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Foresight

AI-driven predictive project delivery platform for megaproject schedules

Cloud platform that ingests existing Primavera P6, Microsoft Project, and Excel schedules for capital-intensive megaprojects (data centers, rail, infrastructure), validates schedule logic, and applies predictive machine learning to forecast completion dates and delay risk, replacing manual quarterly business reviews with automated portfolio dashboards and stakeholder reports.

Pricing
contact the vendor
Alternatives
Hive, BIMCRONE, Asana
Who it's for
Construction, Project Management, Engineering
$25M Series A (announced March 2026), led by Macquarie Capital Venture Capital, with participation from Creandum, ISAI Build (a Bouygues-group VC fund managed by ISAI), i2bf Global Ventures, and Somersault Ventures; an earlier, undisclosed-amount seed round from Creandum closed in 2021 raisedGrowth Stage
Founded 2018 · Exact customer count not publicly disclosed. Named case-study customers/logos include RailCo, Crossrail, Compass Datacenters, Skybox Datacenters, and Ramboll; one case study references "a leading data center developer managing 15 global projects." Note: founded 2018 but did not raise a Series A until March 2026 (an undisclosed 2021 seed round from Creandum preceded it) — a long pre-Series-A runway typical of enterprise megaproject software with a slow sales cycle, not evidence of large-scale customer adoption.
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WHY IT EXISTS

Why This Tool Exists

The Problem

Owners and contractors delivering capital-intensive megaprojects (data centers, rail, large infrastructure) track schedule risk through static Primavera P6/MS Project files and manual quarterly business reviews across dozens of concurrent projects. Delay drivers and schedule-logic errors (false ties, broken links) often surface only after they have already caused cost overruns, and rebuilding portfolio-level status reports each cycle consumes significant project-controls staff time.

The Solution

Foresight connects to existing P6, MS Project, and Excel schedules, cross-references reported progress against a single source of truth, and runs predictive ML models over the schedule data to forecast completion dates, surface delay risk, and flag logic errors automatically. It generates portfolio-wide dashboards and stakeholder-ready reports without a manual rebuild each reporting cycle.

USAGE

How You Use It

Delivery Method
SaaSCloud-based Web Application
Integrations
Primavera P6Microsoft ProjectMicrosoft Excel
Disciplines
Construction
Workflows
Coordination & Delivery
Project Phases
Preconstruction, Construction Administration
Project Types
Data Center, Infrastructure, Industrial, Energy
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Existing project schedule (Primavera P6, Microsoft Project, or Excel)
Optional:Progress/status updates, Portfolio-level project list, Cost and budget data
Formats:Primavera P6, Microsoft Project, Excel
Output
What you get
Format:Executive dashboards, completion forecasts, and stakeholder-ready portfolio reports
Fields:Completion date forecast, Delay risk assessment, Schedule logic errors (false ties, blockers), Schedule quality/health analysis, Performance index and float path trends, Portfolio-wide status rollup
Algorithm
How it works
Model:Proprietary predictive machine-learning models applied to schedule data (marketed by the vendor as a "large construction model"); specific model architecture not publicly disclosed
Accuracy:Vendor claims "2x more accurate" completion forecasts than traditional bottom-up schedules; case studies cite $100M in prevented delays and a 90% cut in reporting overhead for one data center portfolio, a 3,000% faster reporting cycle and 50% better schedule quality for RailCo, and a 400% run-rate increase for Crossrail. Methodology behind these figures is not published and the claims are vendor-reported, not independently audited.
Privacy
How your data is protected
Retention:Personal data is retained "for a period of time consistent with the original purpose of collection" or as required by law; retention of project/schedule data on the platform is governed by individual customer contracts (per the published privacy policy)
Training:Not publicly specified whether customer schedule data is used to train Foresight's predictive models
Compliance:No SOC 2, ISO 27001, or other compliance certification publicly disclosed on foresight.works; the site references being "backed by security" without naming a specific certification
API
Integration
Endpoint:Contact vendor for API access (no public API documentation found)
Method:Not publicly documented
USE CASES

Use Cases

  • ·Forecasting completion dates across a portfolio of concurrent megaprojects
  • ·Detecting schedule logic errors (false ties, blockers) in Primavera P6 or MS Project schedules before they cause delays
  • ·Automating executive-level portfolio status reporting in place of manual quarterly business reviews
  • ·Identifying delay drivers early to reduce cost overruns on data center and infrastructure builds
  • ·Validating reported field progress against a single source-of-truth schedule
PRICING

Pricing

Free
No free tier publicly advertised; platform is accessed via a requested demo (foresight.works/contact)
Enterprise
Custom / contact-sales pricing for enterprise megaproject deployments; no published pricing tiers found
Sources & Research NotesResearch date: 2026-07-17
Data Sources (10)
Fields Checked (14)
problem, solution, deliveryMethod, integrations, disciplines, projectTypes, yearFounded, fundingTotal, output-fields, algorithm-approach, privacy-location, privacy-retention, useCases, customer-case-studies
Not Found (7)
api-documentation, api-auth, algorithm-accuracy-methodology, soc2-or-iso-certification, pricing-tiers, exact-customer-count, data-training-usage-policy
About this research: This record summarizes the cited sources and fields checked. A research date does not establish hands-on testing. Consult the original sources for current details and limitations.
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