How Workliq AI reasons
Most AI tools generate answers.
Workliq generates decisions.
The reasoning layer is where Workliq differs. We don't hand you a chart and let you guess. We tell you what the data means, why it matters, and what to do next — with the evidence behind every claim.
Deterministic first, AI second
Schema inference, anomaly detection, forecasting, statistical tests — all run on pure Python before any LLM sees your data. Numbers come from code you can verify.
Evidence on every claim
Every recommendation lists the drivers behind it — which metrics moved, by how much, with what confidence. Click to expand the SQL and Python.
Counter-hypotheses included
Workliq doesn't just give you one answer. It tells you what could falsify the answer, what to watch for, and what to test next quarter.
Editorial discipline
No 12-slide decks with empty placeholders. Every page in the export has a real number, a real chart, or a real action — no filler.
Decision-ready output
Three watch metrics, three stop-if conditions, three upside levers, one 90-day plan. The format your team can actually act on.
Audit trail by default
Every action — upload, query, export, share — is logged immutably with timestamp and SQL trail. Built for teams that need to show their work.
Want the technical depth?
Full reasoning architecture, model routing, and verification pipeline are documented behind login for paying customers.
Sign up to read more →