Industries / Retail

Turn Data Into
Revenue Growth

Transform siloed retail data into powerful insights that move the numbers up. Real-time competitive intelligence, dynamic pricing, and inventory optimization that discovers new revenue streams while your competitors analyze yesterday's data.

Why Retail Needs
Real-Time Intelligence

Traditional retail analytics are too slow for today's competitive landscape

01 / DATA SILOS

Insights Buried in Disconnected Systems

Sales data in POS, inventory in WMS, customer behavior in e-commerce, competitor pricing in spreadsheets. Decision-makers can't see the full picture, missing opportunities while they wait for reports.

02 / STALE INSIGHTS

Yesterday's Data, Tomorrow's Decisions

ML models train on historical data. Dashboards refresh daily. Competitors change prices hourly. By the time you have insights, the opportunity is gone or the threat has already materialized.

03 / COMPETITIVE BLINDNESS

Flying Blind on Market Dynamics

Manual competitor price checks. Weeks to understand market shifts. No visibility into why sales are up or down. Reactive decisions after revenue is already lost.

04 / INVENTORY WASTE

ML Predictions Meet Real World

Stock algorithms trained on pre-pandemic data. Seasonal models miss trend shifts. Over-stock drains capital, under-stock loses sales. Teams discover problems after it's too late to adjust.

ARPIA: Real-Time
Retail Intelligence

18%
Average margin improvement from dynamic pricing
Real-time
Insights, not daily reports—act before competitors
35%
Reduction in inventory carrying costs

ARPIA unifies your retail data (POS, inventory, e-commerce, CRM, competitor intel) into a real-time knowledge graph. AI assistants give decision-makers instant insights. Proactive AI detects opportunities and risks, generating prioritized tasks. Deploy revenue-driving use cases in 30-90 days.

Retail Intelligence
Use Cases

USE CASE 01

Real-Time Intelligence Dashboards for Decision Makers

Give executives and category managers AI assistants with instant access to unified retail intelligence—turning siloed data into insights that discover revenue opportunities across channels, regions, and product lines.

The Problem

  • Sales data in POS, inventory in WMS, behavior in e-commerce
  • Executives wait days for reports that answer yesterday's questions
  • Revenue opportunities hidden in data silos
  • Teams can't connect the dots between metrics

ARPIA Solution

  • Unified knowledge graph across all retail systems
  • AI assistants answer questions in natural language
  • Real-time dashboards with root cause analysis
  • Discover correlations: "Which products drive basket size?"

Business Impact

  • Insights in seconds, not days
  • 12% increase in cross-sell revenue (discovered opportunities)
  • Decision velocity: 5x faster market response
  • New revenue streams identified monthly
$3.5M
Annual revenue growth from discovered opportunities (mid-market retailer)
USE CASE 02

Proactive AI: Competitive Pricing Intelligence

ARPIA's proactive AI continuously monitors competitor pricing, market trends, and inventory levels—generating prioritized pricing tasks with generative real-time analysis, not just ML predictions trained on old data.

The Problem

  • Competitors change prices hourly, manual checks weekly
  • ML models train on historical patterns, miss real-time shifts
  • Pricing teams reactive, not proactive
  • Lost margin or lost sales—never optimal

ARPIA Solution

  • Real-time competitor price monitoring + generative analysis
  • AI generates tasks: "Review pricing on Category X—competitor dropped 15%"
  • Context included: margin impact, inventory levels, demand signals
  • Proactive recommendations, not reactive alerts

Business Impact

  • 18% margin improvement through dynamic optimization
  • Respond to competitor moves in hours, not days
  • Promotional ROI increases 40%
  • Team focuses on strategy, not data gathering
$5.2M
Annual margin improvement (500 SKU category)
USE CASE 03

Intelligent Inventory: ML + Real-Time Intelligence

Connect ML stock predictions with real-time data from ARPIA's knowledge ontology—proactive AI correlates signals and generates tasks to address inventory risks and opportunities before they impact the bottom line.

The Problem

  • ML models trained on pre-pandemic data
  • Seasonal algorithms miss trend shifts
  • Over-stock ties up $M in capital
  • Under-stock loses sales to competitors

ARPIA Solution

  • Correlate ML predictions with real-time market signals
  • AI detects: social trends, competitor stock-outs, weather impacts
  • Generate tasks: "Increase orders for Product Y—demand spike predicted"
  • Human expertise + AI intelligence = optimal inventory

Business Impact

  • 35% reduction in inventory carrying costs
  • Stock-out rate drops from 8% to 2%
  • Markdown waste reduced 50%
  • Cash flow improvement: weeks of working capital freed
$8M+
Annual savings from optimized inventory (100 stores)
USE CASE 04

Retail-Scale Intelligence Platform

Deploy any retail use case—pricing optimization, customer intelligence, supply chain visibility, store operations—on a single platform that scales from pilot to enterprise-wide with built-in governance.

The Problem

  • Each analytics initiative requires custom data pipelines
  • BI tools can't answer "why" questions
  • 6+ months to deploy new capabilities
  • Analytics sprawl: 15 tools, zero integration

ARPIA Solution

  • Single platform for all retail intelligence use cases
  • Unified knowledge graph across sales, inventory, customers, market
  • Deploy new use cases in 30-90 days
  • Scale from one category to entire enterprise

Business Impact

  • 10+ revenue-driving use cases on one platform
  • 60% reduction in analytics infrastructure costs
  • Innovation velocity: 4x faster deployment
  • Competitive advantage compounds with each use case
$15M+
Total annual impact from unified intelligence platform

Built-In Governance
for Retail

Enterprise AI governance and orchestration designed for retail use cases

AI Governance Engine

Unified policy control for every customer AI system, recommendation engine, and inventory management interaction. Real-time enforcement of pricing rules, privacy policies, and business logic across all AI applications.

Complete AI Audit Trails

Full traceability of every AI decision, customer recommendation, and pricing action. Complete audit logs for GDPR/CCPA compliance, competitive intelligence, and business performance documentation.

Customer AI Governance

Continuous monitoring of recommendation accuracy, pricing fairness, and personalization effectiveness. Automated validation workflows for customer experience optimization and privacy compliance.

Agent Orchestration

Governed orchestration of AI agents across customer service, inventory management, and competitive intelligence. Policy enforcement ensures agents operate within pricing boundaries and privacy requirements.

Knowledge Governance

Unified knowledge ontology connecting customer data, product catalogs, and market intelligence. Ensures AI agents access only authorized, governed knowledge with full GDPR/CCPA compliance.

Real-Time Policy Enforcement

Automated policy rules for customer data access, pricing algorithms, and recommendation behavior. Proactive alerts for privacy violations, pricing errors, and competitive risks before they impact customer experience.

Outperform Your Competition

Leading retailers deploy revenue-driving AI in 30-90 days with ARPIA—while competitors wait months for yesterday's insights. See how real-time intelligence creates competitive advantage.

See How Retailers Win View Pricing