AI Vendor Assessment for IN

IN-specific obligations covered

The output is anchored on the regulations that apply to AI deployments in IN. The top frameworks cited:

• Digital Personal Data Protection Act 2023 (DPDPA)national_law · In force

  Data fiduciaries must obtain valid consent before processing personal data, implement reasonable security safeguards, respond to data principal rights requests including erasure and grievance redressal, and notify the Data Protection Board and affected individuals of data breaches.

• Information Technology Act 2000 and IT (Amendment) Act 2008national_law · In force

  Intermediaries hosting AI services must implement reasonable security practices as per CERT-In directions, comply with government orders to remove unlawful content within 36 hours, and publish user agreements disclosing data practices.

• CERT-In Directions on Information Security Practices 2022regulatory_direction · In force

  Covered organisations operating AI systems must synchronise ICT clocks with NTP servers, maintain logs of all significant activities for 180 days within India, and report cybersecurity incidents — including AI system breaches — to CERT-In within 6 hours.

• RBI Framework for Responsible AI and Machine Learning in Financial Servicesregulatory_guidance · In force

  RBI-regulated entities using AI for credit decisions, fraud detection, or customer interactions must implement model risk management frameworks including independent validation, maintain explainability for adverse decisions, and designate board-level accountability for AI governance.

How the AI Vendor Assessment approaches this

You describe the vendor (name and product or service) and your organisation's context — jurisdiction, industry, staff size, risk appetite — and choose your alignment framework: ISO/IEC 42001:2023, NIST AI RMF, or both. The tool produces a structured, evidence-based assessment ready to hand to your procurement, legal, and information-security teams.

The Executive Summary Word document is a one-page sign-off artifact — recommendation (Approved / Conditional / Rejected), top three risk flags, top three strengths, sign-off block. The detailed Excel workbook is the working assessment instrument: 30 questions across six weighted categories, with evidence guidance, regulatory call-outs, and an auto-summing scoring sheet. Both are AI-assisted drafting aids intended to accelerate review by qualified practitioners.

What you get

• ✓ Four deliverables, three jobs: Executive Summary (.docx) for board sign-off, Detailed Workbook (.xlsx) for the working scoring (with the Evidence Request List on a dedicated tab inside it), Procurement Checklist (.xlsx) for foundational readiness — no overlap, no confusion.
• ✓ Aligned to ISO/IEC 42001:2023 Annex A or NIST AI Risk Management Framework — your choice. Every question carries the framework reference and (where applicable) jurisdiction-critical regulatory call-outs.
• ✓ Excel formulas auto-sum each category total, calculate the weighted overall percentage, and surface Pass / Conditional / Reject thresholds — procurement teams don't have to re-key or re-calculate.
• ✓ Tailored to the vendor's product category, your industry, jurisdiction, and organisation size — not a generic checklist. Designed for review and sign-off by qualified procurement, legal, or information-security practitioners.

Ready to generate?

$29 · one-time — answer a 6-question intake (including jurisdiction = IN), and download your tailored document immediately.

Also available framed for your sector → see industry-specific pages