Constraint-safe
Practical AI
Explainable

AI Assists that make schedules better.

Use AI where it’s strongest: predicting, detecting, explaining, and recommending. Keep the schedule engine deterministic so every plan stays feasible.

AI Shadow Logging

See what AI would recommend — safely, transparently, and without changing your schedule.

📦

Clear change history

Every AI output is recorded as a traceable event: what it suggested, when, and why.

Reviewable history
🛡️

Production-safe by default

Built to run in real factories: predictable performance, sensible limits, and safe data handling.

  • Designed to stay lightweight
  • Captures only what’s needed for monitoring
  • Helps validate AI before rollout
⚙️

AI suggestions won’t auto-change plans

You stay in control. AI assists generate recommendations and explanations — planners decide what to apply.

No behavioral change

Live monitoring + export

  • Watch AI events in real time (helpful during pilots and incident response)
  • Export recent events for troubleshooting and internal review

Replayable history

  • Keep a consistent, ordered stream of AI events
  • Resume where you left off (useful for dashboards and monitoring)
  • Compare results across versions during controlled rollouts

Security + tenant correctness

  • Admin-only access to shadow logs and monitoring
  • Strict tenant isolation (each customer only sees their own events)
  • Designed to avoid accidental cross-tenant leakage

What this enables

  • Safer AI pilots (measure value before turning anything on)
  • Faster debugging when results look “off”
  • Clear governance for audits and internal approvals

Why Choose AI Assists

AI that improves schedules—without breaking your constraints

Constraint-safe by design

AI suggests options; the optimizer enforces capacity, materials, skills, and due dates.

Always feasible
⏱️

Better durations & setups

Deterministic estimation of processing and setup times, with uncertainty (P50 / P90) and a confidence signal based on your own history.

P50
P90
Confidence

Faster disruption recovery

When reality changes, get ranked recovery moves with impact and tradeoffs.

Minutes, not hours
🔮

What-if scenario ranking

Deterministic Monte Carlo what-if: simulate uncertainty with a fixed seed and get KPI ranges (P50 / P90) — not just a single number.

Fixed seed
KPI distributions
P50 / P90
🧹

Data quality guardrails

Pre-solve quality gates catch broken inputs early (blocking issues vs warnings) so you don’t waste planning time or ship misleading schedules.

Bill of Materials
Routings
Calendars
🔁

Learned changeovers

Infer sequence-dependent setup times from your history (A→B differs from B→A) and generate a ready-to-use changeover matrix with P50 / P90 and confidence.

A→B ≠ B→A
Matrix
P50 / P90
🧩

Schedule-ready enrichment

Turn “raw inputs” into schedule-ready inputs consistently: apply improved times, merge inferred changeovers, and return clean deltas — with opt-in rollout before re-planning.

Opt-in, backward compatible
💬

Explanations & reporting

Answer “why is this late?” and generate shift notes and exception summaries.

Traceable

Built for real production teams: consistent results, clear explanations, and no black-box surprises.

Same input = same output
Clear time ranges (P50/P90)
Respects your constraints
Runs in your stack

Deterministic Scheduling AI

A safer way to use AI: consistent results you can review and trust

🔁

Online learning loop

Continuously learn from planned vs actual to improve quantiles and changeovers per plant/line/shift — week over week.

🧠

Context-aware quantiles

More accurate durations using explainable features (family, quantity buckets, shift, skill, machine state) via robust deterministic quantiles.

🚀

Warm-start solving

Generate a strong initial feasible plan (dispatching + inferred setups) and feed it as an incumbent to CP-SAT/MIP for faster convergence.

🧩

Constraint learning

Detect implicit rules from history (no-mix, clean-to-dirty, min waits, batching) and propose them as soft constraints before promoting to hard.

📉

Reliability-aware risk

Calibrate variance and downtime per resource (MTBF/MTTR + calendars) and output probability of meeting due dates per order.

🧭

Multi-scenario autopilot

Automatically sweep bounded scenarios (P50 vs P90, weights, frozen horizon, overtime policies) and rank them by KPI tradeoffs—so planners can choose with confidence.

🧑‍🏭

Planner feedback loop

Learn from planner edits (locks, overrides, resequencing) to capture intent and reduce manual interventions over time.

🧾

Decision trace + repair

Explain “why here?” per operation (binding constraints + objective impact) and offer safe auto-repair for common data issues instead of hard failures.

Data & ERP Integration

AI assists learn from your plan-vs-actual signals. PlanQuill connects to your ERP/MES and keeps schedules synchronized.

🗄

SAP

Native integration with SAP ECC and S/4HANA

Connected
🌐

Oracle

Oracle ERP Cloud and E-Business Suite

Active
💻

Microsoft

Dynamics 365 Business Central

Synced
🔗

Custom

REST API for custom integrations

API Ready
Real-time sync
Data integrity
Zero downtime
Free demo
Fast response
Expert support

See AI assists on your production data

We start with one line or one planning area and prove measurable impact in weeks.

Trusted by industry leaders worldwide

several clients
98% satisfaction
Global reach