It starts with the intelligence layer powering your organization: decisions, policies, roles, customer context, and workflows that both humans and agents can act on. So AI deployments deliver returns you can measure.
companies may be genuinely AI-native at meaningful revenue scale
of workplace AI runs through personal accounts
the first pass of structured work agents should handle once workflows are redesigned
revenue per employee at AI-native startups vs. traditional SaaS
Most companies are illegible to machines: customer truth split across CRM, Slack, inboxes, and the memory of a few indispensable people, policies undocumented, decisions implicit. The coupling gap is what that costs you: hard savings locked inside roles and software that manual workflows require, revenue left on the table as your best people spend their hours on work agents could handle, and cross-functional potential that never compounds because no department can build on what another built. Close the gap and all three open.
There's going to be a huge gap in execution velocity for the foreseeable future between the individuals, teams, and companies that adapt their workflows to work with AI agents vs. those that don't.
Over four weeks, we select the workflows with the highest potential, map them end to end, surface the decisions and rules people carry in their heads, and instrument the baselines needed to measure what moves the needle. The output is a three-layer return estimate: the hard savings available this quarter, the revenue-adjacent KPIs we can move as humans shift to higher-value work, and the cross-functional potential that compounds. You leave with a defensible number, a 90-day roadmap, and an offer structure that puts us at risk against the result.
Bolting agents onto today's structure produces the same pilots, the same failures, the same return of zero. We work underneath to diagnose where the optimization potential is locked, redesign the structure so it's legible to agents and humans alike, then deploy AI into a company built natively around it.
We start where most companies are: AI-assisted, with tools bolted onto a structure built for humans. We map the workflows with the most optimization potential end to end: what triggers each one, what context it needs, where decisions live, and what it costs when it goes wrong. The baselines get set here: hard savings this quarter, KPIs with a dollar chain attached, and the cross-functional potential locked downstream.
Read moreWe make the company legible to agents and to the people guiding them. Policies become explicit. Customer history becomes structured. Pricing logic, brand voice, escalation paths, and approval criteria move out of inboxes and into the intelligence layer. The company becomes AI-readable, and the hard savings start to unlock.
Read moreAgents go live inside a company built to hold them. Structured work routes to agents; judgment, relationships, and growth route to people. KPIs start moving. Every deployment leaves a deposit in the shared intelligence layer, the context compounds, each build costs less than the last, and the cross-functional potential stuck in the coupling gap begins to unlock.
Read moreThe coupling gap costs you savings this quarter, revenue growth next quarter, and cross-functional potential that compounds after. The audit names all three, sets the baselines, and scopes the path from AI-assisted to AI-native.
