Tacitum info@tacitum.ai

Timing is everything…

…in strategy, organization, and work, particularly temporary endeavors: the adaptive projects that deliver your strategic intent in an increasingly uncertain environment. Yet the rules that run the clocks are rarely written down. Tacitum makes them explicit, then lets AI agents run your project portfolio within them. People keep the authority to decide. Agents do the work of keeping everything in step.

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Illustrative values. Benefit grows as outputs are acted on, less when they have waited. Risk is the value still waiting.
Outputs flowing down as inputsOutputs flowing up as inputsEscalation, skipping tiers and handled off-cycleNow
Each tier of a portfolio runs on its own clock, faster at the project level and slower toward strategy. Every time a tier fires, its outputs become inputs to the practices on the tiers above and below it, which can act on them only at their own next cycle. Escalations are the exception: they skip tiers and are handled off-cycle. Where the clocks fail to line up, decisions wait, and portfolios lose time and money, and sometimes cost lives.

Most portfolio failures are failures of timing

A decision arrives after the window it was meant for. A program waits on a project that is waiting on a budget review. Every forum keeps its own calendar, and nobody owns how those calendars fit together.

The rules that would fix this already exist in your organization. They live in habits and in the heads of experienced people, which is why they break when those people are busy or gone. As AI agents take on more of the work, the gap widens, because an agent that does not know the rules acts on its own clock.

Before an agent can be trusted with a portfolio

Three things have to be true.

  • It knows the organization's actual rules: which forums decide what, on which cycle, and what triggers an escalation.
  • It acts only within authority that a named person holds, on the record.
  • Every change to a rule is proposed, approved by a person, and logged, so the system can be audited after the fact.

Few organizations meet the first condition, because the rules were never written down. That is where Tacitum starts.

How Tacitum works

  1. Assess

    A guided self-assessment captures how your portfolio is actually governed: which forums meet, how often, what triggers an escalation, and who decides.

  2. Register

    Tacitum turns the answers into a machine-readable register of rules for cadence, thresholds, and synchronization. Every rule is visible, versioned, and owned by a named person.

  3. Operate

    An AI agent for each portfolio practice, from prioritizing to controlling, proposes and carries out work. A synchronizing core checks every action against the register. That core is deterministic code, not a language model, so the rules hold even when a model errs.

Agents can propose. Only people ratify.

An AI system cannot grant itself authority over when decisions get made. Someone has to hold that authority, on the record, and answer for it. Tacitum is built around that requirement, and it is what makes an agentic portfolio governable.

Built to run where the data lives

Portfolio data is among the most sensitive information an organization holds: budgets, priorities, and decisions not yet announced. Many organizations will not send it to an outside model provider.

Tacitum's agents are being built on open models served on NVIDIA accelerated computing, so they can run inside a customer's own cloud or data center. The workload is inference-heavy. Every agent decision is a model call, and validating the system means hundreds of simulated runs, each requiring thousands of agent decisions, before it touches a real portfolio.

Where Tacitum stands

  • The engine is already built upon institutional standards that govern a multi-trillion-dollar economy of temporary endeavors, standards our co-founder John Schlichter originated and that have been adopted globally for decades.
  • The self-assessment is live and in use with a multinational manufacturer.
  • The governance core is being tested in a simulated portfolio, under an evaluation design registered in advance.
  • The agent layer is in development for 2027.
  • The research behind it is being prepared for peer-reviewed journals in information systems.

Who is behind it

  • John Schlichter John SchlichterCo-founder

    Agents can only keep rules that someone defined. John led the international team of about 800 practitioners in 35 countries that wrote the global standard for organizational project management and project portfolio management, later republished by ISO. His doctoral research at Trinity College Dublin examined how portfolio management becomes a dynamic capability, one that adapts as conditions change. For over two decades he has worked inside the portfolios of global organizations, and he has taught portfolio management at Emory University's Goizueta Business School.

  • Maura Clark Maura ClarkCo-founder

    Running agents inside a customer's own data center, and proving afterward what each agent did, are infrastructure problems. Maura has spent more than 14 years in telecom and data center networking, most recently helping enterprises, cloud providers, and critical infrastructure operators connect AI workloads. She authored UOR-ADDR, an open standard for addressing and verifying AI agent content adopted by the UOR Foundation, and contributed to its Rust reference implementation. She holds certifications in AI infrastructure from NVIDIA and IBM.

  • Scott Darden Scott DardenCo-founder

    Timing failures cost most where many organizations must act in step across borders. For over two decades, Scott has led supply chain and logistics programs across Europe, Africa, and the Middle East, including defense procurement and logistics, enterprise logistics for U.S. government programs, and client program direction at Maersk. For many years, he has also founded startup businesses in Dubai. He knows what it takes for a rule to hold when the work is spread across continents, contractors, and suppliers.

Strategic Advisor

  • Benn Konsynski Benn Konsynski

    Benn Konsynski is the George S. Craft Professor of Information Systems and Operations Management at Emory University’s Goizueta Business School, and he previously held faculty appointments at Harvard Business School and the University of Arizona. His research centers on decision support systems and on information systems that coordinate work across organizational boundaries, two foundations of Tacitum’s governed agents for portfolio decisions. He has served on the boards of several technology companies, and he holds a PhD in computer science from Purdue University.

Test it on a real portfolio

We are looking for a small number of PMO and portfolio leaders who want to see how their portfolio keeps time. Write to info@tacitum.ai to take part.