Symbric

Symbric is building an AI data analyst that answers business questions and attaches a 'receipt' to every number — the data source, its freshness, and the verification checks it passed. It works by building and auto-maintaining a semantic layer from a client's existing code, database schemas and data warehouses.

General AI agents are now confidently feeding plausible-but-wrong figures into board decks and forecasts — what the company calls 'quiet failures'. As more decisions run through chat interfaces, a system that refuses to guess when data is stale or undefined is arguably the safer default.

The company is tackling data reliability head-on, arguing that trust — not raw answering ability — is the missing piece in AI analytics. Founder Angeline Guo is building Symbric around a simple stance: no proof, no answer.

It's early days and pre-funding, so the proof will be in the product — but the founding team has framed a sharp, opinionated wedge in a crowded BI market rather than another generic 'chat with your data' tool.