Smart Operations — Solution
Resource Allocation Optimizer
Stop over-allocating your best people. Our ML engine balances skills, availability, and strategic priorities across every project in your portfolio — in real time.
Capabilities & Technology
Key Capabilities
Multi-constraint workforce optimisation
Skill-gap identification and training recommendations
What-if scenario modelling
Utilisation heatmaps per team
Automated bench management
Technologies
System Architecture
Our hybrid ecosystem integrates seamlessly with your existing infrastructure, providing AI-powered insights secured by blockchain transparency.
Data Sources
Legacy systems, APIs, databases
AI Processing
Machine learning models, predictions
Blockchain Layer
Immutable audit trail, smart contracts
Analytics Engine
Real-time metrics, dashboards
Cloud Infrastructure
Scalable, secure deployment
Automated Workflows
Process automation, integrations
Case Study
Optimising 200+ Engineers Across a Systems Integrator
Executive Summary
A regional systems integrator with 200 engineers across 40 concurrent projects reduced bench time by 28% and improved billable utilisation from 64% to 81% after deploying the Resource Allocation Optimizer.
Think — Constraint-Satisfaction Engine
The AI layer models each engineer's skills, certifications, location, and leave calendar as a constraint-satisfaction problem. Google OR-Tools solves the multi-objective function (maximise utilisation, minimise travel, respect skill requirements) within seconds, surfacing the top three allocation plans.
Honesty — Transparent Allocation Audit
Every allocation decision, override, and escalation is logged to an append-only ledger. Managers can trace exactly why a particular engineer was assigned to a project, preventing favouritism disputes and ensuring compliance with labour regulations.
Operational Metrics
Performance Comparison
See how our hybrid AI + blockchain solution compares to traditional approaches across key operational metrics.
| Metric | Traditional | Hybrid Ecosystem |
|---|---|---|
| Billable Utilisation | 64% | 81% |
| Bench Time | 22% | 8% |
| Allocation Decision Time | 3 days | < 30 sec |
Technical Stack
2026 Roadmap
Q2 2026: Add contractor and freelancer pool optimisation. Q3 2026: Predictive attrition alerts. Q4 2026: Integration with Workday and BambooHR.
“The optimizer paid for itself in the first month. We recaptured nearly 200 billable hours that were previously lost to manual scheduling.”
— Peter Kamau, COO at Savannah Systems