Ask better questions. Get clearer answers.
We combine multiple data sources into one reproducible query, answering your most complex questions and visualizing the results as a fully interactive, parameter-driven graph.
How It Works
Ask once. Compile deterministically.
You start by asking a question in plain English. Instead of re-interpreting that question every time, our platform deeply analyzes it and compiles it into a deterministic, parameterized query.
That query can span multiple data sources—databases, ERPs, CRMs, project management tools, and more—and becomes a stable analytical definition rather than a one-off prompt.
Once compiled, the query does not change. Inputs like time ranges, filters, entities, and thresholds are exposed as parameters you can control directly—without writing a new prompt or regenerating logic.
This allows teams to reuse the same query across scenarios, create reports that are directly comparable, and explore complex questions with confidence. The results are rendered as an interactive graph, giving you full control over how the data is explored and visualized.
The result: consistent answers, reproducible analysis, and reports you can trust over time.
Use Cases
Built for production analytics
For product owners, managers, and analysts who need reliable, auditable insights without technical overhead.
Engineering Manager
Which deployments caused incidents that affected Enterprise customers?
Project Manager
Which epics are over budget and slipping deadlines by team?
Support Manager
Which high-revenue customers are opening tickets after using feature X?
Deployments Causing Enterprise Incidents
Last 90 days • 10 deployments flagged
Adjust Parameters (No AI regeneration)
Epic Budget & Timeline Analysis
All Quarters 2024 • 16 epics tracked
Adjust Parameters (No AI regeneration)
| Epic | Team | Quarter | Budget | Spent | Status | Slippage |
|---|
Why Different
The problem with traditional and chat-based analytics
Agent and LLM-based systems regenerate queries on every request. This breaks determinism and makes time comparisons unreliable.
Traditional and Chat-Based Analytics
Query control requires expertise or re-prompting
To change or refine a query, users must either learn a domain-specific language or rely on an LLM to regenerate the query with new parameters.
AI-driven queries are inherently unstable
When logic is regenerated by AI, even small changes in interpretation can alter how data is fetched—leading to inconsistent results.
Results are difficult to compare over time
Because the underlying query can change between runs, comparisons across reports or time periods can drift and become unreliable.
Analysis is limited to one data source at a time
Most platforms query a single system per analysis, making it hard to answer complex questions that span multiple tools and datasets.
Persistent Analytics
Our Approach
Logic generated once
AI interprets your question a single time, converting it into a deterministic, parameterized query. The underlying logic is never regenerated, ensuring consistent calculations.
Deterministic results
The same query always produces the same results—every time, forever—eliminating inconsistencies and unexpected variations.
Combine multiple data sources
Queries can span databases, ERPs, CRMs, project management tools, and more, delivering unified insights that reflect your entire ecosystem—not just one system at a time.
Reliable time comparisons
Because the logic never changes, you can compare reports across any period with confidence, uncovering trends and patterns that truly reflect your data.
Auditable trends across any period
Every calculation is traceable and reproducible, making it easy to validate insights and maintain compliance.
Parametrized flexibility
Adjust inputs like time ranges, filters, or entities without rewriting queries or prompting AI again. One definition, infinite perspectives.
Analytics you can trust
Stop regenerating queries. Start building persistent analytics that deliver consistent results, every time.