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Oracle + Home Retail: Built for Head of Procurement

Home retailers have 50,000+ SKUs and blind spots hiding in every store. Ward watches them all and delivers the findings your team doesn't have bandwidth to find. Your Oracle Retail data holds answers nobody has time to extract. Ward reads it via read-only APIs.

Ward + Oracle for Home Improvement

Home Improvement retailers running Oracle Retail get AI insight cards without custom development. Project-based purchasing, long-tail SKUs, and seasonal volatility. Ward manages the complexity of 50,000+ SKU environments with ease.

How it works: Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments.

Ward monitors 50,000+ SKUs across your stores and delivers automated insight cards covering Project basket value, Seasonal accuracy, Long-tail turn, and more.

app.getward.ai Live demo
Acme Retail @Merchandising: VP Analyst claude-sonnet default
A

Chat

Ask anything. Ward routes to the right agent and returns cited answers.

Why did Store 37 miss target last week?
You · 9:42 AM
Schema Scout · routed to Merchandising Agent

I pulled Store 37’s last 28 days against the chain baseline. Two root causes, both compounding.

SignalFinding
labor_efficiencyRev/labor-hour −22% vs. cluster, staffing mismatch at 11a–1p peak
inventory.freshFresh fill 83%, backroom replenishment lag at 2–4p
promo.liftBOGO crackers cannibalized Brand Y by 28%, net category +6%

Recommend: re-baseline Store 37 schedule against true peak, raise replen window to 1p, and review the BOGO before next cycle.

8 parallel queries 3 sources cited confidence 0.92
Show me how to fix the staffing mismatch.
You · 9:43 AM
Labor Agent · drafting schedule diff
Querying labor_scheduling
Ask anything, Ward routes to the right agent. Cmd+K

Dashboards

Pinned views built from saved data-lake queries.

Revenue vs. forecast +4.2% WoW
Gross margin % −3.2pp
Fill rate, fresh 83%
Shrink, West region +0.8pp

Sources

Connect external systems to the data lake.

NameTypeLast sync
sap_pos_transactionsimport2m ago
sap_inventory_shrinkageimport2m ago
sap_labor_schedulingimport14m ago
retail_inventory_weeklyimport1h ago
retail_google_ads_dailyimport1h ago
retail_meta_ads_dailyimport1h ago
retail_ga4_website_dailyimport1h ago

Policies

Browse and manage Cedar access policies for your tenant.

TLS 1.3 AES-256 Read-only SOC 2 II
Policy IDEffectResources
merch-read-defaultpermitModel::*
finance-read-shrinkagepermitModel::"inventory_shrinkage"
vendor-blockedforbidModel::"labor_*"
region-west-onlypermitTenant::"acme"
Live product demo, Ward analyzing retail data in real time.

What Ward delivers

  • MSA, DPA, SOC 2 Type II underway, and architecture review available before signature
  • Month-to-month contracts. No multi-year lock-in. No auto-renew traps
  • Transparent pricing set by scope and store count
  • 14-day insight guarantee. If Ward doesn't deliver, month two is on us
  • AI strategy, orchestration and reporting-layer work in enterprise grocery at nine-figure revenue. Reference calls available before signature

Metrics Ward monitors

Project basket value
Seasonal accuracy
Long-tail turn
Pro customer share
Attachment rate

Home challenges Ward solves

  • Project basket identification
  • Seasonal pre-positioning
  • Long-tail inventory
  • Pro vs DIY segmentation
  • Weather-driven demand

How Ward connects to Oracle Retail

Ward integrates with Oracle Retail Merchandising (RMFCS), Oracle Retail Demand Forecasting, and Oracle Retail Analytics. Full stack visibility.

Setup: Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments.

Data Ward reads from Oracle

Sales audit
Inventory positions
Allocation
Replenishment
Demand forecasts
Price management

Impact metrics with Oracle

Fill Rate
Allocation gaps caught
Replenishment outputs checked against actual shelf conditions per store.
Demand Forecast Accuracy
Accuracy gap closed
External signals enrich Oracle forecasts where they drift.
Markdown Waste
Slow movers caught early
Triggers shallower markdowns before inventory ages out.
Inventory Carrying Cost
Overstock freed up
Demand-aligned inventory releases locked working capital.

Data lake enrichment

Ward enriches Oracle data with: Sales audit data, Weather & events, Competitor pricing, Demographic data, Supplier scorecards

Merchandising wants Ward. You sign the contract.

Pain points
  • ×Business sponsor saw the demo. You have a week to vet a vendor you didn't pick
  • ×AI vendors price by seats and tokens. Total cost is unknowable until invoice three
  • ×Multi-year commits with auto-renew. No exit if the pilot stalls
  • ×Renewals come back 30% higher, with no room to push back and no benchmark to cite
  • ×Security and DPA reviews start after the team has already committed
How Ward helps
  • MSA, DPA, SOC 2 Type II underway, and architecture review available before signature
  • Month-to-month contracts. No multi-year lock-in. No auto-renew traps
  • Transparent pricing set by scope and store count
  • 14-day insight guarantee. If Ward doesn't deliver, month two is on us
  • AI strategy, orchestration and reporting-layer work in enterprise grocery at nine-figure revenue. Reference calls available before signature

Enterprise SaaS spend grew 18% YoY. 53% of subscriptions are underused or duplicative. Source: Gartner

Home KPI impact

Seasonal Accuracy
Weather + event driven
Pre-positioning adjusted for peak season signals.
Long-Tail Turn
Dead weight separated
Which tail SKUs serve project needs vs sit idle.
Project Basket Value
Cross-sell surfaced
Project purchasing patterns drive attachment.
Inventory Carrying Cost
Capital freed
Demand forecasting reduces slow-moving overstock.

Frequently asked questions

Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments. Data points include: Sales audit, Inventory positions, Allocation, Replenishment, Demand forecasts, Price management.

Yes. Ward reads Oracle data and combines it with contextual signals (weather, events, demographics) to generate Home-specific insight cards. No custom development required.

Merchandising wants Ward. You sign the contract. Ward solves this with automated insight cards: MSA, DPA, SOC 2 Type II underway, and architecture review available before signature. Month-to-month contracts. No multi-year lock-in. No auto-renew traps. Transparent pricing set by scope and store count.

Ward delivers daily insight cards covering Project basket value, Seasonal accuracy, Long-tail turn, tailored for Procurement decision-making. Each card includes what changed, why it matters, and what to do next.

First insight cards arrive within 48 hours of data connection. Ward needs approximately 2 weeks to establish stable baselines for your specific operation.

No. Ward sits on top of your existing stack. It is the proactive intelligence layer that watches your data continuously and delivers insight cards, so your team acts on findings instead of hunting for them.

See what Home problems Ward catches.

Root causes, not just alerts. See it on your data.

Read-only to start · your LLM keys · SOC 2 Type II underway · or book a call directly

Find out what your data has been hiding.

Tell us about your operation. We’ll show you the problems Ward catches, and the ones your current tools miss.

Step 1 of 3
What are your goals?
Step 2 of 3
About your operation
Step 3 of 3
Your contact info