Connect fragmented systems into one AI-ready retail brain.
PathAnalytics standardizes source data into a governed semantic layer so dashboards, forecasts, Retail Copilot answers, recommendations, and agents all use the same retail truth.
Connected Sources
Amazon, eBay, ShopGoodwill, Shopify, Etsy, Walmart, marketplaces, and owned commerce.
POS, stores, customers, buyers, locations, categories, transactions, and returns.
Inventory management, warehouse, fulfillment, shipping, delivery exceptions, returns, listings, production, BOL, and audits.
Unified Retail Data + AI Semantic Layer
Canonical retail entities, governed metrics, comparison logic, freshness markers, forecasts, and secure business context.
AI and Agents
The AI layer missing from POS, ERP, and ecommerce tools.
Transactional POS engines and ERPs record what happened in the past. Native marketplace dashboards only see their own channel. PathAnalytics acts as the intelligent operating layer on top of your existing systems, unifying physical store and digital marketplace data to predict demand and automate revenue recovery.
Business metrics before raw database access.
Connecting LLMs directly to raw SQL databases can produce metric hallucinations, incorrect inventory joins, and non-reproducible calculations.
PathAnalytics standardizes store, channel, SKU, and customer data into a governed semantic layer. Every Retail Copilot answer and automated recommendation relies on verified, audit-ready metrics.
Why choose PathAnalytics over custom builds or native reports?
Deploy an enterprise Retail AI Platform without multi-year engineering roadmaps or fragmented single-channel dashboards.
Custom In-House Build
- 12-18 month engineering timeline
- $500k+ ongoing data team costs
- Brittle custom LLM pipeline maintenance
- High risk of metric hallucination
Siloed POS and Channel Reports
- Store-only or channel-only blind spots
- Backward-looking historical graphs
- No cross-channel inventory transfers
- Passive reports requiring manual effort
PathAnalytics Retail AI Platform
- Live in days with pre-built connectors
- Fractional cost with fast ROI
- Governed semantic context
- Predictive ML and Retail Copilot workflows
Built to move the metrics retail teams care about.
PathAnalytics is not a generic dashboard layer. It is designed around the decisions that recover revenue, improve sell-through, protect margin, move inventory, and keep customer satisfaction visible.
Drive Better Sell-Through
Find slow movers, stale listings, price gaps, channel mismatches, and replenishment misses before they become margin problems.
Recover Revenue Leakage
Detect missed conversion, stockout risk, return spikes, campaign waste, high-traffic low-sales products, fulfillment friction, and pricing anomalies.
Forecast Demand Granularly
Plan demand by SKU, category, store, channel, location, season, and time period with models shaped for retail behavior.
Predict Sales Earlier
Use channel, inventory, listing, seasonality, and historical demand signals to see likely revenue and unit movement sooner.
Improve Fulfillment Health
Connect orders, shipping, exceptions, missing shipments, delayed deliveries, undelivered packages, service levels, and operational bottlenecks to the same decision layer.
Customer Experience Feedback Loops
Feed missing shipment, delayed delivery, undelivered order, return reason, cancellation, refund, and support signals back into inventory, listing, pricing, and fulfillment decisions.
Recommend Price Moves
Spot markdown, repricing, promotion, and channel-placement opportunities using demand, margin, inventory age, and conversion signals.
Retail Copilot
Let teams ask plain-English questions about demand, stock risk, revenue leakage, pricing, listings, margins, fulfillment, and store performance.
Lister Performance Analytics
Measure listing throughput, quality, conversion, relist activity, average listed days, and sell-through by lister, channel, category, and price bucket.
SKU-Driven Demand Forecasting
Forecast at SKU, store, channel, category, location, and time-window levels so inventory can be matched to where demand is likely to appear.
Customer, Location, and Buyer Insights
Connect customer, buyer, location, store, and channel behavior to inventory, pricing, promotion, and demand decisions.
Approved AI Workflows
Route recommended actions to the right owner, track approvals, and measure whether each workflow improves revenue, margin, fulfillment, or sell-through.
Retail AI Platform, packaged for the jobs teams need done.
Use PathAnalytics as the shared retail AI foundation, then activate focused modules for sell-through, revenue recovery, copilot workflows, and customer targeting.
Sell-Through AI
Find slow movers, stale listings, weak channels, price gaps, stockout risk, inventory age, and demand shifts before margin is lost.
Explore sell-throughRevenue Recovery AI
Detect where revenue leaks through low conversion, abandoned demand, fulfillment friction, return spikes, campaign waste, and preventable cancellations.
Explore recoveryRetail Copilot AI
Let executives, operators, merchandisers, and ecommerce teams ask governed retail questions and approve recommended workflows.
Explore copilotCustomer Targeting AI
Identify engagement, satisfaction, fulfillment, return, and repeat-purchase risks early, then recommend the next best action.
Explore targetingThe operating workspaces teams need on day one.
The beta product already brings core retail workflows into one shell: dashboards, ecommerce, stores, reports, forms, Retail Copilot, account controls, and admin visibility.
Executive Dashboard
KPI cards, sparklines, trend charts, date comparison, forecasts, tenant switching, and dark/light mode in one operating shell.
Ecommerce Workspace
Channel KPIs, pipeline flow, trend windows, order drilldowns, item detail, channel filters, and mobile-aware listing/order flows.
Retail Store Workspace
Store overview, store rows, item detail, transaction detail, and local performance signals tied back to enterprise metrics.
Reports and Export
Grouped report selectors, tabular output, CSV export, shared data-grid behavior, and consistent metric definitions.
Retail Copilot
Ask business questions, investigate drivers, review recommended actions, and use the governed semantic layer instead of disconnected report logic.
Retail Ops Forms
Donations, production, BOL, end-of-day, and store audit workflows with submit, history, and operational visibility.
Channel and Store Controls
Channel list, credential visibility, store list, account profile, company detail, user management, roles, invites, and activity log.
Secure Enterprise Access
Password login, magic links, password reset, email verification, SSO resolution, tenant invites, tenant switch, and audited logout.
Data Freshness Foundation
ETL scheduler, sync runs, cursors, leases, errors, ClickHouse facts, Redis cache, and a path toward connector admin visibility.
More than dashboards: the product routes work to the right place.
PathAnalytics is designed around workflows that detect leakage, recommend corrective actions, route ownership, and measure the outcome after teams act, including delivery and return feedback that affects customer satisfaction.
A closed-loop retail system, not a row of disconnected reports.
Each lifecycle event becomes AI-ready context for the next forecast, recommendation, approved action, customer feedback loop, and measured business outcome.
Every action improves the next decision.
Forecasts, sell-through recovery, inventory matching, pricing actions, fulfillment feedback, and agent workflows use the same unified retail context.
From question to operating action.
PathAnalytics gives every team a practical way to move from business question to recommendation, approved workflow, and measured outcome. Leaders get the high-level answer, operators get the exception list, and frontline teams get the next action.
- Merchandising: Which products need pricing, markdown, replenishment, or transfer action?
- Ecommerce: Which listings, listers, channels, and relistings are holding back sell-through?
- Operations: Where are missing shipments, fulfillment delays, aging inventory, and order exceptions creating risk?
- Customer Experience: Which delivery failures, return reasons, and support issues are hurting satisfaction?
- Executives: What changed, where is revenue leaking, and which actions protect revenue and margin?
Why did sell-through drop in women’s apparel, and what should we do this week?
Demand shifted to Marketplace and two stores are overstocked.
Forecast variance is highest in denim and outerwear. Listings with missing measurements have 18% lower conversion, and fulfillment delays are affecting one channel.
Make retail data usable by teams, copilots, and agents.
See how PathAnalytics turns ecommerce, POS, inventory, fulfillment, customer, buyer, and location data into governed answers, revenue recovery recommendations, approved workflows, and measurable outcomes.
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