What I like most about Deepnote is how seamlessly it brings collaboration, data science workflows, integrations, and AI assistance into a single platform. Teams can work together in real time on complex projects without constantly switching between tools.
Its intuitive, well-designed interface makes notebooks easy to organize and use, while its integrations and built-in capabilities support a wide range of AI and data science applications.
Overall, Deepnote stands out for its combination of power, flexibility, and ease of use. Review collected by and hosted on G2.com.
One area where Deepnote could improve is its support for software testing and education-focused workflows. More seamless unit-testing capabilities within notebooks would make it easier to validate code and maintain quality in complex projects.
In academic settings, built-in autograding tools and integrations with learning management systems such as Canvas, Blackboard, or Moodle would also be highly valuable. My students use Deepnote for collaborative group projects, and features for distributing assignments, tracking submissions, and providing automated feedback would make the platform even more effective for teaching. Education is a substantial market, and these capabilities could help Deepnote serve instructors and students more comprehensively. Review collected by and hosted on G2.com.