ReviewBay gathers every public review of a brand, stores it in Neon with pgvector, and lets you ask questions in plain English, with links back to the original reviews. No dashboards to build. No guesswork.
Four stages that run themselves: collect every public mention, store it, give it meaning, and put an analyst on top of it.
Collectors watch review sites, social platforms, app stores, and forums for your brand. New mentions land in the pipeline within minutes, deduplicated, timestamped, and source-linked.
Raw mentions are normalized into a single review model: source, author, rating, sentiment, product line. Your Postgres, your data, queryable from day one.
Every review is embedded on-device with a local model, so nothing is sent to a third party. Semantic search finds the complaint about "checkout freezing" even when nobody used those words.
Ask in plain English. The AI answers from retrieved reviews only, and every claim links back to the original post. No hallucination. No black box.
Answers are auditable by design: click any citation and read the original review, on the original site, in context.
→ Open the chatPoint ReviewBay at a brand name. The dashboard fills in as reviews arrive, and the chat answers with citations. No data engineering. No setup project.
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