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Releasing AI


As modern development teams keep pace with the growing need for AI innovation, it’s critical their releases are on point. Using Split, teams can bring new AI-backed capabilities to market quickly and safely. Importantly, Split helps teams ensure new AI solutions are performing at their best, driving maximum value for end-users and business.

Delivering new AI models and AI-powered features comes with risk, uncertainty, and unprecedented pressure to stay ahead of the competition.

There’s an expectation to deliver value and ensure nothing breaks or is compromised along the way. That’s why it’s critical to quickly determine whether the AI you release is making things better or worse.

To proceed with confidence, give your teams control and visibility with Split’s Intelligent Feature Management.

Bring New AI to Market Quickly

The market is moving fast, and you need an efficient way of working to keep up. Feature flags change the way you work by decoupling deploy from release. The ability to safely push changes all the way to production without exposing them to customers, allows you to avert risk and quickly deploy AI capabilities without worry. 

Keep all tools, processes, and people moving forward in unison. Easily collaborate on flag set-up, react to changes, and manage the entire feature delivery lifecycle across all stakeholders. 

Do No Harm: Catch Bugs Before They Bite

Gradual rollouts allow you to safely learn about your AI releases without disrupting your entire user base. Release to a small percentage of your users and know when it’s time to move on to the next stage. If there’s an issue, Split will immediately identify it and inform the teams involved, so they can quickly resolve it.

Continuously Improve & Make Frequent Updates

After releasing a new AI model, the job is far from complete. It takes time to fine-tune your model and that involves training  it with new data.  Split automatically watches every metric of every release, creating a continuous feedback loop to help you make the adjustments you need. 

By leveraging causal data, you can understand if the updates you release are impacting performance, experience, or any other metric. This helps you continuously optimize both your  AI model, as well as the UI layer with confidence.

Test & Iterate Without Limitation

    Not sure about the placement of your AI chatbot or how it interacts with your users? What if you’re looking to experiment with different prompts? Split provides you with all the tools needed to run experiments to quickly improve the performance of a model, the AI user experience, and the overall business impact.


Feature flags give you a simple way to launch code without exposing it immediately to users.