Build a Custom Predictive Analytics Dashboard Using AI in Minutes
Describe your Predictive Analytics Dashboard in plain English and create a production-ready build, from design and development to deployment, in minutes. No code needed.
Trusted by Builders Worldwide
Active Builders Worldwide
Apps Successfully Created
Countries Globally Reached
Emergent Key Features for Building a Predictive Analytics Dashboard
Scores delivered as a ranked worklist with the reasoning shown and accuracy monitored over time.
Predictions as an Action List
Scored records arrive ranked with owners assigned, so a model produces work rather than a report somebody reads occasionally.
Every Prediction Stored with the Outcome
Forecasts are retained against what actually happened, which is what makes accuracy measurable rather than asserted.
Drift Detection
Input distributions are compared with the training period, so a model degrading because the world changed is caught before decisions suffer.
Segment Level Accuracy
Performance is reported by segment, revealing where the model is unreliable rather than presenting one overall figure.
Explanations per Record
The factors driving each individual score are shown, which is what allows the person acting on it to trust and use the prediction.
Threshold Effects Modelled
The trade off from moving the action threshold is calculated, so the cutoff is an operational decision rather than a default.
Predictive Analytics Dashboard Use Cases You Can Build in Minutes
Deliver Predictions as Work, Not as a Chart
Current records scored by likelihood of the predicted outcome with the top contributing factors for each, the recommended action, cases already actioned with outcome recorded, high scoring cases not yet reviewed and the expected value of acting.
window.awbMockup = { predictionWorklist: "Build a predictive analytics dashboard showing current records scored by likelihood of the predicted outcome, ranked with the top factors contributing to each score, records above the action threshold assigned to an owner, actions taken and their result, and outcomes for records that were and were not acted on.", modelAccuracy: "Build a model performance dashboard comparing predictions against actual outcomes over time, showing accuracy, precision and recall at your chosen threshold, performance by segment to reveal where the model is weakest, the effect of moving the threshold, and accuracy trend since the model was last retrained.", modelDrift: "Build a model monitoring dashboard showing how the distribution of input data has shifted since training, features whose distribution moved most, prediction distribution against the training period, accuracy decline over recent periods, records the model is least confident about, and a signal when retraining is warranted.", featureInsight: "Build a model explanation dashboard showing which inputs most influence predictions overall, how each feature affects the outcome across its range, features that have become more or less important since training, correlated inputs adding little independent value, and a plain language explanation for any individual prediction."};
Check the Model Beats the Obvious Rule
Predictions against actual outcomes over time with accuracy, precision and recall at your chosen threshold, performance across score bands, comparison against a simple baseline rule and how accuracy changed since the last retrain.
window.awbMockup = { predictionWorklist: "Build a predictive analytics dashboard showing current records scored by likelihood of the predicted outcome, ranked with the top factors contributing to each score, records above the action threshold assigned to an owner, actions taken and their result, and outcomes for records that were and were not acted on.", modelAccuracy: "Build a model performance dashboard comparing predictions against actual outcomes over time, showing accuracy, precision and recall at your chosen threshold, performance by segment to reveal where the model is weakest, the effect of moving the threshold, and accuracy trend since the model was last retrained.", modelDrift: "Build a model monitoring dashboard showing how the distribution of input data has shifted since training, features whose distribution moved most, prediction distribution against the training period, accuracy decline over recent periods, records the model is least confident about, and a signal when retraining is warranted.", featureInsight: "Build a model explanation dashboard showing which inputs most influence predictions overall, how each feature affects the outcome across its range, features that have become more or less important since training, correlated inputs adding little independent value, and a plain language explanation for any individual prediction."};
Catch the Degradation Nothing Else Reports
How the distribution of input data has shifted since training per feature, features drifted beyond tolerance, the share of predictions falling in unfamiliar ranges, accuracy trend since the last retrain and a recommendation on retraining.
window.awbMockup = { predictionWorklist: "Build a predictive analytics dashboard showing current records scored by likelihood of the predicted outcome, ranked with the top factors contributing to each score, records above the action threshold assigned to an owner, actions taken and their result, and outcomes for records that were and were not acted on.", modelAccuracy: "Build a model performance dashboard comparing predictions against actual outcomes over time, showing accuracy, precision and recall at your chosen threshold, performance by segment to reveal where the model is weakest, the effect of moving the threshold, and accuracy trend since the model was last retrained.", modelDrift: "Build a model monitoring dashboard showing how the distribution of input data has shifted since training, features whose distribution moved most, prediction distribution against the training period, accuracy decline over recent periods, records the model is least confident about, and a signal when retraining is warranted.", featureInsight: "Build a model explanation dashboard showing which inputs most influence predictions overall, how each feature affects the outcome across its range, features that have become more or less important since training, correlated inputs adding little independent value, and a plain language explanation for any individual prediction."};
Explain a Score to the Person Acting on It
Which inputs most influence predictions overall, the direction of each relationship, features whose importance shifted since training, cases where the model and human judgement disagreed and features with missing data affecting reliability.
Explain a Score to the Person Acting on It
Which inputs most influence predictions overall, the direction of each relationship, features whose importance shifted since training, cases where the model and human judgement disagreed and features with missing data affecting reliability.
Build a custom predictive analytics dashboard in 4 simple steps
Put model predictions in front of the people who act on them, with accuracy and drift visible, so forecasts are trusted and used.
Start with the outcome you are predicting, the records to be scored, the threshold at which someone should act and who receives the list. Emergent builds the prediction and the action list together, because a score nobody acts on changes nothing.
Link the historical records containing both the inputs and the outcomes. Emergent trains against your own history, scores current records and stores each prediction with what actually happened, so accuracy becomes measurable.
Ask to add a feature, change the prediction window, alter the score threshold or retrain on more recent data, and the worklist and accuracy views rebuild around it.
Publish one link where the team sees scored records ranked by likelihood with the factors driving each, and analysts see model accuracy and drift. Predictions arrive as work rather than as a report.
More things you can build
with Emergent
AI Website Builder
Build and publish responsive websites with AI — from landing pages to complete websites.
AI App Builder
Create and launch mobile apps with AI, without the complexity of traditional app development.
AI Web App Builder
Build and ship fully functional web apps with custom interfaces, logic, and workflows.
AI Dashboard Builder
Create interactive dashboards to visualize data, track KPIs, and manage business operations.
AI SaaS Builder
Build complete SaaS products with user accounts, subscriptions, dashboards, and core product workflows.
AI CRM Builder
Build custom CRMs for managing contacts, leads, pipelines, campaigns, and automated workflows.
AI Agent Builder
Create AI agents that can understand tasks, use tools, automate workflows, and work across your business.
Build Your Own
Start with any idea and build exactly what you need with AI — no templates or limits.
Why choose Emergent?
Most tools give you a demo you have to rebuild. Emergent gives you a product that is ready to run.
| Comparison | Other Tools |  |
|---|---|---|
| Built for | Demos and MVPs | Products you keep growing |
| What you get | Front end shell only | Full stack, wired end to end |
| Backend and database | Set it up yourself | Built and connected for you |
| Customization | Surface level styling | Deep workflow control |
| Integrations and APIs | Manual glue work | Connected from a prompt |
| Code ownership | Locked to the platform | Clean code you can export |
| Time to launch | Weeks of patching and setup | Live the same day |
Pick the Pricing Plan That Works for You
Choose the plan that fits your building ambitions. From weekend projects to enterprise applications, we've got you covered.
No credit card required*
Find the Right Dashboard Builder
for Your Business
Frequently Asked Questions
Your Questions, Answered
Don't change this element unless you know what you are doing
on Emergent today
