When a customer asks ChatGPT about your company, the answer is not pulled from your website in real time. It is assembled from what the model absorbed during training - Common Crawl web pages, Wikipedia, news, reviews, Reddit threads, job postings and structured databases like Crunchbase and Wikidata - frozen at a knowledge cutoff months before the model shipped. This story explains where that knowledge comes from, why it drifts stale, how gaps and old narratives creep in, and what companies can actually do to correct the record.
Tonic.ai builds synthetic data infrastructure that lets engineering and AI teams work with realistic, privacy-safe stand-ins for production data. Its platform de-identifies, masks, subsets, and synthesizes both structured databases and unstructured text so developers can test software, train models, and feed LLM and RAG pipelines without exposing sensitive information. Founded in 2018 by a team out of Palantir and Tableau, the San Francisco company serves enterprises across finance, healthcare, and technology and has raised roughly $56M in venture funding.