# How to choose AI for a corporate finance or M&A advisory firm: a checklist

> A vendor-neutral checklist for choosing AI software for a corporate finance or M&A advisory firm: data residency, sub-processors, classification, audit trail, template fidelity, ownership, integrations and implementation.

URL: https://www.mindro.co/guides/choosing-ai-for-corporate-finance
Last updated: 10 October 2026

**Short answer:** Choose AI software for a corporate finance firm on four things: where client data is stored and processed and who can see it; whether the output matches your firm's own templates and standards; whether the knowledge it builds belongs to your firm; and whether the vendor helps your team change how it works. The checklist below turns these into questions you can put to any vendor, followed by Mindro's own answers.

## The checklist

| Question to ask | Why it matters for a corporate finance firm |
|---|---|
| Where is data stored and processed, and can EU-only be guaranteed? | Client materials are confidential and often covered by NDAs and GDPR |
| Who are the sub-processors, and is there a Data Processing Agreement? | You need to know which model and cloud providers touch client data |
| Can access be limited per tool and per classification level? | Not every AI tool should see client data under NDA, let alone inside information |
| Is every data access logged by user, tool and time? | You must be able to show who saw what, and through which tool |
| Is client data used to train models? | Your deal knowledge should not improve a model everyone else uses |
| Can every figure in a draft be traced to its source? | IMs and pitch materials must stand up to buyer and client scrutiny |
| Does it follow your own templates and output in the formats you use? | Most firms work in PowerPoint and in their own house style |
| How deep is the integration with where your documents live? | Most deal history sits in SharePoint, CRM, email and meeting notes |
| Who owns the knowledge the system builds, and can you take it with you? | Your firm's knowledge is part of its value |
| Which models does it use, and can you switch without renegotiating compliance? | Models change quickly; your data rules should not |
| What implementation, training and engineering support is included? | Software alone rarely changes how a team works |
| Can it connect to the AI tools your team already uses, under your rules? | Some teams already work in Claude, ChatGPT or Microsoft Copilot |

## How Mindro answers the checklist

| Question | Mindro |
|---|---|
| Data storage and processing | SaaS run fully in Europe; EU data residency guaranteed. Institutions can also run Mindro in their own VPC, on-premise, or ring-fenced in another region |
| Sub-processors and DPA | Mindro is data processor under a DPA. Sub-processors: Google (Vertex AI / Google Cloud), Weaviate, and Anthropic (Claude) when Claude is used |
| Per-tool, per-level access | Configured per client in the Institutional setup: Mindro and the client agree which data levels each connected AI tool may use |
| Audit trail | Every data access logged by user, tool and time |
| Training on your data | We do not train on your data |
| Traceability | Every figure in a draft links back to its source document |
| Templates and formats | IM drafts follow your firm's own template; output is PowerPoint, with PDF export from there |
| Integrations | SharePoint (deep, proven), CRM, email, meeting notetakers, Microsoft 365 add-ins, and data providers such as Gain and Inven |
| Ownership | Your firm owns its firm brain, portable by contract |
| Models | Claude, Gemini and Mistral; an AWS-based setup on request also allows OpenAI models |
| Implementation | Transformation support, training and data and AI engineering included in every plan. [Services](https://www.mindro.co/services) |
| Other AI tools | MCP and API connections configured per client on request. [Setups for institutions](https://www.mindro.co/institutional) |

## Questions to ask in a demo

1. Show a draft built from our own materials, and trace three figures back to their source.
2. Show the draft in our template, in PowerPoint.
3. Show who accessed a document, when and through which tool.
4. Explain what happens to our data, and our firm's knowledge, if we leave.

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