ng>Airflow DAGs</strong>, giving data scientists flexibility in experimentation. But transitioning to real-time execution threatened this agility. Every change would now require backend engineering support, <strong>slowing down iteration cycles</strong>.</p>
<p>That’s when the idea struck:<br>
<!-- -->We needed a <strong>framework for real-time DAG execution</strong>—one that preserved the same flexibility as Airflow but worked for <strong>streaming data</strong>.</p>
<p>This moment shaped the <strong>n