Offerings

One path, taken in steps.

Three AI engagements, designed as a progression. Most organizations start with the Clarity Sprint and find a Use Case Build emerging from it. Some arrive with the gap already named. The right entry point depends on where you actually are.

AI Clarity Sprint

A safe first step toward clarity.

Duration: Two to four weeks
Investment: $20,000 range
Best for: Leaders who have been pitched too much, piloted too little, and need a sober readout: one the operator can put in front of the board, and a tangible artifact the executive team can actually touch.

You leave with

A four-axis gap reading (Data, Software, Collaboration, and Skills) sized against what your strategic plan actually requires, paired with our honest read of how far we can move each one
Clear answers to the questions your leadership is likely asking: what’s leaking, what’s silently holding you back, what’s genuinely possible here, and what to do first
Two to three prioritized opportunities, ranked with cost, complexity, and risk laid out without hedging
A scoped, priced first Use Case Build you can take straight into a budget conversation
The findings rendered in the formats your stakeholders actually engage with: boardroom PDF, written report, interactive microsite, podcast episode, or a loaded AI context bundle for your own environment

How it goes

01

Listen

1:1 conversational interviews with operators across the business, captured carefully. We ask how your stakeholders consume information so the readout lands in the formats they’ll actually use.
02

Measure

A subjective gap reading on four axes (Data, Software, Collaboration, Skills) sized against the strategic plan. Concrete enough to make the funding case, honest about where we can and can’t move the needle.
03

Diagnose

What’s leaking now. What’s silently holding you back: the legacy system, the bad-fit vendor, the aging internal tool whose economics may have just flipped. What’s genuinely possible. No sales pitch in the synthesis.
04

Render

The same source material, shaped into the formats your stakeholders engage with. Boardroom deck, written report, microsite, podcast, AI context bundle, chosen with you in week one.
05

Recommend

A scoped, priced first Use Case Build the operator can take straight into a budget conversation.

The first Use Case Build is part of the deliverable. By the end of the Sprint, the next step is already scoped and priced.

AI Use Case Build

From a named gap to a working capability in production.

Duration: A couple of months. Fixed price, fixed scope, one team.
Investment: $75,000 range
Best for: Organizations ready to close one of the capability gaps named in the Sprint, in service of a specific outcome the strategic plan actually requires. You want a tool your team can use every day.

You leave with

A working capability in production, owned outright by you, with the data infrastructure behind it
New collaboration patterns inside the organization (channels of trust, decision rights, and routines) built around the capability
Trained people at every level that touch the capability, from leadership to daily operators
An updated map of candidate next Builds, refined by what this one taught everyone

How it goes

01

Data

Connect, clean, and govern the data infrastructure the capability needs. Picked from the inventory the Sprint produced.
02

Software

Build the sanctioned capability on top of that infrastructure. Visible, operator-grade, in production. Not a prototype.
03

Collaboration

Establish the channels of trust and the routines that make the capability usable: decision rights, meeting cadences, handoffs. The organizational change is threaded through delivery, not bolted on as a side workstream.
04

Training

Bring every relevant employee and leader to real working capability, from 1:1 coaching for an executive up to fifty-person workshops for a function. Often basic AI fluency before anything advanced.

Most clients run a couple of Builds in succession. The first proves the pattern; the next one or two extend it into adjacent areas. By the end of that small series, a Transformation MOU is the obvious next move.

AI Transformation Partnership

From scattered adoption to an organization that uses AI well.

Duration: Ongoing, annual cadence
Investment: Custom, scoped to cadence
Best for: Organizations that want AI working across the whole business, not as a series of pilots, but as a shift in how people are trained, what tools they reach for, and how they decide when to use AI and when not to.

You leave with

An organization-wide training program: leadership, operators, and staff each meeting AI at the right altitude
A tooling landscape that’s been chosen on purpose, not accumulated by accident
Shared discernment: clear criteria for when AI is the right answer, and when it isn’t
Guardrails that travel: security, privacy, and human-review patterns that hold up across departments

How it goes

01

Assess

We look at the whole organization: how work flows, where people already use AI, where shadow usage has crept in, and where the real risks live.
02

Train

Role-appropriate education across the org. Leaders learn to govern, managers learn to direct, operators learn to use the tools well.
03

Equip

A coherent tooling stack, chosen, configured, and secured, instead of a dozen overlapping subscriptions.
04

Discern

An ongoing cadence for deciding what to adopt, what to pause, and what to walk away from. AI gets used where it earns its place.

Curious where to start?

Let’s figure it out together.

Most organizations start with the Clarity Sprint and build from there. Some arrive with the gap already named. If you’re not sure where you fit, that’s exactly what the Sprint is for.

Talk through your situation