EntGovReady helps regulated Indian organisations put real governance around the AI they already run — mapped to ISO/IEC 42001, the RBI's FREE-AI framework and the DPDP Act, and built to survive an audit rather than sit in a folder.
Most organisations adopted AI faster than they built controls around it. Credit decisions, underwriting, fraud screening, hiring, supplier scoring — running live, with no owner, no test record and no way to explain a decision to the person it affected.
Sector regulators now expect a named owner, a documented risk assessment and evidence that the model was tested before it went live — not an assurance that it works.
Directors are being asked to sign off on systems nobody in the room can explain, with liability that sits squarely with them if one of those systems gets it wrong.
An answer of "the model decided" is no longer defensible — commercially, reputationally or under the transparency obligations now landing across jurisdictions.
Each stage stands alone, and each one sets up the next. Most organisations start at the assessment and decide from there.
A complete inventory of the AI in use — including third-party and shadow systems — scored against ISO/IEC 42001, RBI FREE-AI and the DPDP Act. You get a gap register, a risk-ranked view of which systems matter most, and a twelve-month roadmap you can take to the board.
The core build. Governance structure, ownership and escalation paths, plus a set of policies written for your systems and your risk appetite — not a template pack. Covers the AI lifecycle end to end: risk, fairness testing, validation, explainability, monitoring, data and third parties.
For organisations going all the way to a certificate. Internal audit against the standard, closure of nonconformities, evidence organised the way a certification body expects to receive it, and hands-on support through Stage 1 and Stage 2.
Governance decays the moment the project ends. A standing retainer keeps it alive: monthly review of drift and fairness metrics, quarterly compliance checks, regulatory change tracking, and the annual refresh that keeps your documentation true.
A focused review of a single AI system — before you launch it, or after someone has asked a hard question about it. Fairness testing, accuracy validation, explainability review, and a written assessment you can hand to a regulator or an internal audit committee.
ISO/IEC 42001, RBI FREE-AI and the DPDP Act ask overlapping questions in different language. Treated as three programmes, you pay three times. Treated as one control set, most of the work is shared.
| Governance domain | ISO/IEC 42001 | RBI FREE-AI | DPDP Act | EU AI Act |
|---|---|---|---|---|
| Accountability & ownership | Leadership | Governance | Fiduciary duties | Provider duties |
| AI inventory & scope | Context | Infrastructure | — | Registration |
| Risk & impact assessment | Cl. 6.1.2 / 6.1.4 | Assurance | Impact assessment | Risk management |
| Data governance & privacy | Annex A | Protection | Core obligations | Data quality |
| Fairness & bias testing | Annex A | Fairness sutra | — | Bias examination |
| Transparency & explainability | Annex A | Understandable by design | Notice & consent | Transparency |
| Monitoring, drift & incidents | Cl. 9 | Assurance | Breach reporting | Post-market |
| Third-party & vendor AI | Annex A | Policy | Processor duties | Value chain |
| Audit evidence & records | Cl. 9.2 | Assurance | Record-keeping | Documentation |
Coverage shown at domain level. The clause-by-clause mapping forms part of the assessment.
No discovery phase that produces a slide deck. Every phase ends in something you can act on, show a regulator, or hand to an auditor.
Interviews across technology, risk, compliance and the business. Every AI system catalogued — including the ones procured without anyone telling the risk team. Scored against the frameworks that apply to you, and ranked by exposure.
Working sessions to set your risk appetite, name the accountable roles, and design a governance structure that plugs into the committees you already run rather than adding another one nobody attends.
The policy set, drafted against your systems and reviewed with the people who have to live with it. Lifecycle, risk, fairness, validation, explainability, monitoring, data, third parties — each one specific enough to be followed and short enough to be read.
Committee stood up, dashboards reporting, escalation paths tested, teams trained. Then internal audit against the standard, and — if certification is the goal — evidence assembled the way a certification body expects it.
Credit scoring, underwriting, collections and fraud models under direct RBI and IRDAI expectations, where an unexplainable decline is a regulatory problem before it is a customer one.
Fast-moving lending and risk models built before governance existed. Usually the quickest to fix — and increasingly asked about during bank partnership and investor diligence.
AI in supply chain, quality, hiring and ESG data collection. Governance gaps show up as unreliable disclosure long before they show up as a regulatory finding.
If you sell AI into regulated buyers, their procurement team now audits your governance. Being able to answer that questionnaire is a sales asset, not a compliance cost.
RBI FREE-AI and the DPDP Act are the starting point, not an appendix bolted onto a European framework. International standards are mapped in — the other way round.
You get the person who does the work. No partner at the pitch and an analyst on delivery, and no six-week ramp-up billed back to you as discovery.
Policies specific to your systems, short enough that people read them, and structured so the evidence an auditor asks for already exists as a by-product of running them.
The failure mode is a framework that is perfect on the day it ships and stale six months later. Monitoring, review cadence and regulatory tracking are designed in from the start.
A 30-minute call, no charge and no deck. Tell me what you have running and what is worrying you, and I will tell you honestly whether you need an assessment, a full framework, or nothing at all yet.