# RootCause Assistant (BETA) The RootCause Assistant lets you interact with your data, Digital Twins, and analyses through natural language. Ask questions, run simulations, and explore causal relationships — all through conversation. Unlike typical AI chat tools, the Assistant doesn't try to reason about your data directly. It orchestrates RootCause's analytical engines — causal discovery, counterfactual simulation, data queries — and reports what those engines compute. The AI handles the conversation; the math comes from purpose-built algorithms.
Four-stage diagram showing how RootCause Assistant works: You Ask, Assistant Orchestrates, Engines Compute, Result plus Evidence

The Assistant is an orchestration layer. Your question triggers precise tool calls to causal engines — the numbers come from the math, not from AI pattern-matching.

*** ### Accessing the Assistant Click the chat icon in the bottom-right corner of the screen. The Assistant panel slides open and is available throughout the platform — whether you are viewing a Data View, exploring a Digital Twin, or writing a report. It adapts to your current context: on a Digital Twin page it can run simulations directly; on a Report page it can help add content. *** ### What you can do **Ask questions about your data** > "What's the average churn rate across all customers?" "Show me the distribution of customer tenure" "What columns are in the Sales dataset?" The Assistant executes queries against your data and returns results as tables, charts, or summary statistics — each with an evidence reference you can verify. **Run causal simulations** > "What happens to churn if we offer free tech support?" "Find the optimal marketing spend to maximise conversions" "What's driving customer churn?" "What would it take to reduce churn by 20%?" The Assistant calls the appropriate simulation type — intervention, optimisation, explanation, or counterfactual — runs it against your Digital Twin, and presents computed results with full traceability. **Navigate the platform** > "Open the Revenue Digital Twin" "Show me the customer 360 Data View" "Take me to last month's board report" **Get help** > "How do I upload a file?" "What's the difference between intervention and counterfactual?" "Explain what the causal graph is showing me"
RootCause Assistant conversation showing a data query returning average churn rate, followed by a simulation of offering free tech support with key findings and causal pathways

Two questions in one session: a data query returning the average churn rate (26.27%), then a simulation showing that offering free tech support would reduce churn by roughly 8.5% through four identified causal pathways.

*** ### Evidence and traceability Every result from the Assistant carries an evidence reference. Click it to see the query or computation that produced the result, the source data used, the Digital Twin version, and the simulation parameters. **Example:** > **You:** What's the predicted impact of a 10% price increase on revenue? > > **Assistant:** Based on the Revenue Twin, a 10% price increase is predicted to reduce revenue by 4.2% (95% CI: 3.1%–5.3%). \[Evidence: SIM-2847] For important decisions, click through to the evidence. Verify the query was correct, the data was appropriate, and the computation makes sense. *** ### Context mentions Use `@` to reference specific objects in your workspace: * `@Customer_360` — a Data View * `@Revenue_Twin` — a Digital Twin * `@Q4_Report` — a report > "Run an intervention on @Revenue\_Twin to see what happens if we increase marketing spend by 20%" Context mentions eliminate ambiguity about which object to use for a query or simulation. *** ### Rich responses The Assistant returns structured results, not just text: data previews, charts, KPI cards, causal graphs, simulation results, and tables. Each includes an evidence link back to the underlying data or computation. *** ### Session context Within a session, the Assistant remembers what you have discussed — follow-up questions can reference earlier results without repeating yourself. Across sessions, the Assistant remembers your workspace structure but not previous conversation details. *** ### Tips * **Be specific** — "What's the average revenue per customer in Q4 from @Sales\_Data?" gets a better result than "Tell me about revenue" * **Use `@` mentions** — reference specific objects to avoid ambiguity * **Ask one thing at a time** — break complex requests into steps * **Check the evidence** — for decisions that matter, click through and verify *** > **BETA:** The RootCause Assistant is in active development. Capabilities are expanding and some responses may require verification. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.rootcause.ai/more-details/rootcause-assistant.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.