Indellia offers an Agentic Voice of Customer (VoC) platform that aggregates product feedback from sources like Amazon, Walmart, Best Buy, and internal support tickets, then uses named AI agents to link each comment to the exact SKU by model number, UPC, or ASIN. This SKU‑level linking enables consumer brands to detect anomalies, surface emerging themes, and respond to issues in real time across all retail channels.
Funding
Funding not disclosed
Founders
Product
Problem
Consumer brands struggle to connect unstructured feedback from multiple retail and support channels to the exact products they reference, making it difficult to identify product‑level sentiment, defects, and emerging issues across SKUs.
Solution
Indellia’s Agentic VoC Platform aggregates reviews, support tickets, returns, and survey responses from major retailers and direct channels, then links each piece of feedback to its specific SKU using model numbers, UPCs, or ASINs. Named AI agents automatically cluster feedback into evolving themes, detect anomalies, and surface root‑cause insights without requiring a pre‑built taxonomy. The platform’s architecture exposes these insights through an MCP server that integrates with enterprise LLMs such as Claude, ChatGPT, and Cursor, allowing teams to query the feedback corpus in natural language. Brands can also generate draft responses that match their brand voice and push them directly to retailer accounts. This end‑to‑end solution turns raw product feedback into actionable intelligence at the SKU level.
Target Audience
Primary customers are consumer product brands and their QA, manufacturing, and marketing teams that need SKU‑specific insight from retail and support feedback.
Features
- SKU‑level linking of every review, ticket, and return via model number, UPC, or ASIN across Amazon, Walmart, Best Buy, Costco, Target, and other channels
- Theme Agent that clusters feedback into dynamic topics without a predefined taxonomy, with merge, rename, and pin controls
- Anomaly Agent that models normal feedback patterns per SKU and theme, flagging unexpected changes days before category trends shift
- Defect Agent (beta) that surfaces root‑cause themes for quality and manufacturing issues ahead of warranty data
- Response Agent that drafts brand‑consistent reply suggestions for retailer platforms, editable before posting
- MCP Server integration enabling natural‑language queries through Claude, ChatGPT, and Cursor over the entire feedback corpus
- Native retail channel ingestion pipelines ensuring comprehensive coverage of major e‑commerce and brick‑and‑mortar sources