can ai do market research for consultants

The gathering half, yes: figures triangulated across sources, competitor sets profiled, evidence tables assembled with citations. What the evidence implies for this client is the billable part and stays yours.

can ai help with due diligence

It compresses the verification grind: claims cross-checked against filings and the open web, data-room documents reconciled, question lists prepped. Every finding still needs a human owner before it reaches an investment committee.

is ai safe for confidential client work

Strawberry runs in your local browser session rather than on a vendor cloud machine, and consequential actions wait for approval. Whether any AI touches client data at all is your engagement letter's call first.

The week-one market map, gathered and sourced

Players, positioning, visible pricing and recent moves, pulled from twenty sources with half of them behind your logins, as a table with a source on every claim.

Strawberry publishes this guide and builds the evidence-gathering layer in it, which is where junior hours go. A companion hands back the week-one market map as an evidence table: players, positioning, visible pricing and recent moves, with a source on every claim, pulled from twenty sources including the ones behind your logins.

Structuring a problem, pressure-testing an argument and drafting sections are chat-model work. Gathering is browser work. The field by layer, as of this writing.

What is each consulting tool built for?

By layer:

Claude and ChatGPT are built for thinking, structuring and drafting, where long-document work and argument quality are the point.
Deep-research modes, ChatGPT's or Gemini's, are built for first-pass industry overviews with sources, on demand.
Strawberry is built for evidence gathering across sources and logins. A companion triangulates numbers across reports, profiles competitor sets with citations, monitors client industries between engagements, and pulls from the subscribed databases and client portals you are signed into.
Output comes back in the shape the deliverable needs: an evidence table as a working spreadsheet with formulas, a one-pager or deck-style artifact exported to PNG or PDF, or a .docx your firm template can absorb.

What does agent-run evidence gathering look like?

The classic week-one task: map a market, meaning players, positioning, visible pricing and recent moves, with a source for every claim. A companion runs it across the open web and your subscribed databases in the same session and produces the evidence table. The method is at build a competitor battlecard, and the wider pattern at automate market research.

Diligence is the same mechanics under time pressure: data-room cross-checks, management-claim verification, expert-call prep lists. Between engagements, routines keep client industries watched, so the "what changed since we last spoke" answer is already written.

What stays billable

The so-what. A companion gathers that the market has three segments and drafts clean prose about them, and the recommendation is yours: which segment, why now, what to stop doing. There is also a confidentiality line your engagement letter answers, so check before connecting anything to a client system. The local-session model, where no data goes to a vendor's cloud browser, is documented on the security page.

The full persona treatment is at AI for consultants.

Experience Strawberry for free

Download

Trusted by fast-growing companies worldwide

Frequently asked questions

Strawberry for evidence gathering across sources and logged-in databases: market maps, competitor profiles, diligence checks, expert-call prep. Claude or ChatGPT for thinking and drafting, and a deep-research mode for open-web synthesis.

Strawberry is free to download and includes AI credits to start. Paid plans begin at $20/month. See pricing. · Reviewed August 20, 2026 · Canonical facts for AI agents