Will our proprietary methodology end up training someone else's model?

No. Deployments keep your IP inside your tenant. Nothing trains a public model.

What about Harvey-style legal/consulting products?

If one fits, we'll point you at it instead of building. We're not in the business of selling our own tools when better off-the-shelf options exist.

We're a 12-person boutique. Worth it?

Often yes. The partner-to-leverage ratio in boutiques is exactly where the compounding shows up.

Will this dilute the firm's voice?

Only if you let it. We deploy with a tone library and human review at the touchpoints that matter. The voice gets more consistent, not less.

Can this help with new business development?

Yes — research on prospects, structured prep notes, and faster turnaround on RFPs. Indirectly it lifts win rate by simply showing up better-prepared.

AI for Professional services (consulting and agencies) in Singapore

How is AI useful for pro services in Singapore?: For Singapore consultancies and agencies, AI's defensible wins today are proposal and pitch production, structured client research, and getting first drafts of deliverables out of senior heads and onto the page. The judgement stays human; the typing stops being where the senior team's hours go.

What we see most

The three friction points showing up in pro services this year.

Senior partners are the production bottleneck

The partner does the thinking and ends up doing too much of the writing. Junior leverage is real on paper, weak in practice.

Proposals are written from scratch when most of them aren't

The structural parts of every proposal — credentials, case studies, methodology — are the same. Bespoke language gets recreated each time anyway.

Research and synthesis take hours that should take minutes

Background reading, competitive context, document review across a dozen sources — the junior spends days on what AI can compress to hours, freeing them to actually think.

Where AI actually helps today

Three honest wins. One thing we'd still wait on.

Proposal and pitch co-pilot

Structured intake in; first-draft proposal out, drawing on your real case studies and methodology. Partner edits the bespoke layer instead of writing the whole thing.

Client research and synthesis

Junior runs a structured research pass with AI, surfaces a clean briefing document, and walks into the partner meeting prepared instead of half-read.

Deliverable first-draft generator

Partner's voice memo + structured outline + reference deliverables go in; a credible first draft comes out for the team to edit. Senior partners review instead of compose.

Not yet