AI Browser for Consultancies: Meeting Prep

How consultancies run meeting prep in Strawberry. Surfaces, signals, real output, and tradeoffs for consultancies.

This guide is for consultancies that run meeting prep. It names the surfaces a consultancy typically uses, where the friction sits, and how an AI browser like Strawberry runs the workflow without forcing the team to learn a new stack.

How consultancies approach meeting prep

A consultancy runs this work in a specific way: deliver strategy, transformation, and ops work for client companies on a project or retainer basis. The current pain is concrete - every engagement repeats the same research, framework selection, and reporting work but for a different client. The reason an AI browser helps here is that consultancies already touch many surfaces (Google Workspace, Slack, Notion or Confluence, Looker Studio or Excel, LinkedIn), and the bottleneck is the human moving data and context between them.

What a good meeting prep run looks like for consultancies

The goal is to produce a one-page brief for each upcoming meeting so the person walks in informed and time isn't wasted. Success metric: subjective - the meeting feels productive; objective - notes/next-step ratio is high. In an industry context that means: deliverables that look like a senior consultant wrote them, in less time, and easier to update mid-project.

Buying signals meeting prep should react to

The signals that should trigger meeting prep for a consultancy include: client growth-stage shift, regulation change in client industry, leadership team change. Strawberry watches the public web (LinkedIn, news, job boards, the company's own site) for these and pairs them with whatever lives in the team's existing tools.

How Strawberry runs meeting prep for consultancies

  1. Connect the existing stack (Gmail, CRM, sheets, Slack, etc) so Strawberry can read in-place.
  2. Define one sentence of what 'done' looks like for meeting prep in your specific consultancy setup.
  3. Ask Strawberry to read the relevant context, then research the gaps via the browser.
  4. Strawberry produces the meeting prep output in the shape your team can use immediately.
  5. A human reviews before any external action (send, update, post) goes out.
  6. The approved output gets logged back into your system of record so the next person sees it.

A real meeting prep output for consultancies

This is an example of the shape, not your literal team's output - swap the specifics for your context:

  • Meeting: 14:00 Thursday with Anna Lindqvist (VP Marketing, Voi) and Erik Nilsson (Head of Growth)
  • Last touch: warm intro from Marcus on May 14, no reply since
  • Company news: Germany pullout announced May 28; hired 4 paid acquisition managers in Q1
  • Suggested agenda: 1) Their take on Germany decision, 2) Where retention sits in 2026 priorities, 3) Show 90-sec demo of win-back loop
  • Three questions: How is the team structured post-pullout? What's the budget cycle? Who owns retention KPIs?

When this is right for consultancies, and when it is not

This workflow is right when consultancies have multiple recurring instances of meeting prep to run each week, and when the existing stack is mostly online and connectable. It is the wrong fit when meeting prep happens once a quarter or requires deep domain expertise the agent does not have. In that case, the consultancy should run it manually and capture the playbook for the next iteration.

Three mistakes to avoid

  • Generic bios instead of role-specific context
  • Missing the most recent news that the prospect would expect you to know
  • No link back to the prior conversation thread

Caveats

Strawberry holds back on sending email, updating CRM records, or changing shared systems until a human approves the action. Treat the agent as a fast first-draft author, not an autopilot.

Consultancies + Strawberry running meeting prep

1 Inputs

Stack

Typical consultancy surfaces: Google Workspace, Slack, Notion or Confluence.

2 Triggers

Signals

Watch: client growth-stage shift, regulation change in client industry.

3 Output

Compose

Synthesise into the meeting prep shape.

4 Review

Human

Approve before external actions; log to system of record.

FAQ

Does this work for small consultancies?

Yes - the workflow scales down to a 2-person consultancy. The smaller the team, the more leverage an AI browser provides because the same person owns multiple surfaces.

Which tools do consultancies need to connect?

The most common stack: Google Workspace, Slack, Notion or Confluence, Looker Studio or Excel, LinkedIn. The browser handles everything else without setup.

What is the biggest mistake to avoid?

Generic bios instead of role-specific context.