Forsight Engine learns from your firm's historical project data to significantly improve cost and schedule prediction accuracy.
Whether you're a specialty contractor or a large GC, overruns consume profit
With net margins of 4-7% and typical overruns far exceeding that, a single mis-estimated project can eliminate an entire year's profit. Many contractors operate at breakeven when they should be highly profitable.
Estimated annual losses for a $25M revenue contractor:
Estimated annual losses for a $250M revenue GC:
Estimated annual losses for a $1B revenue firm:
Firm-specific intelligence trained on your historical project data
Your completed projects train a custom AI model that understands your CSI codes, cost structures, and systematic biases. Not a generic tool—your preconstruction team, amplified.
Receive P50, P80, and P90 confidence intervals—not just a single number. Understand the most likely, conservative, and contingency scenarios before you submit your bid.
"Your firm underestimates electrical switchgear by 22%." FSE identifies which line items you systematically mis-estimate based on actual project outcomes.
Every estimate includes 2-5 similar completed projects from your own backlog. Ground predictions in actual outcomes from comparable scopes.
As projects reach substantial completion, FSE retrains on actuals. Your model compounds institutional knowledge with every closeout.
Analyze PM reports and OAC meeting notes for early warning signs. Flag at-risk projects 2-4 weeks earlier than traditional EVM methods.
Machine learning provides high-quality baseline estimates by analyzing patterns across thousands of data points simultaneously. Unlike human estimators, ML models avoid unspoken biases—the optimism that creeps into familiar scopes, the anchoring to recent bids, the institutional blind spots that compound over years. Forsight Engine delivers estimates grounded purely in historical outcomes, not gut feel.
Peer-reviewed studies demonstrate ML outperforms traditional estimation
Mean Absolute Percentage Error (MAPE) — lower is better
Industry-standard accuracy expectations by project definition level:
Even with near-complete project definition, traditional methods achieve ±10-15% accuracy. FSE delivers <5% accuracy at earlier project stages.
Forsight Engine is the foundation—here's what comes next
Real-Time Project Intelligence & Manager Accountability
An AI system that continuously analyzes project manager updates, daily logs, and weekly summaries to deliver real-time cost and schedule forecasts directly to leadership.
Automatic estimate-at-completion recalculations based on reported progress, change orders, and emerging risks
Measures reporting patterns over time—does the PM surface issues immediately or minimize problems until they escalate? Leadership gains insight into which managers provide reliable early warnings
Portfolio-wide visibility into project health, with AI-prioritized attention flags and trend analysis across all active jobs
Bespoke Technology Consolidation
A custom-engineered solution that consolidates your fragmented technology stack into a single, coherent system—eliminating data silos, redundant workflows, and integration headaches.
Connects Procore, Sage, Viewpoint, P6, and your custom tools into a unified intelligence layer
Agentic development approach—automating workflows, routing decisions, and issue resolution where AI adds measurable value
Every implementation is architected around your specific systems, processes, and operational requirements—not a one-size-fits-all product
See what Forsight Engine can deliver with your historical project data.