A Feasible Shift-Wise Plan, In Minutes Instead of Hours
An AI resource-planning pipeline that helps supervisors build the daily, shift-wise production plan — respecting every hard constraint and pausing for human approval at defined checkpoints.
A manual decision made fresh, every day, across three shifts
Every day a production supervisor decides who works where, making what and how much, across shifts A, B and C. The decision depends on customer work orders, raw-material inventory, which operators showed up, their skills, which machines are running, and quality or tooling holds. Today this is largely manual, slow, and hard to explain or repeat.
Want a Shift-Wise Plan Built Around Your Own Constraints?
We'll scope a pilot around your exact work orders, materials, attendance and machine data — with hard-constraint feasibility and clear success metrics before any production commitment.
An agentic planning system that treats every input as a hard constraint
It proposes a complete shift-wise plan the supervisor can review, adjust and approve — explaining its reasoning, flagging exceptions (shortages, breakdowns, absences), and pausing for human approval at defined checkpoints.
Work orders and demand
From ERP or CSV/Excel — plans today's target per order, finishing days before the due date.
Inventory and materials
Never plans more than material on hand, and flags shortages.
Workers and attendance
Only present operators are assigned, via face-recognition attendance.
Skills
Operators only go to machines they're qualified on, per skill matrix L1-L4.
Machines
Broken or maintenance-window machines are excluded, via IoT status.
Tooling, quality holds, shift calendar
Held material and unavailable tools are not planned.
How it works
A clear split of responsibilities: the optimiser (mathematical optimisation, MILP) does arithmetic and feasibility — capacity, staffing, material, skills — and gives the same answer every time. AI agents (Claude) do judgment and communication — choosing options to try, explaining trade-offs, briefings and Q&A. The production supervisor makes the final decision; low-risk plans can release on their own. The AI never sets quantities or assignments — it only chooses from a fixed menu of options and recommends among plans the optimiser has already proven feasible. Every final plan is re-checked against hard rules by independent code, with deterministic fallbacks if the AI service is unavailable.
The daily flow
- 1Collect and freeze data into one snapshot
- 2Check and diagnose gaps between demand and capacity
- 3Solve variants (overtime, cross-skilled operators)
- 4AI agents recommend and explain trade-offs
- 5Human checkpoints for review, edit and approval
- 6After the shift, actual output is recorded and any shortfall carries into the next day's targets
What the supervisor gets
- A feasible shift-wise plan in minutes instead of hours
- Plain-language explanations
- Early warnings with re-plan suggestions
- One web interface for orders, materials, attendance, machines, planning and end-of-day actuals
Trust and safety
An append-only, hash-chained audit log of inputs, decisions, approvals and reasons; every AI call and plan step traced; the same snapshot always reproduces the same plan.
Status: done on a demo plant — end-to-end planning pipeline, optimiser, AI agents with fallbacks, audit log, material workflow, pace advisor and web UI. Next: connect live ERP, attendance and IoT feeds; validate against historical days; pilot with supervisors at one plant.
An engineering team that ships deterministic, auditable systems, not slide decks
AWS Advanced Tier Partner
Certified cloud and AI delivery, so your planning system runs on infrastructure built to AWS Well-Architected standards from day one.
Pilot-first engagement
We scope, build and validate against real plant data before you commit to a production rollout — exactly like Sandhar's demo-plant build.
A hash-chained, append-only audit log
Every input, decision, approval and reason is logged, with every AI call and plan step traced for review.
Deterministic fallbacks, always
The AI never sets quantities or assignments on its own — every final plan is re-checked against hard rules, with deterministic fallbacks if the AI service is unavailable.
Trusted by forward-thinking teams
AWS-Certified Experts Delivering Cloud Excellence.
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View All AI SolutionsWant a Shift-Wise Plan Your
Supervisors Can Trust?
Tell us about your production constraints — we'll help you scope an agentic planning pilot with MILP feasibility checks and human approval checkpoints.