks.

Multi-Jurisdiction AI Compliance

For AI products serving global markets — compliance advisory covering DPDP Act (India), EU AI Act, GDPR automated decision rules, UK ICO AI guidance, and US state AI regulations simultaneously. One governance framework that works across every market you operate in.

AI Ethics & Privacy Training

Training programmes for data science teams, product managers, and leadership — covering responsible AI principles, privacy-preserving ML techniques, bias identification and mitigation, and the legal obligations that apply to every person who builds or deploys AI systems in your organisation.

India's primary data protection law — the foundation of all our AI governance advice. We ensure AI systems meet consent, purpose limitation, data minimisation, and rights requirements under the Act.

The world's first comprehensive AI regulation — risk-based classification of AI systems, prohibited AI practices, transparency requirements, and human oversight obligations. Applies to any AI system used in the EU market.

GDPR's automated decision-making provisions — right to human review, right to contest, and requirement to explain automated decisions. Critical for AI serving European users or companies.

The US National Institute of Standards and Technology AI Risk Management Framework — the globally recognised standard for identifying, measuring, and managing AI-related risks across the full model lifecycle.

The international standard for AI management systems — providing a structured approach to responsible AI development, deployment, and monitoring. The AI equivalent of ISO 27001 for information security.

India's Ministry of Electronics and IT advisory guidelines on responsible AI — covering transparency, accountability, safety, inclusivity, and privacy principles specific to the Indian regulatory and social context.

AI Product Companies

Businesses building AI-powered products — chatbots, recommendation engines, fraud detection, computer vision, NLP tools — that process personal data as their core input or output.

FinTech & BFSI

Banks, NBFCs, and FinTechs using AI for credit scoring, fraud detection, KYC, insurance pricing, and investment advisory — where automated decisions directly affect individuals' financial lives.

HealthTech & MedTech

Healthcare AI applications — diagnostic tools, patient risk stratification, drug discovery, medical imaging — handling the most sensitive personal data category with the highest regulatory expectations.

E-Commerce & Retail

Personalisation engines, dynamic pricing algorithms, customer segmentation, and purchase prediction models that profile millions of customers based on their behaviour and preferences.

HR Tech & Hiring Platforms

AI-powered candidate screening, interview analysis, performance prediction, and employee monitoring tools — where automated decisions directly affect employment outcomes and carry significant bias risk.

Enterprises Deploying AI

Large organisations integrating third-party AI tools (Microsoft Copilot, Salesforce Einstein, custom LLMs) into operations — needing governance policies for responsible internal AI use and vendor AI oversight.

Law + Technology Combined

AI governance requires both legal expertise and technical understanding of how AI systems actually work. Our team includes advocates with Cyber Law and IT expertise alongside technologists — rare in India's advisory landscape.

India Context Expertise

Deep understanding of how the DPDP Act applies specifically to AI in the Indian context — including sector-specific requirements from RBI, SEBI, IRDAI, NHA, and MeitY that global AI governance consultants often miss.

Global Framework Fluency

Fluent across DPDP Act, EU AI Act, GDPR, NIST AI RMF, and ISO 42001 — giving Indian businesses building for global markets a single advisory partner for all jurisdictions.

Ahead of Regulation

AI regulation is evolving rapidly. We track every development — DPDP Rules notifications, EU AI Act implementation timeline, MeitY guidance updates — so your governance framework stays ahead of regulation rather than catching up to it.

Practical, Not Theoretical

We deliver governance frameworks your engineering teams can actually implement — not academic policy papers. Every recommendation comes with practical implementation guidance your developers and product managers can act on.

Continuous Advisory Model

AI systems evolve. AI regulations evolve. We offer retainer-based ongoing advisory so your governance stays current as your models change, new use cases emerge, and regulators publish new guidance.