Reduced Project Delays: By identifying risks early and taking proactive measures, the company was able to reduce project delays by 30%, keeping critical infrastructure projects on schedule.

Improved Safety Compliance: Real-time monitoring of safety data allowed the company to address compliance issues before they became critical, reducing safety incidents by 20% across multiple project sites.

Increased Project Success Rate: By continuously monitoring and mitigating risks, the company improved its project success rate by 25%, ensuring timely delivery and client satisfaction.

The Challenge

Large-scale construction and infrastructure projects involve coordination across multiple teams, contractors, systems, and locations.

Project data is often distributed across scheduling platforms, financial systems, field reports, safety logs, and operational tools. Teams work with fragmented information, making it difficult to maintain a real-time understanding of project risks and overall performance.

This creates ongoing operational challenges:

  • Limited visibility into project risks across systems and teams
  • Delayed identification of budget overruns and schedule issues
  • Difficulty tracking resource allocation and field performance
  • Inconsistent monitoring of compliance and safety activity
  • Manual coordination required to assess and respond to risks

Without a unified operational view, project issues can escalate before teams are able to take corrective action, leading to delays, increased costs, and disruptions across the project lifecycle.


The Syntes AI Solution

Syntes AI provides a unified operational intelligence layer for construction project management and risk oversight.

The platform connects project schedules, budgets, resource plans, field activity, safety reports, and operational systems into a live knowledge graph that continuously reflects project conditions and dependencies.

AI agents operate across this environment to monitor project activity, identify emerging risks, and support operational coordination across teams and systems.

The system enables project managers and risk teams to maintain a continuously updated understanding of project performance and operational exposure.


How It Works

  1. Unified Project and Risk Context
    Project management systems, financial tools, performance metrics, and safety data are connected into a single operational model.
  2. Continuous Operational Memory
    Historical project activity, delays, budget trends, safety incidents, and mitigation actions are retained and linked over time to support forecasting and analysis.
  3. Agent-Supported Risk Monitoring and Mitigation
    AI agents assist teams by:
    • Monitoring project data for early warning signs of risk
    • Identifying budget deviations and schedule delays
    • Tracking resource allocation and operational dependencies
    • Highlighting compliance and safety concerns
    • Supporting mitigation planning and operational coordination

Each workflow is supported by continuously updated project context and operational data.


Key Capabilities

  1. Comprehensive Project Data Integration
    Connects project schedules, budgets, field activity, performance metrics, and safety reports into a unified operational view.
  2. Real-Time Risk Detection
    Monitors project activity continuously to identify emerging risks related to cost, schedules, resources, and compliance.
  3. AI-Driven Risk Mitigation Support
    Provides recommendations and operational visibility to support proactive response planning.
  4. Customizable Operational Dashboards
    Enables teams to visualize project performance, timelines, risks, and operational metrics in real time.
  5. Cross-System Coordination
    Aligns data and workflows across project management, financial, and operational systems.
  6. Audit and Traceability
    Maintains a complete history of project activity, risks, decisions, and mitigation actions.

Implementation Approach

  1. Data Integration
    Use Syntes AI’s connectors to integrate project management systems, financial tools, field reporting platforms, and operational data sources into a unified environment.
  2. Risk Monitoring and Analysis
    Apply AI-driven analytics and operational monitoring to identify emerging risks related to budgets, schedules, safety, and resource allocation.
  3. Operational Coordination and Mitigation
    Support project teams with visibility into risks, recommended actions, and coordinated workflows for mitigation and oversight.
  4. Continuous Project Oversight
    Track project performance and operational metrics in real time, enabling teams to respond quickly as conditions change.

The Outcome

Construction organizations gain a more connected and proactive approach to project oversight and risk management.

  • Project risks are identified earlier
  • Visibility into budgets and schedules improves
  • Operational coordination becomes more efficient
  • Teams respond faster to emerging issues
  • Manual reconciliation and reporting efforts are reduced
  • Compliance and safety oversight become easier to manage

The result is a construction project environment supported by continuously updated operational context, real-time visibility, and coordinated risk management workflows.

DataRobot has been instrumental as we work through our generative and predictive AI use cases. With DataRobot’s LLM operations (LLMOps) capabilities and out-of-the-box LLM performance monitoring, we’re equipped to implement cutting-edge generative AI techniques into our business while monitoring for toxicity, truthfulness and cost.

Frederique De Letter

Senior Director Business Insights & Analytics, Keller Williams

A complete AI lifecycle platform is invaluable in optimizing the effectiveness and efficiency of our growing data science team. The DataRobot AI Platform provides full flexibility to integrate within our current ecosystem, including pulling data directly from Microsoft Azure to save time and reduce risk, and providing insights through Microsoft Power BI. This flexibility drew us to DataRobot, and we look forward to leveraging the integration with Azure OpenAI to continue to drive innovation.

Craig Civil

Director of Data Science & AI

The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards. We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence

Rosalia Tungaraza

Ph.D, AVP, Artificial Intelligence, Baptist Health

DataRobot is an indispensable partner helping us maintain our reputation both internally and externally by deploying, monitoring, and governing generative AI responsibly and effectively.

Tom Thomas

Vice President of Data & Analytics, FordDirect