Operator vertical
Demand Forecasting AI for Distributors
Demand forecasting, fill-rate versus inventory tradeoffs, and EDI exception agents for $50–500M wholesale distributors still running ERP plus spreadsheets.
Built for: VP Supply Chain, CFO, or CIO at a $50–500M wholesale distributor
What breaks before AI
- ERP forecasts ignore real lead times and exception mess
- A-movers stock out while the long tail sits
- EDI exceptions become chargebacks
- Reps call accounts they like, not accounts about to reorder
SKU-branch forecasts wired to replenishment and EDI—measured on fill rate and inventory dollars, not dashboard vanity.
Workflow pages operators search
Each page owns a specific job-to-be-done query. Start with the bottleneck that hurts this quarter.
Demand forecasting
Search: demand forecasting for distributors
Forecast at SKU-branch with your lead times and seasonality—not a national average in Excel.
Inventory vs fill-rate
Search: wholesale inventory optimization AI
Show the CFO the dollars tied up to buy the next point of fill rate—then stock the SKUs that move it.
EDI exception agents
Search: EDI exception management AI
Read 810/856 exceptions, propose codes, and escalate only what needs a human.
Rep account scoring
Search: distributor sales account scoring AI
Rank accounts by reorder likelihood and whitespace so field time follows margin.
Business outcomes AI can move
- Raise fill rate without adding a warehouse of safety stock
- Cut excess inventory on the long tail
- Clear EDI exceptions before they become chargebacks
- Point reps at accounts most likely to reorder
AI capabilities
Each capability maps to a business KPI, revenue, cost, risk, or cycle time, not model accuracy on a slide.
Revenue
Distributor demand forecasting
Forecast at the SKU-branch level with seasonality and lead time, not a national average in Excel.
Rep account scoring
Rank accounts by reorder likelihood and whitespace so field time follows margin, not habit.
Cost
Inventory versus fill-rate tradeoff
Show the CFO the dollars tied up to buy the next point of fill rate, then stock the SKUs that move it.
Cycle time
EDI exception agents
Read 810/856 exceptions, propose codes, and escalate only the ones that need a human.
Production use cases
- SKU-by-branch demand forecasting
- Fill-rate versus inventory optimization
- EDI invoice and ASN exception agents
- Outside-sales account scoring
How to engage
Start bounded. Scale only when the KPI moves.
Forecast diagnostic
From $7,500Fill-rate vs inventory baseline and SKU-branch opportunity map.
Scoped production mandate
From $15kForecast or EDI exception agents live in 6–10 weeks.
Embedded partnership
From $25k/moExpand categories, branches, and sales scoring.
Frequently asked questions
We already bought an ERP planning module. Why you?
Most ERP forecasts are unused because they ignore your real lead times and exception mess. We wire the forecast to replenishment and EDI, then measure fill rate.
How do you scope AI for our industry?
Week-one discovery locks business KPIs—revenue, cost, risk, or cycle time—not model vanity metrics. We map your data sources, compliance constraints, and existing stack, then propose a fixed-scope mandate with acceptance criteria or redirect you to a simpler path.
Do you have experience in our sector?
Proven depth sectors (financial services, federal, real estate, telecom, higher education) reflect production systems we've shipped. Growth and operator verticals (MGAs, credit unions, property management, 3PL, RCM, staffing, licensed iGaming, FFL) are selective mandates where those patterns transfer with industry-specific tuning. Biotech, insurance, and regulated work often runs under NDA.
What do we get at the end of an engagement?
Deployable code in your repos, monitoring and runbooks, documentation your team can operate, and knowledge-transfer sessions. The Production Standard is contracted in writing—no handoff to a junior bench after the sale.
What's the fastest way to start?
Book a discovery call or start with a bounded diagnostic: $2,500 Postgres audit, insurance claims-fraud diagnostic from $7,500, or the free MLOps readiness assessment. Each path surfaces whether AI is the right tool before a larger commitment.
The Production Standard
The Production Standard
Six commitments contracted in writing on every engagement.
01
Deploy or redirect
If AI isn't the right tool, we say so in week one and redirect budget to what will ship. No POC theater.
02
Metrics before models
Business KPIs locked in discovery. Model selection follows the metric, not the hype cycle.
03
Governance from day one
Model cards, access controls, evaluation harnesses, and audit trails, not a compliance bolt-on at go-live.
04
Production artifacts
Deployed code, monitoring dashboards, CI/CD pipelines, and incident runbooks. Not recommendations for someone else to implement.
05
6-week production target
Scoped projects designed for production in 6–10 weeks. Boutiques move; global programs wait for steering committees.
06
Capability transfer
Your team can operate, extend, and maintain what we build. IP and documentation transfer is included, not upsold.
Every scoped project includes a production deliverable checklist signed off before close. If we can't commit to deployable output, we won't take the engagement.
Selective intake · 2026
Your next system shouldship to production.
Agentic development from architecture through deployment, with the Production Standard contracted in writing.