You sit on millions of customer conversations you can’t use for decisions. We join that language to CRM, usage, and financial data, then an AI agent answers why metrics moved and writes the report.

ChatGPT can talk about a file you upload. It can’t enrich hundreds of thousands of conversations, join what people said to whether they churned, or ship a sourced executive report. We build the Meaning Layer first, then the agent runs on it.

Every insight is traceable back to the exact conversations that produced it. We extract structured fields from every record through validated pipelines, with classification accuracy exceeding 99%. When a report says churn risk spiked in a segment, you can click through to the verbatims and verify it yourself. One customer described being "burned by ChatGPT" before switching to us. They stayed because every claim we surface can be sourced and validated.

Questions your current tools can't. Which conversation signals predict churn before usage metrics decline. What themes in support tickets correlate with renewal outcomes. Which product complaints are statistically significant and tied to real revenue impact. What changed since last month and why. We recently generated a full executive-level analysis for a professional sports franchise, correlating fan feedback with satisfaction scores, identifying the exact drivers of low experience, and delivering board-ready recommendations, all from a single question to our AI agent.

Any text-based conversational data: call transcripts, live chat and chatbot logs, support tickets, open-ended survey responses, CRM notes, and emails. We also ingest structured data like CRM records, product usage, financial data, and satisfaction scores so you can correlate what customers say with what they actually do.

Your current tools can tell you sentiment is down or ticket volume is up. They can't tell you why, which customers are affected, or what to do about it. Dimension Labs enriches every individual conversation, connects patterns across your entire dataset, joins them with your structured business data, and lets anyone ask a question in plain English and get an answer backed by evidence. One enterprise customer spent six months trying to build this internally with their data team and couldn't operationalize a single repeatable pipeline. They were live with us in two weeks.

No. You can use Dimension Labs standalone with built-in querying, auto-generated charts, dashboards, and full executive reports. Or plug structured output into Snowflake, Databricks, or BigQuery so your data team can query it alongside everything else they already use. We're not replacing your stack. We're giving it a data source it's never had access to.

Most customers are live within one to two weeks. Enrichment begins immediately once your data is connected. Customers routinely tell us what used to take a research team weeks now takes a single question to our AI agent.