Tricuss

Tricuss positions itself as an AI platform for people who make decisions from experimental and operational data. The core idea is that a research question should not require days of SQL, spreadsheet work, and manual literature review. The Co-Researcher Agent unifies the research assets a company already owns — datasets, documents, prior studies — and drives the workflow from question to answer, while the Data Researcher Agent reads not just the numbers but also published papers, returning insights and suggested next actions.

Underneath the agents is an AI-ready data layer. Tricuss builds on Data Lakehouse, Hadoop, and Spark technologies and also helps customers stand up the foundational data governance and integration plumbing (scheduled synchronization, schema updates, ETL) that AI projects usually stall on. The company reports throughput such as 10 million records processed in about 12 seconds, and advertises compression of analysis cycles from days to seconds as well as up to 100x faster design of experiments and root cause analysis.

A newer addition is a shared AI workstation: one workspace for a team's files and agents where members can browse, ask questions, and turn a conversation into an editable document. Tricuss targets industrial research, manufacturing, and other settings where depth, speed, and broad team access all matter. Pricing is not published — the company routes buyers through a demo request.