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Cross-Client Project Management

Optimize the overall success of your client engagements with a portfolio view of project management

  • Eliminate process and data gaps across clients from bid to invoice with a single view of all projects
  • Leverage the power of machine learning to proactively manage the health of all of your projects simultaneously under the constraints of the available skills and capacities
  • Reduce the burden of manual re-planning since AI continuously suggests project management improvements across your project portfolio

AI-driven margin optimization from the single source of truth

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Cross-Client Engagement Management

Eliminate process and data gaps from bid to invoice with a single view of all projects

  • Integrate with existing project and resource management tools to consolidate data into a single UI for all projects from bid requests to invoices
  • Manage your consulting engagements with industry-specific solutions for project management, project estimations, scheduling and revenue collection
  • Reduce the effort of manually adjusting plans across multiple clients by using an AI-driven project management platform that is designed for the unique needs of the consulting industry

Cross-Client Project Optimization

Leverage the power of machine learning to proactively manage the health of all of your projects simultaneously under the constraints of the available skills and capacities

  • Easily identify the impact of changes in one project on other engagements
  • Quickly develop options for reallocating skills and capacities to meet project timelines or improve margins with recommendations from the platform
  • Tune skills, availability, rates and cost data to maximize overall performance across your projects
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AI-Powered Project Insights

AI continuously suggests optimization across your project portfolio and reduces the burden of manual project management

  • More accurately estimate required project budgets and durations by gaining insight from historic data
  • Avoid losses due to discrepancies between planned and actual efforts, revenues or costs
  • Predict project risks by identifying patterns in the evolution of project data over time
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