Optimize your MOCO schedules with Artificial Intelligence
Swiftask analyzes your projects in MOCO to generate optimized schedules. Assign resources with precision and anticipate overloads.
Result:
Maximize project profitability while reducing time spent on administrative scheduling.
AI Agents
moco
Connector moco · Secure OAuth 2.0
The complexity of manual scheduling in MOCO
Managing availability and skills in MOCO takes valuable time. Manual adjustments often lead to allocation errors and unexpected bottlenecks.
Main negative impacts:
Resource underutilization
Poor visibility into real workloads prevents balanced distribution, directly impacting your operational margin.
Unexpected overloads
Lack of predictive analysis leads to overwhelmed teams, increasing the risk of project delays.
Administrative time drain
Re-adjusting schedules in MOCO every week is a time-consuming task that distracts managers from strategic missions.
Swiftask synchronizes with MOCO to automate resource recommendations based on skills, deadlines, and real workloads.
BEFORE / AFTER
What changes with Swiftask
Traditional manual management
The project manager spends hours cross-referencing MOCO timesheets with team availability in a third-party tool. The plan is outdated as soon as it's published.
Swiftask augmented planning
Swiftask reads your MOCO projects in real time. The AI proposes optimal allocation, adjusts schedules based on absences, and updates assignments instantly.
Deploy your optimization in 4 steps
1
STEP 1 : Link your MOCO instance
Connect Swiftask to your MOCO account via API to import project data and resource availability.
2
STEP 2 : Define your constraints
Tell the agent your priorities: deadlines, specific skills, or workload balancing.
3
STEP 3 : Generate proposals
The AI agent analyzes the data and suggests the best assignments for your ongoing projects.
4
STEP 4 : Validate and sync
Validate suggestions with one click to automatically update your schedule in MOCO.
Advanced scheduling features
Analysis of skills, timesheets, and remaining capacities of collaborators.
- Target connector: The agent performs the right actions in moco based on event context.
- Automated actions: Automatic resource recommendation, schedule conflict detection, dynamic adjustment based on unforeseen events, data export to MOCO.
- Native governance: All changes are logged, allowing for post-project analysis of your planning accuracy.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-moco@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Operational benefits
Improved project margin
Optimized allocation avoids downtime and underutilized resources.
Increased reactivity
Adapt your schedule in seconds following a change in client priorities.
Better talent retention
A balanced workload reduces stress and improves team well-being.
Predictive precision
Anticipate recruitment needs thanks to the long-term visibility provided by the AI.
Seamless integration
Work directly in your usual ecosystem without changing your methodology.
Security and confidentiality
Swiftask applies enterprise-grade security standards for your moco automations.
- Secure API connection: Use of restricted access tokens to communicate with your MOCO instance.
- Data isolation: Your company data is never used to train global models.
- GDPR compliance: Hosting and processing compliant with European data protection standards.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your performance
| Metric | Before | After |
|---|---|---|
| Scheduling time | 4-6 hours / week | Less than 30 minutes |
| Utilization rate | Variable and imprecise | Optimized by +15% |
| Scheduling conflicts | Frequent | Detected and resolved proactively |
Take action with moco
Maximize project profitability while reducing time spent on administrative scheduling.