Your AI-powered project management system
AI takes the reporting, the summaries, the project memory. Your managers keep the judgment. We build it on your tools and your context, and measure what changed.
Your AI runs on the same models as everyone's.
What it lacks is everything that makes your projects yours: who promised what, why decisions were made, which deadline is contractual and which is a hope. Without that, AI writes plausible text with wrong specifics, your managers double-check everything, and adoption quietly dies.
So we don't start with tools. We build your project context: commitments, decisions, history, language, structured so both your managers and your AI can use it. The same context that briefs a new manager in days is what makes an AI status draft come out right.
Structuring it is management work, not IT work. Knowing what counts as a commitment and which decisions matter is methodology. That's what eighteen years of building project management systems are for.
Who we build systems with
- Owners, CEOs and COOs of 100+ person project-driven organizations where delivery depends on a few strong managers
- PMO directors who inherited a tool zoo without a method
- Leadership teams whose maturity roadmap stayed on paper
- Organizations that invested in AI and see no trace of it on projects
- Commercial and non-profit alike: donor accountability changes the governance lens, not the disease
Four phases.
Diagnostic
2 weeks, fixed fee. Management maturity, information flows, where context lives today and where it dies. Ends with numbers and a build roadmap, useful whether or not you continue with us.
Diagnostic page →System design
The method that fits your organization, the decision cadence, and the split between what AI does and what managers decide. Validated with your leadership before anything is built.
Build
We configure the tools you own and add only what's proven missing. We build the context layer: glossary, templates, decision log, commitment register, project memory. AI starts producing the routine inside your own tools.
Adoption and measurement
Your managers learn the system as a cohort. We re-measure maturity against the baseline, hand over, and check again after 30 days. Your team runs it without us.
Outcomes you can see
- 1A new manager takes over a project in days, not months. The context brief exists before they ask.
- 2Commitments stop getting lost. Every promise has an owner and a date, and surfaces before it burns, not when the client calls.
- 3Decisions keep their reasons. "Why did we do it this way" takes a minute to answer, not a meeting.
- 4Your AI finally has something to work with. Status drafts, summaries and briefs come out right, because the context underneath them is right.
- 5When someone leaves, their projects stay.
We won't promise revenue growth, we don't control your market. We won't promise AI replaces managers, it doesn't, and you wouldn't want the version that pretends to. We promise the context layer works, your people can run it, and we measure both.
We train your teams and managers, you implement the changes. Cohort programs on your own work.
We build the system with you and share accountability for what changes. Training is inside the engagement, your managers learn the system as it's built.
Do we need to buy new tools?+
Usually no. We build on what you own and recommend additions only where a gap is proven. We take no commissions from any vendor, so the recommendation has no agenda.
We already did a maturity assessment once.+
Good, bring it. If it's current, we skip ahead and you don't pay for it twice. The difference this time is that the roadmap ends in a built system, not a document.
How is this different from hiring an integrator?+
An integrator configures software. We decide, with you, what the software should hold: what counts as a commitment, which decisions get recorded, how a project's knowledge is structured. That's methodology, then configuration follows.
Can our team run it without you afterwards?+
That's the test of the engagement. Managers train as a cohort during the build, and we re-check 30 days after handover. If it only works while we're in the building, we haven't finished.
Where does AI governance fit?+
Accountability for AI outputs is built into every system we deliver. Where a regulator, donor or board needs more, our AI Governance Advisory covers policy, risk controls and audit readiness.
Start with the Diagnostic
Start with the Diagnostic: two weeks, fixed fee, numbers at the end. Or bring one process to a 30-minute call, we'll show you what it looks like automated, and tell you straight where AI should not be trusted. We respond within one business day.
Price: on request
Upcoming courses, workshops and webinars
Practical training from people who do the work. Pick your track, from management foundations to AI mastery.