DigiQuench

Home / Agents / RetailAnalytics

Agent 12 · Retail

RetailAnalytics Agent

Cleans sales data and writes the owner's daily brief.

Narrow scope firstInsightLangGraph + CrewAI

Found21
Fixed + verified21
Held for approval0
Recall1.00

One offline run on demo data with planted problems (recorded platform test, November 2026).

How RetailAnalytics heals data, step by step
Client problem
Owners never see a clean daily picture; guest checkouts and bad prices distort numbers.
What it does
Fixes missing customer IDs, impossible prices and duplicates; builds daily sales; detects revenue drops.
How it heals
Repairs data and has a CrewAI team write a grounded daily brief.
Human gate
None (read-only insight).
Typical buyer
Retail owners
Built with
LangGraph self-healing loop with a CrewAI crew (analyst, fixer, reviewer)
Demo data
Kaggle carrie1/ecommerce-data (UCI Online Retail, ~540k invoice lines).
Tables
online_retail ← Kaggle carrie1/ecommerce-data
Target outcome
Target: owner brief ready by 6 AM every day.
Path to production
Insight Pack.
Issues detected on the demo data
IssueRiskProposed fixCount
missing_customer_id
'customer_id' is empty
lowTag as guest customer10
out_of_range_price
price=-1.69 outside [0, None]
lowQuarantine – likely cancellation or entry error3
duplicate_record
Duplicate on line_id
lowDrop duplicate invoice line5
revenue_drop
Revenue 1,843 vs 7-day average 3,575
lowExplain in the daily brief with drivers3

How we demo it

  1. Load UCI Online Retail II.
  2. Run RetailAnalytics.
  3. Read the daily brief.

Built on AWS

Runs in the platform container on EC2 Graviton (or on demand in Lambda), writes healed tables to the S3 lakehouse, uses Amazon Bedrock only to write explanations, and reports six metrics to CloudWatch.

More Retail agents

Related agents

Step into DigiQuench.
Agents that heal your data.

Watch an agent find planted problems, fix the safe ones and wait for your approval on the rest. Thirty minutes, live.