Evidence-backed data visualization and sharing workspace

Reduce tool sprawl while keeping one traceable path from raw data to a shared, reviewed visualization. For data and analytics teams in mid-sized companies who build and share dashboards, convert connected data sources, query logic, transformation steps and team permissions into an approved interactive visualization linked to its evidence. The benefit is a testable hypothesis, measured through accepted shared visualizations per analyst hour and corrections after publication; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect connected data sources, query logic, transformation steps and team permissions, then follow this sequence: 1. Connect to external databases, warehouses and files. 2. Clean and restructure data for analysis. 3. Write and edit queries in an interactive editor. 4. Accept natural language questions and translate them into queries. 5. Convert JSON, YAML, CSV and XML into diagrams. 6. Generate charts and diagrams from prepared data. 7. Edit, navigate and debug visual structures in real time. 8. Search and filter nodes within diagrams. Resolve uncertain cases with qualified reviewers, approve approved interactive visualization linked to its evidence, and measure accepted shared visualizations per analyst hour and corrections after publication against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One approved data model and permission set; final data interpretation and publication checks remain with the data owner. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve data lineage, source attribution, access permissions and usage rights. Data owners approve substantive changes and publication scope. One approved data model and permission set; final data interpretation and publication checks remain with the data owner. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

What to build first

Pilot scope: One approved data model and permission set; final data interpretation and publication checks remain with the data owner. Implement one approved input format, a bounded representative case set and the first two task modules: connect to external databases, warehouses and files; clean and restructure data for analysis. Support the third module with operator review: write and edit queries in an interactive editor. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

What it can connect to

Customer-owned databases, warehouses and files. Cloud storage, browser extension and publishing destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

The screens in detail

Primary screens: Data source and query setup, Editable visualization canvas, Review and sharing. Use a thumbnail gallery for projects, a large central canvas for charts and diagrams, and a right-hand panel for query logic, transformation steps, permissions and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant chart or node. Make the task-specific outcome approved interactive visualization linked to its evidence visible beside its evidence, review state and value baseline.