01
Execution risk
The project fails before the dashboard admits it.
Risk propagates through dependencies, interfaces and handoffs while the enterprise sees disconnected schedule, cost, contract and partner fragments.
Outcome pattern>90% of major capital projects miss cost or schedule targets.
Annual loss$1.6T in estimated annual value lost to low construction productivity.
Missing layerOne authoritative project state for governed action.
Current tools record fragments. Cybereum computes the project as a system.
02
Operating model
AI needs a living model of the project before it can govern action.
Operational contextPhases, packages, systems, owners and external participants normalized into one project state.
Forecasting & riskDelay propagation, criticality, uncertainty and milestone exposure computed continuously.
Reasoning layerCauses, recovery options and intervention leverage evaluated against the live graph.
Governed actionRanked mitigations, ownership, decisions and auditable follow-through.
Project model → computation → reasoning → coordinated delivery.
03
Hyperscale data centers
Capacity readiness is the real delivery state.
The control surface runs from power and utilities through civil, MEP, IT fit-out, long-lead equipment, commissioning, acceptance and partner delivery.
RFS forecastingKnow the real power-on date using P50/P80 forecast exposure—not baseline fiction.
Long-lead equipmentTransformer or switchgear slip becomes milestone exposure immediately.
Commissioning gatesIST, punch-list risk, acceptance evidence and handover actions stay tied to schedule logic.
From procurement to power-on.
04
Platform architecture
The project graph becomes the operating backbone for delivery.
Connected project modelOntology · normalization · temporal knowledge graph
Project network intelligencePaths · interfaces · delay propagation · bottlenecks
Prediction + simulationProbabilistic forecasting · ML · risk simulation
Reasoning + guidanceAI grounded in live project graph + analytical outputs
Schedule · cost · change · contracts · risks · readiness · partner obligations.
05
Commercial wedge
Start with one schedule. Return a recovery decision.
A bounded first engagement proves value before production integration: one schedule package, one delivery question, one governed recovery view.
IngestP6 XER / MSP plus selected cost, change, risk or issue data.
DiagnoseSchedule quality, critical paths, near-critical paths and interface exposure.
ForecastRisk-adjusted dates, causal pathways and emerging milestone exposure.
GovernRank mitigations, assign ownership and show likely milestone effect.
Low-friction entry → execution intelligence → continuous governance layer.
06
Product evidence
The operating model is already visible in the product.
DiagnoseCritical, near-critical and structurally important paths—not just the single longest path.
ForecastP50/P80 dates, scenario exposure and leading indicators.
GovernMitigations, ownership, decisions and follow-through remain traceable to project state.
Works with the data and systems that already exist.
07
Team
Project operators. Technology builders. Institutional advisors.
Megaproject delivery, enterprise software, AI architecture and senior advisory coverage across government, AEC technology, commercialization and deep-tech GTM.
Ananth NatarajanFounder & CEO
RB
Reilly BrownProduct
AA
Alex AzarhArchitecture & AI
Christopher CassOperations
Christopher StelterMarketing & Sales
Strategic advisors
Patrick SuermannTexas A&M · construction technology · former dean · USAF
Rick RundellAutodesk · AEC technology and industry innovation
Justina GallegosFormer White House OSTP · commercialization
Ben BattatDeep-tech companies · GTM and fundraising strategy
08
Investor thesis
The wedge can become the multi-party governance platform for capital delivery.
Execution intelligenceLand with one schedule and one high-value delivery question.
Operating layerExpand across schedule, cost, risk, readiness, decisions and corrective action.
Multi-party governanceOwners, EPCs, suppliers, financiers, regulators and agents coordinate against shared state.
Execution ecosystemApplications, agents and transactional workflows compound value across participants.
As participation broadens, multi-sided platform economics can emerge around the shared execution model.