AI for teams

Give your whole team hours back each week.

Most organizations already pay for AI tools, and a few staff use them a lot. The rest don't know where to start, what's allowed, or whether it's worth the time. We start with your goals and the work your team repeats each week, then set AI up for that work.

Get a free Discovery and reportSee the process
"I work about ten times faster than I did a year ago. For a client, that means the same work at a fraction of the cost, or far more done on the same budget. Your team can learn to work this way too."
Dustin ColeFounder, Datawake

What we build with you

Six parts of a team that works well with AI

Each one is something your team keeps and runs after we're done.

Goals

We start by looking at the work your team does each week. Together we pick the tasks where AI can help most and agree how you'll measure it.

  • Two to five team goals with a measure for each
  • A list of tasks ranked by value and ease
  • What AI should not do, in writing

Knowledge

We organize your documents, policies and data so AI tools answer from your own sources.

  • A cleaned-up, well-named shared library
  • Source documents AI tools can use
  • A plan for keeping it current

Shared skills

Your team gets a library of tested assistants for the work you do every week, so people stop writing their own prompts from scratch.

  • Skills for grant drafts, donor letters, summaries and more
  • An owner and a review date for each skill
  • A simple way to suggest new ones

Training

Hands-on sessions grouped by role, using your real work. People leave each session with a finished piece of their own work.

  • Sessions for leaders, program staff and operations
  • Short recorded refreshers
  • Office hours while habits form

Reports and dashboards

You'll see who is using AI, for what, and whether it's moving your goals.

  • An adoption dashboard
  • Time saved on your goal tasks
  • A monthly summary for leadership or the board

Guardrails

Data privacy comes first. Short, clear rules so people feel safe using AI: what data can go in, what needs a human check and who approves new uses.

  • Data handling rules for donor, student and client records
  • A one-page AI use policy
  • A review step for anything public-facing

How an engagement runs

Eight steps, and you see each one before we move on

You get a written status report every week, and we meet at least weekly. Nothing gets built until your team has seen it and had a say.

1

Discovery

We interview people across your team, look at the tools you already pay for and learn where time goes each week.

You getA short findings report: what's working, what isn't and where AI could help first.
2

Workshops

Working sessions with your staff to map the real work, agree on goals and decide what AI should and shouldn't touch.

You getAgreed team goals, a ranked list of tasks and a draft of your guardrails.
3

Mockups

We show you the skills, the knowledge library and the dashboard as clickable mockups before anything is built.

You getMockups you can click through and share with your team.
4

Feedback

Your team tries the mockups and tells us what's missing or confusing. We revise until they say it fits how they work.

You getA design your team has signed off on, with their changes made.
5

Training

Hands-on sessions by role, on real tasks from your own week, while the pieces are being built.

You getTrained staff, session recordings and a cheat sheet for each role.
6

Documentation

Plain-language guides for every skill, every policy and every dashboard, written for the people who'll use them.

You getA guide your team owns and can update without us.
7

Delivery

We switch everything on in the tools you already use, then stay close for the first weeks to catch problems early.

You getWorking skills, a live dashboard and a named owner for each piece.
8

Success

We check results against the goals from step 2 and agree on what comes next, whether that's more help or none at all.

You getA results review against your goals and a plan for the next quarter.

What success looks like

How we measure it

We agree on the exact measures with you in the workshops. A typical engagement looks something like this.

30 days

Goals agreed, guardrails drafted, knowledge library organized and the first shared skills in mockup.

60 days

Every role trained, the first skills in daily use and the dashboard showing real usage.

90 days

Results reviewed against your goals, documentation handed over and your team running it on their own.

Built on systems that work

Your data has to be in good shape first

AI repeats whatever mistakes are in your records. Because we've spent 10 years on nonprofit Salesforce and data work, we can merge duplicates, connect your tools and fix your CRM in the same project, so AI reads from clean records.

See what we help with →

See what this would look like for your team

Start with a free Discovery and report. We'll talk with people across your team, look at the AI tools you already pay for and write up where AI would save the most time first.

Get a free Discovery and report