Talk to your data in plain English. Automated monthly reports. Executive dashboards with generated insights. No analyst dependency, no waiting.
# "Which 5 plants had the highest throughput # variance vs target last quarter, by month?" → Intent parsed · 2 databases relevant ✓ → SQL generated · joins + aggregation ✓ → Query executed · 5 plants returned ✓ → Chart rendered · variance by month ✓ ✓ Answer + visual + plain-English summary · 6.8s
Business users and leadership ask in plain language; a multi-agent pipeline parses intent, writes and runs the SQL, and returns visuals with a written explanation.
Four intelligence agents that turn data into decisions — without SQL, without waiting.
Anyone can query enterprise databases in plain English — visual results and written explanations included.
Reporting cycles eliminated — data consolidated across systems, variance computed, and the management narrative written automatically.
Real-time dashboards with generated alerts, anomaly detection, and plain-language summaries of what changed and why.
Continuous OEE, throughput, and cost analysis — root causes identified and recommendations surfaced proactively.
Each question flows through a specialised pipeline — visible and auditable at every step.
Understands intent and context, clarifies ambiguity, and determines which databases and tables matter.
Converts intent into precise SQL and executes it — joins, aggregations, and filters across one or many databases.
Computes the final answer, renders the charts, and writes a plain-English explanation of what was found.
Plant managers, finance, and leadership self-serve — analysts stop being a bottleneck for routine questions.
The generated SQL, the sources, and the reasoning are always inspectable — trust through visibility.
Row- and table-level access follows your existing data permissions — people only query what they may see.
Metrics defined once, reused everywhere — the variance in Tuesday’s report matches Friday’s dashboard.
Queries are schema-grounded and validated before execution; ambiguous questions trigger a clarifying question instead of a guess, and every query is inspectable.
Major warehouses and databases — SQL Server, Postgres, Oracle, Snowflake, SAP HANA and more — queried individually or across sources.
Yes — queries execute under the asking user’s entitlements, so the agent can never return data the user couldn’t access directly.
It complements them — dashboards stay for monitoring; the agent handles the ad-hoc questions and narrative reporting that BI backlogs are made of.
Bring three real business questions to the demo — watch them answered in seconds.
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