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Des dashboards qui se construisent depuis une question, pas un ticket

Posez en langage naturel et recevez un dashboard gouverné—drill-down expliqué, embarqué dans vos outils, avec l'IT qui tient la couche sémantique.

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The problem

Dashboards die in tickets, business questions wait weeks

  • Dashboard tickets queue in IT

    Business asks; IT translates; analyst builds; revisions cycle. By the time the dashboard ships, the question has changed or the decision has been made without data.

  • Business users blocked at self-service

    Self-service tools are powerful for analysts and intimidating for everyone else. Business users either ask IT or build broken spreadsheets.

  • Semantic definitions drift across tools

    What is 'active customer'? It depends on which dashboard you open. Without a governed semantic layer, every team reports a different number.

  • NL queries hallucinate without grounding

    Generic NL-to-SQL tools invent column names, mix tables, and produce confidently wrong numbers. Trust collapses after the first board meeting.

Fonctionnement

Semantic layer governs, NL generates, business self-serves

Étape 1

Govern the semantic layer

Metrics, dimensions, joins, and policies defined once and reused across NL queries—the only source of truth for what 'active customer' means.

Étape 2

Generate from natural language

Users ask in plain language; the system grounds the query in the semantic layer, generates the dashboard, and explains the steps it took.

Étape 3

Embed and govern

Dashboards embed into Teams, Slack, Notion, and the CRM; IT sees usage, lineage, and quality—change tracking and approval included.

Flow adapts to your warehouse, semantic layer, and embedding surfaces.

Des dashboards qui se construisent depuis une question, pas un ticket

Ce qui est inclus

Everything you needfor governed self-service analytics

NL generation, semantic layer, embedding, and governance in one layer on Synapse—delivered with IT owning the metric definitions and business users self-serving.

NL dashboard generation

Natural-language queries produce dashboards grounded in the semantic layer—no hallucinated metrics.

Semantic layer & lineage

Metric and dimension definitions managed centrally with version control and column-level lineage.

Drill-down with explanation

Every chart drills into the data with a plain-language explanation of how the number was built.

Embed in productivity tools

Dashboards live where work happens: Teams, Slack, Notion, CRM—not just in BI.

Governance gates

Approval workflows for new metrics; usage and quality telemetry visible to IT and data product owners.

Change tracking

Every metric change tracked with reviewer, reason, and downstream impact—rollback when needed.

Propulsé par Synapse

Résultats

What changes when this runs in production

Results vary by data maturity, semantic layer quality, and adoption support. We scope honestly before we promise precisely.

−70%

dashboard ticket queue depth

Orientative—depends on current self-service maturity.

10×

more business users active in analytics monthly

Orientative—based on early implementations.

Single

semantic layer for all NL-generated dashboards

Notre façon de travailler

From first call to production—without the usual drag

Assess

Week 1–2

Map current BI estate, semantic layer maturity, top recurring questions, and the dashboard backlog.

Design

Week 3–4

Define metric ownership, NL query policy, embedding surfaces, and governance workflow.

Build

Week 5–8

Set up semantic layer, integrate NL generation, pilot embedding in one team's flow.

Scale

Week 9+

Roll out by team, expand semantic coverage, tune governance, retire legacy dashboards.

Timelines vary by BI estate complexity, semantic layer maturity, and adoption support.

Commencer

Ready to make dashboards a question, not a ticket?

No commitment. We start with a scoped session to map your BI estate, semantic layer, and backlog.

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