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CORAA University · AI Lab

Hands-on AI for audit.

A free practice ground for Indian CAs to learn AI tools used in audit. Practical guides, a prompt library built for the work you actually do, tool walkthroughs, and a synthetic SME you can poke around in. No certification, no paywall — just useful.

Read the practical guideBrowse the prompt library
What’s in the Lab

Five spaces, all audit-specific.

Each section is designed around how a practising CA actually works — engagement risk, sampling, vouching, CARO drafting, review notes, working-paper documentation. Not generic “AI for finance” content.

Guide · live
Using AI in Statutory Audit
The practical guide. Where AI helps in an Indian statutory audit, where it does not, what to keep off the prompt, and how to document AI use under SA 230. Read before you do anything else.
Read the guide →
Library · live
Audit Prompt Library
30+ audit-specific prompts you can copy. Planning, risk, sampling, vouching, CARO drafting, review notes. Each one shows the safe pattern — no client data, no sensitive identifiers.
Browse prompts →
Walkthroughs · live
AI tool guides for audit
How Indian CAs use Claude, ChatGPT, and Perplexity in audit work. What each tool is good at, where it falls short, and the prompts that fit each tool's strengths. DataSnipper / MindBridge / AlphaSense walkthroughs in the next drop.
Open the tool guides →
Tool · live
CARO 2020 Clause Navigator
All 21 CARO 2020 clauses in one interactive view — reporting requirement, what to verify, sample observation language for applicable and not-applicable cases. Sticky TOC for fast lookup.
Open the navigator →
Tool · live
SA-by-SA Audit Procedure Library
Browseable library of the Standards on Auditing — objective, key requirements, typical procedures, common pitfalls per SA. Filter by audit phase.
Open the SA library →
Playground · soon
Practice on a synthetic Indian SME
A browser sandbox with a 12-month synthetic SME — Tally export, GST returns, bank statements, statutory registers, planted anomalies. Try AI-assisted procedures without touching real client data.
Coming after tool walkthroughs
Weekly · soon
Audit + AI Weekly
One new tool, one regulator update, one prompt, one short read — every Tuesday. Stays in your inbox or on the archive page.
Signup opens soon
What this is, and isn’t

A learning ground, not a credential.

What we are
  • A free practice environment built by an audit-software team
  • Audit-specific content — Indian SA / Ind AS / Companies Act context
  • Hands-on labs and a prompt library you can copy and adapt
  • An onramp to the AI tools the rest of the profession is already using
What we aren’t
  • A certification body — only ICAI confers audit credentials in India
  • A CPE-hour issuer — refer to your ICAI Regional Council for structured CPE
  • A substitute for ICAI’s official AI programmes (AICA Level 1, AURA)
  • A place to upload real client data — everything here uses synthetic examples
Note on scope
CORAA AI Lab is a free practice environment built by CORAA. It is not a certification, not a substitute for any qualification issued by the Institute of Chartered Accountants of India (ICAI), and does not award structured CPE hours. ICAI’s official AI programmes — including AICA Level 1 and AURA — remain the authoritative credentials for AI competency in audit. We recommend using the Lab alongside or in preparation for ICAI’s programmes.
For real client data — built differently
CORAA is the AI engine built for Indian audit — India-hosted, DPDPA 2023 compliant, no training reuse.
Seven hubs covering the whole engagement: Setup → Scrutiny → Reconciliation → Procedures → Working Papers → Findings → Reporting. 164 scrutiny rules across 13 modules. SA 230, 240, 320, 450, 510, 530, 570, 700 baked into the workflow.
India-hosted
Every byte on Indian soil. Azure India regions for all production workloads.
DPDPA 2023 compliant
Data-fiduciary obligations built in by default. Not bolted on after the fact.
ISO 27001:2022 · SOC 2 Type II
Certified and attested. The security baselines enterprise audit committees actually ask for.
No training reuse
Client data never enters any foundation model. Contractual, not aspirational.
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