Build a Custom Business Intelligence Dashboard Using AI in Minutes
Turn a plain-English description of your Business Intelligence Dashboard into a production-ready build, from design to deployment, in minutes. No code needed.
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Emergent Key Features for Building a Business Intelligence Dashboard
Governed dashboards as software your whole organisation can open, without a seat licence for every person who needs to read them.
Warehouse Native Queries
Generated code queries BigQuery, Snowflake and Postgres directly with sensible aggregation, so performance holds on tables your business actually has.
One Definition per Metric
Measures are calculated in a single place and reused, which prevents the drift that happens when each dashboard implements revenue slightly differently.
Genuine Self Serve
Filters, groupings and drilldowns are functional, so a stakeholder answers the follow up question themselves instead of filing a request.
Multi Tenant Embedding
Dashboards can be embedded in your product scoped to each customer's data, turning internal BI work into a feature you ship.
Row Level Access Control
Permissions can restrict what each role or region sees from the same build, so governance does not require maintaining parallel dashboards.
No per Viewer Licensing
Access is a web app rather than a seat, which means giving the whole company data access is not a budget conversation.
Business Intelligence Dashboard Use Cases You Can Build in Minutes

Let People Answer Their Own Questions
Users pick a metric, a dimension to group by and a date range, then see the result as a chart and a table with drilldown to record level. Saved views mean they return to their own analysis.
window.awbMockup = { selfServeExploration: "Build a self serve BI dashboard on a warehouse table where users pick a metric, a dimension to group by and a date range, then see the result as a chart and a table with drilldown to record level, saved views they can return to, and an export of the current selection.", semanticLayer: "Build a governed metrics dashboard where every measure has a single defined calculation, showing the metric catalogue with its definition, owner and source table, alongside dashboards that consume those definitions so a change to a metric updates consistently everywhere it appears.", embeddedCustomerAnalytics: "Build an embedded analytics dashboard for customers to view inside your product, showing only their own data through a tenant identifier, with usage metrics, trends against their prior period, benchmark comparison against anonymised averages, and styling that matches the host application.", executiveBiSummary: "Build an executive BI dashboard summarising company performance from the warehouse across revenue, retention, unit economics and efficiency, showing each against target and prior period, with automatic callouts naming the largest movers and a drilldown from every headline into its underlying detail."};

One Definition for Every Metric
A governed catalogue where each measure has a single calculation, owner and source table, with dashboards consuming those definitions. Change a metric once and it updates consistently everywhere it appears.
window.awbMockup = { selfServeExploration: "Build a self serve BI dashboard on a warehouse table where users pick a metric, a dimension to group by and a date range, then see the result as a chart and a table with drilldown to record level, saved views they can return to, and an export of the current selection.", semanticLayer: "Build a governed metrics dashboard where every measure has a single defined calculation, showing the metric catalogue with its definition, owner and source table, alongside dashboards that consume those definitions so a change to a metric updates consistently everywhere it appears.", embeddedCustomerAnalytics: "Build an embedded analytics dashboard for customers to view inside your product, showing only their own data through a tenant identifier, with usage metrics, trends against their prior period, benchmark comparison against anonymised averages, and styling that matches the host application.", executiveBiSummary: "Build an executive BI dashboard summarising company performance from the warehouse across revenue, retention, unit economics and efficiency, showing each against target and prior period, with automatic callouts naming the largest movers and a drilldown from every headline into its underlying detail."};

Ship Analytics Inside Your Product
An embedded dashboard scoped to each customer through a tenant identifier, showing their usage, trends against their prior period and benchmark comparison, styled to match the host application.
window.awbMockup = { selfServeExploration: "Build a self serve BI dashboard on a warehouse table where users pick a metric, a dimension to group by and a date range, then see the result as a chart and a table with drilldown to record level, saved views they can return to, and an export of the current selection.", semanticLayer: "Build a governed metrics dashboard where every measure has a single defined calculation, showing the metric catalogue with its definition, owner and source table, alongside dashboards that consume those definitions so a change to a metric updates consistently everywhere it appears.", embeddedCustomerAnalytics: "Build an embedded analytics dashboard for customers to view inside your product, showing only their own data through a tenant identifier, with usage metrics, trends against their prior period, benchmark comparison against anonymised averages, and styling that matches the host application.", executiveBiSummary: "Build an executive BI dashboard summarising company performance from the warehouse across revenue, retention, unit economics and efficiency, showing each against target and prior period, with automatic callouts naming the largest movers and a drilldown from every headline into its underlying detail."};

Give Leadership the Warehouse in Plain Terms
Company performance across revenue, retention, unit economics and efficiency, each against target and prior period, with automatic callouts naming the largest movers and drilldown into the detail behind them.
Give Leadership the Warehouse in Plain Terms
Company performance across revenue, retention, unit economics and efficiency, each against target and prior period, with automatic callouts naming the largest movers and drilldown into the detail behind them.
Build a custom business intelligence dashboard in 4 simple steps
Turn your warehouse into governed, explorable dashboards without per seat BI pricing or a queue for every new request.
Start with the metric definitions your business agrees on and the dimensions you slice by. Emergent builds a consistent calculation layer around them, so revenue means the same thing in every view rather than being redefined per report.
Link BigQuery, Snowflake, Redshift or Postgres, including the models your team already maintains. Emergent reads the schema, writes efficient queries against large tables, and respects the transformations you have built rather than duplicating them.
Ask to alter how a measure is calculated, add a dimension or expose a new drilldown, and every dashboard consuming that definition updates. Governance changes stop requiring a project.
Deploy dashboards with filters and drilldowns that stakeholders can use themselves, on one link with access rules. Requests for a slightly different cut stop arriving in your queue because the view already answers them.
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Why choose Emergent?
Most tools give you a demo you have to rebuild. Emergent gives you a product that is ready to run.
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Choose the plan that fits your building ambitions. From weekend projects to enterprise applications, we've got you covered.
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