About OntaBuild
We’re building an AI‑first platform that delivers predictive certainty— forecasting cost, schedule, and risk before a shovel hits the ground.
Forecastable outcomes
Evidence‑based cost & time windows
Explainable AI
Drivers, priors, and confidence
Aligned incentives
Contracts & workflows that match forecasts
Continuous learning
Every project improves the next
Mission
To replace guesswork in construction with explainable, probabilistic forecasts and data‑defined workflows that align Owners, GCs, Designers, and Subcontractors.
Predictive Certainty
Reference Class Forecasting + causal features produce cost & time windows with confidence bands.
Operational Control
Control Tower orchestrates scope, logistics, contracts, and constraints across teams.
Continuous Learning
Every project feeds the models; provenance, drift, and feedback are tracked by design.
Origin Story
OntaBuild was founded by a builder, a scientist and a software developer who saw the same pattern again and again: budgets and schedules set by optimism and convention rather than evidence. We started with an epistemic question—why does construction fail in the face of innovation and intellectual talent?—and built a stack that turns knowledge structures into delivery systems.
- 20+ years of vertical construction experience embedded into the model design.
- Research‑backed approach: reference classes, unpacking, and bias mitigation.
- Platform services that meet teams where they work—field to boardroom.
Timeline
- Year 0
Research
Studied failure patterns; formalized domain ontology.
- Years 1+2
Prototype
Reference classes + pilot datasets; first accuracy wins.
- Years 3+4
Platform
Control Tower, Data Fabric, and assurance features.
- Next
Scale
Portfolio learning across owners, GCs, and public sector.
Operating Principles
Epistemology → Ontology
Define knowledge first. Formalize the domain. Then automate delivery with agents.
Explainability
Show drivers, priors, and confidence. Decisions should be auditable and defensible.
Alignment by Design
Incentives, contracts, and data access designed to align all stakeholders.
Human‑in‑the‑Loop
AI accelerates expertise; it doesn’t replace it. We keep the practitioner in control.
Security & Governance
Role‑based access, provenance tracking, and compliance for enterprise & DoD.
Outcomes over Outputs
We measure certainty windows, variance reduction, and portfolio‑level learning.
Method
From Knowledge to Control
- 1
Unpack
Structure drawings, narratives, and history; unify taxonomies for cost & time.
- 2
Model
Build reference classes, causal features, and priors for asset types.
- 3
Forecast
Generate distributions; expose drivers and assumptions.
- 4
Decide
Operationalize into contracts, procurement windows, and logistics strategies.
- 5
Learn
Close loop with actuals; detect drift; improve models and playbooks.
Platform Stack
- Forecasting Engine Probabilistic cost & schedule with confidence bands.
- Control Tower Orchestrate scope, risk, and logistics across teams.
- Data Fabric Ingest, normalize, govern; maintain provenance and lineage.
- Assurance Security, auditability, explainability for enterprise & DoD.
Team
Builder, scientist, and software developer with experience across federal, healthcare, industrial, and commercial programs.
Founder / CEO
Bio placeholder
20+ years building complex programs; platform strategy and partnerships.
Head of Data Science
Bio placeholder
Reference classes, Bayesian modeling, and explainability.
Head of Software
Bio placeholder
Control Tower & field data workflows from precon to handover.
Security & Compliance
- Role‑based access, audit logs, and signed data lineage.
- Alignment with public‑sector procurement and program controls.
Measurement
Variance Reduction
Δ vs baseline
Confidence Coverage
P50/P80 hit rate
Change‑Order Risk
Likelihood index
Cycle Time
Throughput gain
Join Us
If replacing guesswork with predictive certainty sounds like your kind of challenge, we’d love to talk.