Where should a fund start?

With a workflow that has high friction or high volume: often the fundraising CRM or document due diligence, with a proof of value before scaling up.

Does AI replace investment judgement?

No: it speeds up analysis and frees up time; decisions and relationships remain human.

Should we go for a bespoke tool or an off-the-shelf SaaS?

A SaaS can be enough for a standard need; bespoke becomes necessary when the business has specific stages (fundraising, 100-day plan) that a generic tool does not model.

How is confidentiality protected?

Through a sovereign architecture: controlled hosting, role-based access, full ownership.

Where AI really creates value in a fund

In private equity, AI creates value in four places: speeding up sourcing and analysis, shortening document-heavy due diligence, industrialising portfolio monitoring and reporting, and smoothing investor relations. According to Bain's Global Private Equity Report 2025 (investors representing $3.2 trillion in assets), nearly 20% of portfolio companies have already operationalised generative AI with concrete results, while most are still at the testing stage.

The four value levers

Lever	What AI changes	Watch point
Sourcing and analysis	Screening a large number of targets on adjustable criteria, surfacing signals	Fundamental analysis and relationships remain human
Due diligence	Querying a data room in natural language, extracting the essentials from thousands of documents	Human verification on the decisive points
Portfolio monitoring	Consolidating reporting, surfacing revenue and margin variances, executing the 100-day plan	Reliability of the upstream data
LP relations and fundraising	Capturing field information, structuring the pipeline, automating investor reporting	Sovereignty of the investor base

At fund level or portfolio company level?

Two complementary areas of action. At fund level: equipping investment teams (sourcing, due diligence, LP reporting). At portfolio company level: supporting portfolio companies in their own AI transformation, a lever for operational value creation over the holding period. The same method applies to both: start from a workflow, prove the value, industrialise.

Why industrialisation makes the difference

Launching a tool is easy; getting it adopted and keeping it running over time is less so. The advantage goes to funds that build usage suited to their business rather than stacking generic tools: a CRM modelled on the real stages of a fundraise will be filled in; a generic CRM forced on the team will be worked around, as our AI Smart case shows. Institutional investors are also starting to assess managers on their command of AI, which makes it a matter of differentiation, not just efficiency.

Sovereignty, the non-negotiable condition

A fund's data (deals, investors, portfolio companies) is a strategic and confidential asset. Any deployment must provide for sovereign hosting, role-based access, ownership of the code and reversibility. The investor base remains yours. See also our AI for private equity pillar page.

Frequently asked questions

Where should a fund start?: With a workflow that has high friction or high volume: often the fundraising CRM or document due diligence, with a proof of value before scaling up.
Does AI replace investment judgement?: No: it speeds up analysis and frees up time; decisions and relationships remain human.
Should we go for a bespoke tool or an off-the-shelf SaaS?: A SaaS can be enough for a standard need; bespoke becomes necessary when the business has specific stages (fundraising, 100-day plan) that a generic tool does not model.
How is confidentiality protected?: Through a sovereign architecture: controlled hosting, role-based access, full ownership.

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Let's start with a single workflow

The entry point is simple, bounded, and you walk away with something useful either way.

You pick a workflow that costs you time or margin.

Within a few weeks, we diagnose it with your teams.

You leave with a costed plan and a first proof of value.