In large-scale renewable energy projects, delays can lead to millions in lost value and penalties. We recently partnered with a solar and wind EPC firm to solve a key challenge: How can we identify project risks early and improve execution timelines without adding overhead?
In project timeline deviations
AI-generated risk flags across ongoing projects, reviewed weekly by PMs
This was made possible by combining real-time project data, GenAI-driven alerts, and structured reviews from the project team.
We connected multiple systems: SAP project schedules, procurement systems, site updates, and vendor delivery trackers.
We deployed a suite of Project Intelligence Agents with weekly PMO review processes to prioritize actions.
We built comprehensive dashboards and action engines with human-in-the-loop approval processes.
| Agent Type | Role |
|---|---|
| Data Integration Agent | Unified schedules, vendor, and site reporting |
| Delay Pattern Agent | Flagged early risks based on historical delay profiles |
| Resource Allocation Agent | Highlighted labor/material shortages by task |
| Milestone Alert Agent | Live tracking of plan vs. actual, triggering early flags |
| Insight Agent | Curated weekly project risk digests for PMO |
PMOs moved from reactive reporting to proactive risk management
Engineers and site managers had real-time visibility on project blockers
The leadership team gained cross-project summaries with human-vetted AI insights
ZapSight enabled a shift from managing delays to preventing them. In the capital-intensive renewables sector, AI-driven foresight paired with expert judgment helped ensure delivery on time and under budget.
Transform your project management from reactive to proactive with AI-driven risk detection and human expertise.