Schedule smarter. Operate with less friction.
A production-ready optimization engine that turns your service requirements, employee availability and business rules into a conflict-free, cost-aware schedule — in under 5 minutes.
Scheduling is one of the most costly unsolved problems in operations.
Companies either build tools that break when the rules change, or plan by hand. Both leave money on the table.
Planning is slow and error-prone
Days lost in spreadsheets — and the result still has conflicts.
- Availability, services and rules live in separate files
- Every change means manual reconciliation
- Conflicts only surface after the schedule is published
Workload is unfairly distributed
The same people keep getting the demanding shifts.
- No systematic way to balance load
- Some staff overloaded, others underutilized
- Complaints and churn follow
Operational cost is hidden
Invisible in a spreadsheet, very real on the balance sheet.
- Idle gaps between sessions
- Avoidable overtime
- Inefficient travel routing
- Cost of last-minute changes
Rescheduling is a nightmare
One sick day means rechecking every assignment by hand.
- Every downstream assignment needs revalidation
- No way to compare scenarios
- What-if analysis is impractical
Measurable returns from day one.
Scheduling isn't a cost — it's infrastructure. Automating it recovers hours and cuts cost in ways that compound.
What used to take a planner two days now runs in minutes. Redeploy that time to higher-value work.
Fewer idle gaps, less overtime, better coverage — the optimizer finds savings invisible to manual planners.
Fair, transparent assignments distributed by algorithm — not perception. Staff trust the system when rules are visible.
Non-negotiable constraints, every run.
The solver will never violate these. No workarounds, no manual review required.
- No employee is double-booked
- Only qualified staff assigned to each service
- Employee availability windows are respected
- Unavailable periods (holidays, sick leave) are blocked
- Daily working time capped at 8 hours
- Max 6 working days in any 7-day window
- At least one full weekend off per month
Tune the optimizer to your business priorities.
Every weight is configurable. Change priorities without touching a single line of code — just re-run.
- Balance weekly hours across all staff
- Minimize overtime and undertime
- Bonus for tight consecutive session chains
- Minimize idle gaps during a shift
- Ensure fair night-shift distribution
- Configurable weights per business priority
Tweak a weight, change a constraint, add new sessions — and re-run the optimizer. No rebuilding, no reconfiguring. Results land within 5 minutes, ready for review or export.
Works for any industry with recurring service sessions.
The constraint model is domain-agnostic — the same engine adapts to your rules.
Multi-service, multi-location workforce
Dozens of client locations, staffed automatically.
- Different service types
- Varied shift patterns
- Travel constraints
Credentialed staff across specialties
Practitioners matched to patient sessions.
- Qualifications and certifications
- Availability windows
- Legal rest requirements
Large-scale shift optimization
Hundreds of employees across buildings and time zones.
- Rules per site
- Rules per contract type
- Rules per service tier
API-first scheduling engine
Embed the optimizer directly in your product over REST.
- Full async execution
- Webhook callbacks
- Reschedule endpoint
Something changed? Re-optimize without undoing what's committed.
Feed in the existing schedule and a cut-off date. Everything before it is locked; only open slots are re-optimized.
- Past assignments are never modified
- Only future open slots are re-planned
- New employee or session added mid-period? Just re-run
- Compare multiple what-if scenarios side by side
A multi-stage optimizer built on CP-SAT.
Asynchronous by design: submit a job over REST, then poll or take a webhook. No custom infrastructure on your side.
- 01
Input Collection
Everything the solver needs is loaded from your database or API.
- Sessions and service pools
- Employee availability
- Constraints and previous assignments
- 02
Baseline Assignment
CP-SAT fills as many required slots as possible within normal hours.
- All hard constraints respected
- Service qualifications matched
- 03
Multi-Stage Optimization
Your weighted priorities decide the best feasible schedule.
- Coverage and fairness
- Cost and overnight shifts
- Idle-gap penalties
- 04
Output & Delivery
The finished schedule is written to Azure Blob Storage as CSV.
- Job status endpoint
- Webhook callback
- No blocking, no timeouts
The extensibility roadmap is already planned.
Built to grow: new capabilities layer on top without code rewrites.
Cost-minimization with travel distances
Stage 2 optimization layer that routes staff to minimize logistics cost across locations.
Employee preference fairness
Add preference weights so employees can express shift preferences that the optimizer respects when possible.
Real-time micro-adjuster
React to sick-leave notifications mid-day and instantly re-optimize only the affected slots.
Dashboard-based scenario explorer
Non-technical planners can tweak weights and regenerate schedules without touching the API.
Turn scheduling into a measurable operational advantage.
We'll adapt the optimization model to your constraints and business priorities.