AI superpowers for all

Companies of all sizes—from early startups to large enterprises—leverage AI in apps to drive outcomes

More revenue growth

Turbocharge product experiences with AI to grow customer adoption, account expansion, and net new acquisitions.

More efficient operations

Leverage LLMs to reduce development costs and accelerate time to market. Keep your team focused on your core.

Continuous improvement

Run more experiments with greater agility and tighter feedback loops to learn faster and execute smarter.

Any data, in any app experience

Connect any data source to start building apps immediately with beautiful out of the box components for Tables, Charts, Maps, Lists, Alerts, Automations and more—no engineering required.

Completely customize and integrate with full-code extensibility.

Make apps
a team sport

Workspaces for governed collaboration

Real-time comments and tasks make it easy to work together live or leave feedback async. Manage for individuals or groups.

Tools for all skill levels

Our consumer-grade tools make it easy for anyone to start building. Enterprise-grade extensibility enables teams to build for any level of complexity.

Modern version control for safe deployment

Maintain development best practices as you enable more people to build more apps. Leverage built-in branching and version history... or manage it all in Git.

Empower domain experts, safely

Let the people closest to the business problem build better solutions with the full trust of their technical teams.

Securely share or embed app experiences with fine grained access controls, and rest assured with performance monitoring, reliability safeguards and Git integration.

Crawl, walk, run

Manage all of your data apps across their full development lifecycle.

No data, no problem

If you can't connect the real data, we'll automatically generate a synthetic data set so you can test live, functional prototypes for higher resolution feedback.

Run multiple experiments in parallel to better validate use case requirements and your app specifications.

Launch, measure, iterate

When you're ready to push your app into production  with real users, track usage analytics for insights and monitor logs to troubleshoot any issues.

To iterate, simply create a new branch, invite your collaborators, and run tests to make sure your improvements are working before you release them.

Drive new revenue

Extend smart data apps to your customers, and charge a premium for your most valuable features.

Leverage our monetization tools out of the box to offer custom pricing models and configurations.

Frequently asked questions

1.  What is a Data App Platform?
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A data app platform is software that helps people efficiently build solutions to business problems and make work easier. Think of it as a set of building blocks that are straightforward to assemble into useful things.

For example, consider a customer-facing usage analytics dashboard. Rather than requiring a software engineering team to build all the individual visualizations, filters, pivots, queries and access controls from scratch, companies can leverage pre-built parts out of the box and focus their technical teams on higher value work.

This often means fewer people—including non-technical domain experts—can build what they need for themselves and deliver better solutions faster and cheaper.

2.  What is Inventive used for?
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Inventive is for product and engineering teams across the application development lifecycle and shines most when helping those teams drive more and better 'product-market-fit.'

With Inventive's data app platform, they can rapidly: prototype with live data to learn detailed technical specifications; ship near real-time operational solutions at full scale; run multiple experiments in parallel across different user segments to validate user demand for various solutions; collaborate across teams and organizations to evolve the underlying data model with tighter feedback loops; monitor, manage and maximize custom app adoption, performance and reliability; tailor and monetize new features to specific customer segments, and so on.

3.  Why use Inventive vs. Embedded analytics?
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Historically, companies considering the "build vs. buy" decision for their data experiences have often turned to "embedded business intelligence and analytics" (a.k.a. "embedded analytics") to provide largely static, informational reports and dashboards.

In contrast, Inventive's approachable and flexible data app building blocks lets companies provide higher value and higher complexity interactive application experiences, much faster and cheaper. Think: operational apps where users to get their work done (vs. limited and often generic charts) in days, not quarters.

4.   How does Inventive use AI For its Data App Platform?
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Born in the "Era of AI", Inventive has been architected to accelerate teams looking to augment their users with "smart" AI-powered data apps.

Because Inventive sits on top of the modern data stack to help teams with the last mile of delivering great data app experiences, data science teams can write their model outputs to the database, or they can leverage integrations that pass those model outputs to Inventive directly.

Behind the scenes, Inventive also leverages LLMs and other ML models to help companies deliver their smarter data app experiences in easier and faster ways.