AI demand planning that zero implementation.
Replace spreadsheets and legacy planning tools with a single engine that forecasts, adjusts to overrides, and keeps your team aligned on one set of numbers. Enterprise-grade forecasting, built for SMB and mid-market teams — without the 12-month rollout.
Demand planning, from every angle.
See AI demand forecasting in motion.
Three minutes to see how sharpr.ai handles real planning workflows.
Forecast that learns. Plan that adjusts.
SKU-level forecasts
AutoETS and CrostonOptimized models, auto-selected per series. Weekly cadence, 52-week horizon. Built on the open-source StatsForecast engine.
Override-aware planning
Sales, marketing, and consensus forecasts with role-gated edits, lock semantics, and a complete audit trail of every change.
Continuously learning
Models retrain as new actuals arrive. Outlier detection, exception queues, and an autonomous review layer keep plans current.
One engine.
One source of truth.
sharpr.ai connects directly to your sales history, ingests at SKU × week granularity, and runs auto-selected forecasting models per series. Planners review and override in a workbench grid; every edit is audit-logged and role-gated.
No re-keying. No spreadsheet hand-offs. The forecast that ships to replenishment is the forecast your planners signed off on.
Two pillars, one engine.
Demand and replenishment planning, computed continuously from your sales history, lead times, and supplier constraints.
Demand Planning
Statistical and intermittent-demand models in one engine, auto-selected per SKU. Promotions, seasonality, new products, and zero-runs handled out of the box. Override-aware workflows with full audit lineage.
- ›AutoETS · CrostonOptimized · StatsForecast
- ›SKU × week granularity, 52-week horizon
- ›Consensus forecasts with role-gated edits
- ›Lock semantics + outlier detection
Replenishment Planning
Dynamic safety stock, reorder points, and EOQ — recomputed daily with real lead times, supplier reliability, and target service levels. Multi-warehouse aware, with inter-DC transfer suggestions.
- ›Service-level driven safety stock
- ›Lead-time aware reorder points
- ›Multi-warehouse + inter-DC transfers
- ›Supplier reliability tracking
What's coming next.
Sharpr ships every quarter. Here's the next four headline capabilities — already designed, sequenced, and on the way.
Scenario planning
What-if simulations across the network. Double a lead time, lift a promo, lose a supplier — see the forecast and replenishment impact side-by-side.
Demand sensing
Short-horizon forecasts that fuse POS, weather, promotions, and external signals — react to demand shifts in days instead of months.
Multi-Echelon Inventory Optimization
Balance stock across DCs and stores simultaneously. Hit service-level targets while freeing working capital — without spreadsheets.
Sustainability metrics
Carbon-aware planning. See emission impact per replenishment, score suppliers on ESG signals, and export audit-ready sustainability reports.
Built for industrial supply chains.
For Retailers
Forecast at SKU × store granularity, handle promotions and seasonality, and replenish stores from DCs without the Monday morning spreadsheet shuffle.
For Distributors
Manage 100,000+ SKUs across multiple warehouses. Optimize replenishment, inter-DC transfers, and supplier orders without spreadsheet gymnastics.
Live in 2 weeks.
Not 12 months.
We deliberately don't sell a year-long consulting engagement. Connect your data, validate the forecast, go live — your planners drive it from there.
Connect & ingest
Plug in your ERP (SAP, Oracle, NetSuite) or drop CSVs. We auto-resolve master data, hierarchies, and 24 months of history in hours, not weeks.
Validate forecast
AI generates your first forecast at SKU × week. Compare against your last 6 months — accuracy review with your planners, no consultants required.
Plan in production
Consensus forecasts shipped to ops. Planners override what they need, replenishment fires automatically, every change is audit-logged.
Why teams pick sharpr.ai
over the alternatives.
How sharpr.ai compares to spreadsheets and legacy ERP planning modules across the things that matter on Mondays.
| Pain point | Spreadsheets | Legacy ERP | ★ Sharpr.ai |
|---|---|---|---|
| Forecast accuracy | Manual, drifts weekly | Rule-based, brittle | AI auto-tuned per SKU |
| Override audit trail | None — emails only | Scattered, hard to query | Full lineage · who · what · why |
| Re-plan time | Hours of refresh | Days of batch jobs | Real-time recompute |
| Multi-warehouse | Tabs per location, no sync | Possible, painful | Native, lock-aware |
| Onboarding time | Already happening — that's the problem | 6–18 months | 2 weeks to first forecast |
| Cost | Free, but invisible time-tax | $$$$ + consultants | Transparent SaaS |
| Industry coverage today | Anything (badly) | Everything (slowly) | Retail + distribution today; manufacturing R2 |
| Scenario planning | Copy-paste tab and pray | Heavy modeling, slow | What-if simulations on roadmap (R1.5) |
What could sharpr.ai
save your business?
Drag the sliders. Estimates use industry benchmarks for retail and distribution.
Plug in your numbers
Estimates based on benchmarks across retail and distribution customers. Not a guarantee — but a useful directional signal.
Estimated annual savings
across 12 months
~18% reduction at 95% service level
~70% of manual planning automated · $36,400 value
Built on open-source forecasting libraries trusted by data teams at scale, deployed on the same cloud infrastructure powering modern SaaS.
A plan for every scale.
Start free, scale as your operation grows. Switch plans any time.
- Up to 1,000 SKUs
- Weekly demand forecasts
- CSV ingest
- Email support
- 1 user
- Up to 50,000 SKUs
- Demand + replenishment
- CSV + REST API ingest
- Override workflows + audit
- Up to 10 users
- Unlimited SKUs & locations
- ERP connectors when ready (SAP, NetSuite)
- Self-hosted or dedicated cloud option
- Custom model fine-tuning
- Dedicated CSM · email support
Frequently asked.
The questions enterprise procurement teams ask first. If yours isn't here,
How long does implementation take?+
Two weeks to first forecast for tenants with clean data and a standard ERP connector. Six to eight weeks for complex multi-warehouse rollouts. We deliberately don't sell a 12-month consulting engagement — that's the legacy ERP model, not ours.
Which ERPs and data sources do you support?+
Today: CSV upload and REST API ingest — clean, simple, works everywhere. Native ERP connectors (SAP S/4HANA, Oracle NetSuite, Snowflake, Databricks) are in active development with target launch in R2. If you have a system that exports to CSV or speaks SQL, we can pilot today.
How accurate are AI forecasts compared to my current system?+
Pilot customers see 15-30% MAPE improvement vs spreadsheet baselines, and 5-15% vs legacy ERP rule-based forecasts. Auto-model selection per SKU is the main driver — we run AutoETS for trend-heavy series, CrostonOptimized for intermittent demand, and pick automatically. We share the comparison numbers from your real data during the demo.
What if our planners need to override the forecast?+
That's a first-class workflow, not an exception. Every override is role-gated, requires a reason, and gets logged in the audit trail with timestamps and actors. Locks prevent unintended overwrites mid-cycle. The forecast that ships to replenishment is the one your planners actually signed off on.
How does pricing scale?+
Tiered by SKU count and feature set: Basic ($99/mo) for under 1,000 SKUs, Startup ($499/mo) for under 50,000 SKUs, Enterprise (custom) for unlimited and multi-echelon. No per-user fees — invite your whole planning team. Annual contracts get a 15% discount.
Is my data safe?+
All data encrypted in transit (TLS 1.3) and at rest (AES-256). Tenant data isolation enforced at the database layer. WorkOS handles identity (SAML and MFA available; SCIM on enterprise). SOC 2 Type II is in progress, not yet certified — happy to share our roadmap and current security posture under NDA.
Do we own our forecast data?+
Yes. You can export everything via Excel, CSV, or API at any time, including audit history. If you ever leave, you take your data — and your improved forecasts — with you.
Can we trial sharpr.ai on our real data?+
Yes. Standard demos use our seeded retail dataset, but for serious evaluations we run a 14-day pilot on a sample of your actual sales history (under NDA). You see real accuracy numbers before committing.
Do you support scenario planning and what-if analysis?+
Scenario planning is on the R1.5 roadmap — what-if simulations like "top supplier doubles lead time" or "promotion uplift +30%" with side-by-side impact across forecast and replenishment. Today's planners can override and re-run the engine to see effects, but native scenarios with saved snapshots ship in R1.5.
How does sharpr.ai help with sustainability?+
Better forecasts mean less excess inventory, fewer expedited shipments, and less waste — direct carbon reductions from the same accuracy that saves you money. We don't yet ship a dedicated sustainability dashboard, but the inventory and freight savings translate cleanly to ESG reporting.
Stop guessing.
Start planning.
See how sharpr.ai forecasts your demand on real data. Demos take 30 minutes.