Retail intelligence

Ask your stores anything.
Ward answers, then fixes it.

Ask in plain English. Ward writes the query, reads every system, and answers with the source cited, then runs the playbook to fix it.

Built by operators who scaled 400+ locations.
app.getward.ai Live
Why did Store 37 miss target last week?
Schema Scout → routed to Merchandising Agent

Pulled Store 37’s last 28 days against the chain baseline. Two compounding causes:

labor_efficiencyRev/labor-hr −22% — staffing miss at 11a–1p peak
promo.liftBOGO crackers cannibalized Brand Y −28%, net cat +6%
8 parallel queries 3 sources cited confidence 0.92
›Ask anything — Ward routes to the right agent.⌘K

Playbooks — agentic triggers

Conditions that arm a workflow and run it automatically. Write-back gated on a named human.
WHEN fill_rate < 95% · 2 days → Stockout escalation armed
WHEN net_promo_lift < +3% · mid-flight → Promo conflict cancellation running
WHEN invoice ≠ contract price → Vendor invoice dispute armed
WHEN shrink > 1.5× baseline → Shrink investigation armed
WHEN style_velocity < cluster −25% → Markdown cadence reset fired 2×
43 playbooks armed across merchandising, supply chain, store ops, finance & more.

Dashboards built by chat

Pinned from saved questions. No BI ticket.
Revenue vs forecast+4.2% WoW
Gross margin %−3.2pp
Fill rate · fresh83%
Shrink · West+0.8pp

Build your own data sources

Connect any system. Ward routes queries to it automatically.
SAP POS transactions federated 2m ago
Shopify orders federated 5m ago
Snowflake · margin marts federated live
GA4 · web events import 1h ago
Relex replenishment federated live
+ Connect a source — Ward maps the schema and routes to it

Intelligent query routing

Each query goes to the cheapest model that clears the quality bar.
“List stores below fill-rate SLA” → Haiku $0.002 bar 0.96
“Explain Store 37 miss” → Sonnet $0.011 bar 0.92
“Model 3 markdown ladders” → Opus $0.040 bar 0.95
“Daily KPI summary” → Haiku $0.002 bar 0.97
Mixed routing this month saved 61% vs. all-premium.

Compute management

A budget per department and user. Caps spend, not answers.
Merchandising
71%
Supply Chain
65%
Store Ops
61%
Ecommerce
94%
Finance
48%
Ecommerce flagged at 94% — before it became a surprise invoice.

Bring your own LLM

Your keys, your models. Route per task. No lock-in.
Anthropic● keys live
Claude Opus · Sonnet · Haiku
OpenAI● keys live
GPT-4o · o-series
Google● keys live
Gemini Pro · Flash
Ollama● keys live
Llama 3 · on-prem
Switch models without rewriting the stack. Read-only by default.
SOC 2 Type II in progress TLS 1.3 in transit AES-256 at rest Read-only by default
01
What Ward runs on

Three pillars.
Insight, automation, governed routing.

Every answer and every action Ward produces is one of three things working together: insight pulled in plain English, automation that acts on it, and a routing layer that keeps it cheap, governed, and always on.

01 Dashboards built by chat
Data insight
Ask Ward in plain English. It writes the query, reads every system, and answers with the SQL cited. No analytics queue, no ticket, no BI backlog.
  • Natural-language dashboards
  • Cited SQL on every answer
  • Self-serve for store, ops & finance
02 Playbooks
AI automation
Pre-built retail playbooks detect what changed, attach the right procedure, and write back to the system of record. Gated on a named human. Closed only when the KPI moves.
  • Playbooks by industry & department
  • Write-back to the system of record
  • Outcome-anchored, fully audited
03 Your keys. Right model. Never down.
Governed routing
Every query routes to the cheapest model that clears the bar, on your own keys, read-only by default, with automatic failover. Finance caps the spend without capping the answer.
  • Intelligent query routing for cost savings
  • Bring-your-own-LLM, no lock-in
  • Read-only data governance & audit trail
  • Multi-model redundancy, no single point
02
The Loop

Six stages. One unbroken chain.
Signal in, outcome out.

Most tools stop at the alert. Ward owns the next five steps, all the way to a measured KPI.

01
Detect
Ward watches every store and every KPI. Anomalies surface against your estate baseline.
POS · ERP · WMS · finance ledger
02
Attribute
Cause attributed: vendor short-ship, promo conflict, planogram drift, schedule miss.
Reasoning graph · audit log
03
Recommend
Insight opens a case with the right play attached. Owner, deadline, success metric on day one.
Plays catalog · case object
04
Execute
Procedure runs against the system of record. Write-backs gated on a named human.
Manhattan · Blue Yonder · SAP · Relex
05
Audit
Every step signed, logged, and ready for review. SQL, model card, approver.
SIEM stream · Splunk · Datadog
06
Measure
Case closes only when the KPI moved. Outcome attaches to the play that fired it.
KPI delta · attribution chain
Walk the loop →
03
Playbooks

Pre-built. Retail-specific.
One per job, by industry and department.

Playbooks are ready-to-run procedures, not configurable workflows. Each one pairs a data insight with the automation and write-back to act on it. Browse them by industry, department, and the systems they run against.

Stockout escalation
Forecast says zero-on-hand within 48 hrs. Ward opens a case, raises replenishment against the SOR, and notifies the buyer. Closed when shelf reads green.
VerticalGrocery · C-Store · Pharmacy
Target KPIOn-shelf availability
Executes in≤ 6 hrs
System of recordManhattan · Relex
Vendor invoice dispute
Ward reconciles invoice line items against receipt logs and contract terms, drafts the dispute packet, and routes to AP with the evidence chain attached.
VerticalAll
Target KPICOGS recovery
Executes in≤ 24 hrs
System of recordSAP · Coupa · Oracle
Promo conflict cancellation
Cannibalization detected mid-promo. Ward proposes to kill the offending overlap and pings the merchandising lead. Approval required before write-back.
VerticalGrocery · Fashion
Target KPINet promo lift
Executes in≤ 2 hrs
System of recordPromo engine · POS
Planogram correction
Sales-correlated drift flagged. Ward issues the corrected planogram to the field, tracks the reset, and verifies compliance with next-cycle photos.
VerticalConvenience · Specialty
Target KPICompliance + sales lift
Executes in≤ 12 hrs
System of recordJDA · field-ops app
Shrink investigation
Cause attributed: dock vs. floor vs. admin. Ward opens an LP case with the transactions, the camera windows, and the recommended next interview.
VerticalAll
Target KPIShrink %
Executes in≤ 48 hrs
System of recordLoss-prevention case mgmt
Markdown cadence reset
Style velocity below cluster. Ward proposes a shallower-but-earlier markdown ladder and writes the schedule into the pricing engine on approval.
VerticalFashion · Home Improvement
Target KPISell-through at full margin
Executes in≤ 24 hrs
System of recordPricing engine · POS
See the playbook →
04
Why a Loop, Not a Layer

A dashboard tells you something is wrong.
A loop closes the case.

Stage
Without Ward
With Ward
Detection
Weekly report. The store you're losing money on right now is on slide 14.
Continuous. Anomaly surfaces against per-store baseline before close of day.
Decision
An analyst gets an email. They guess at the cause and ping three people.
Cause attributed in the audit log. The right play is already attached to the case.
Resolution
A ticket lands in someone's queue. Maybe it gets done. The KPI never gets revisited.
Write-back fires against the system of record. Case closes only when the KPI moves.
05
Retail Verticals

Vertical depth is the moat.
The loop reads each one differently.

Every play speaks your vertical: grocery, fashion, convenience, pharmacy, home improvement, specialty. The math is tuned to the vertical's velocity, regulation, and SKU density.

30,000+ SKUs
Grocery & Supermarket
U.S. grocery shrinkage topped $37 billion in 2023, with perishable waste accounting for nearly a third.
30K+SKUs per store
15,000+ SKUs
Fashion & Apparel
The average fashion retailer marks down 30–40% of inventory, erasing up to $150 billion in margin industry-wide each year.
15K+SKUs per location
3,000+ SKUs
Convenience & C-Store
Inside-store sales account for only 33% of c-store revenue but 70% of gross profit. Optimizing that mix is the margin game.
24/7daypart monitoring
20,000+ SKUs
Pharmacy & Health
Front-of-store categories drive up to 65% of pharmacy gross margin, yet most chains still manage them with spreadsheet-era tools.
48hrillness demand lead time
50,000+ SKUs
Home Improvement
Home improvement retailers lose an estimated 4–8% of revenue to seasonal overstock and stockout imbalances each year.
50K+SKUs optimized
10,000+ SKUs
Furniture Manufacturing & Retail
Furniture manufacturers operate on 3–6% net margins. A single quarter of misread demand or buried inventory data costs more than most analytics budgets.
3–5disconnected systems unified
5,000+ SKUs
Specialty Retail
Specialty retailers with strong customer data outperform peers by 2–3x on repeat purchase rate and lifetime value.
5K+SKUs per boutique
06
Built for the scale-up

800 stores today.
3,000 stores soon. +2% EBITDA along the way.

Ward is the analytics and closed-loop layer for retailers tripling their footprint without tripling their back office. We are in active pilot today with an 800-store, $300M a year fresh grocery chain. Not built for the demo. Built for the trajectory.
Where the points come from
Hitting +200 bps on EBITDA is arithmetic across four signals. None of them require a new analyst.
~30 bps
Fill rate · fewer lost baskets
~50 bps
Assortment · better mix, less long tail
~80 bps
Shrink · cause-attributed loss
07
Enterprise

Audit-grade by default.
Procurement-ready by design.

Every case signed. Every write-back logged. Every number traceable to the SQL, the model card, and the named approver. SOC 2 Type II in progress. ISO 27001 on the roadmap. Customer-managed keys, SSO/SAML, SCIM, RBAC.

Trust & integrations
SOC 2 II in progress. MSA, DPA, COI on file.
Security questionnaire pre-answered, sub-processor list current, cyber and tech E&O with an AI rider. Integrations are tiered: native (Manhattan, Blue Yonder, SAP, Oracle Retail, Relex, Snowflake, Databricks), write-back, and read-only. The directory says which is which before you sign.
Deploy & pilot
Multi-tenant SaaS, customer VPC, or on-prem connector
Pick the boundary that survives your security review, with reference architectures before signature. The 90-day pilot is structured: pre-agreed KPIs, cases, and close criteria. No value debate at month four.
Open the trust center → Browse integrations →
08
FAQ

Frequently asked questions.

SAP, Oracle Retail, Shopify, BigQuery, Snowflake, flat files, and any system with a REST API.

First cards within 48 hours. Robust baselines in roughly 2 weeks.

No. Ward sits on top as the intelligence layer that watches your data.

TLS 1.3, AES-256 at rest. SOC 2 Type II in progress. On-prem available.

Yes. Ward scales from 5 stores to 5,000.

Based on store count and data volume. POC engagements at a fixed fee.

A workflow is a builder. A play is a verb. Plays are the retail moves every operator should be running, vendor invoice dispute, stockout escalation, promo conflict cancellation. Each one is specced end-to-end: trigger, procedure, write-back, proof. You don't configure them; you run them.

See your stores through Ward’s eyes.

Start a 90-day pilot. Pre-agreed metrics, pre-agreed plays, pre-agreed close criteria.

Get a demo →
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Find out what your data has been hiding.

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