Anticipate the invoice.
Build expected billing before the document arrives.
Invoice Alpha is an 8-week Genesis Cohort for procurement, AP, finance and commercial leaders exploring how AI and agents can maintain the obligation continuously — across contracts, POs, delivery, performance and supplier context — so teams can detect divergence earlier, protect entitlements, prevent leakage and decide what should be paid before payment pressure takes over.
Traditional AP becomes active when an invoice arrives. But performance, acceptance, usage, credits, scope and supplier context can change what should be owed days or weeks earlier. Invoice Alpha explores what happens when agents maintain that obligation continuously instead of discovering it at the payment queue.
The cohort is built around three changes in where the work starts, what the system maintains and how payment decisions are made.
Build an expected obligation from contract terms, delivery, usage, performance and known adjustments before the supplier bills.
Separate authorized, committed, delivered, accepted, invoiced and paid value so the commercial state is understood before AP is forced to resolve it.
Pay deliberately, protect entitlements, re-scope, notify, challenge, accelerate or hold within clear authority boundaries.
Acme Corporation lets us create realistic conflicts between contracts, POs, delivery, acceptance, performance and supplier behavior — without exposing customer data.
The six experiments share suppliers, commercial history and operating context, so the agents accumulate a coherent position rather than solve isolated invoice exceptions.
Sets the starting obligation and available rights.
Creates confirmed and contested credits before billing.
What Acme currently believes should be owed.
The invoice becomes a variance event rather than the first moment of understanding.
Challenge entitlement while preserving service continuity.
The experiment sequence moves from anticipating a recurring invoice to managing the supplier’s broader commercial position.
Build expected billing before the document arrives.
Separate authorized, committed, delivered, accepted, invoiced and paid value.
Translate service performance into expected credits before billing.
Detect scope drift, spend trajectory and authorization gaps upstream.
Balance discounts, cash, disputes, due dates and supplier criticality.
Connect invoice behavior to performance, leverage and renewal strategy.
Select a week to see the session focus, optional lab, Friday artifact and the practical idea participants can take back to their own teams.
Orient around Invoice Alpha, the Acme world, the three-position model and the questions the cohort will explore together.
See the synthetic enterprise, obligation model, agent roles, authority boundaries and how the six experiments will run.
Share where invoice value is lost today, what you would delegate and which situations you most want pressure-tested.
Our team turns the live session into the next scenario, capability and evaluation changes.
Participants see the experiment. Our teams build alongside it. The week ends with a designed evidence trail rather than a webinar recap.
Frame the question, reveal the scenario, show what the agents know and run the first live working session.
Scenario logic, evidence, agent behavior and evaluation rules are refined using what the cohort surfaced.
Introduce new evidence, test a supplier response, compare alternative moves and see how the position changes.
Receive a shareable report with the position, alpha, failures, participant judgment, system changes and next experiment.
Each week leaves behind a designed evidence record. The final report synthesizes what six experiments taught us about obligation intelligence, alpha, autonomy and the emerging operating model.
Follow the managed-services experiment from performance signal to expected obligation, supplier challenge, disposition, outcome and learning review.
See the experiment map, alpha taxonomy, results, human + agent operating model, system evolution and the next questions to test.
Genesis separates synthetic experiment results from customer claims. The point is to make the evaluation model visible and build evidence about where agents help, where they fail and where humans should retain authority.
Accuracy, entitlement, prevention, timing and commercial-position value.
How much earlier a material signal becomes visible and actionable.
Evidence chasing, manual touches, exception handling and preparation.
What can be autonomous, bounded, governed or human-owned.
Monitoring, forecasting and evidence collection can run continuously.
Routine notice, challenge preparation, partial payment and bounded holds.
Settlement, waiver and strategic supplier concessions remain human-owned.
Designed for leaders who want to understand where AI and agents can genuinely improve buy-side obligation management — and where commercial judgment still matters.
Tell us your role and the invoice or obligation problems you want to explore.
Selected applicants are invited to a short conversation about fit and relevant context.
Commercial terms and cohort details are shared before participation is confirmed.