decídalo V3 is here! Skills and CV management with GPT-4. Find out more here!
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
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
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