By Fit

How we choose engagements.

Two to three new clients a year. The math is on purpose. Most companies who reach out, we politely decline.

Four criteria. All four required.

01

Proprietary intelligence inside the company.

You have decision frameworks, operational playbooks, underwriting rules, trading heuristics, customer history. The intelligence is real. It lives in people’s heads and in isolated spreadsheets. We will help you make it legible to agents and own it as IP.

Disqualifier / If your company has no proprietary intelligence to surface, the AI-Native rebuild has nothing to compound on.

02

A leader at the CEO or President level willing to redesign the company.

The transformation is structural, not tooling. Better AI usage will not get you where you need to go. The leader has to mean it.

Disqualifier / If the project is owned three layers below the person who would actually make the call, we say no.

03

Small enough to move, large enough to matter.

Companies between $25M and $100M in revenue. Privately held. Operator-led.

Disqualifier / Below $25M is rarely deep enough to compound. Above $100M is usually too big to move at the pace this work requires.

04

Willing to let us go deep.

Deep means our team sees the books, sits with the people, gets handed the spreadsheet that has the real overlays in it.

Disqualifier / Companies that need to keep their consultants at arm's length are not for us.

The decision.

When all four are true, we say yes. When one is missing, we have an honest conversation about whether the fit is real. When two are missing, we say no, and we tell you why. If we are not the right firm, we will tell you that and refer you to people who are.

Financial Services Focus.

We have built our deepest expertise in financial services. The industry's combination of high-stakes decisions, structured data, and stitched-together legacy systems is exactly where AI-Native transformation produces a number that matters. Two areas in particular have shaped how we work.

Mortgage.

Mortgage is the proving ground for almost everything we believe about AI-Native operations. Twenty years of stitched-together loan origination systems. Scattered borrower data. Undocumented overlays held in three people's heads. Compensation structures built on transactional volume. Lock desks negotiating exceptions verbally. We have lived inside this environment long enough to know which workflows are worth rebuilding first, and we have built the tools to rebuild them.

The cost-per-funded-loan can drop by a number that matters when the cognition map, the operating layer, and the agent infrastructure all come online together. The 150-person mortgage company starts doing the work of 400, and the remaining humans are doing higher-judgment work than they were doing before.

Asset Management.

Asset management is the other domain we know well. Trust administration. Estate complexity. Investment research. Compliance overlays. Family-office coordination. The work is dense, the data is fragmented, the decisions are senior, and the stakes are personal.

AI-Native operations let smaller teams handle far more volume without losing the judgment that defines the business. We have built tooling specifically for this market. Software that turns estate administration from a coordination problem into a managed pipeline. View more detail on the Case Studies page.

The First Conversation.

Thirty minutes. No deck. By phone or video, with one of the partners.

We learn where you are in the journey. You learn what we actually do. Both sides decide whether the fit is real before any proposal exists.