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A new era for data work: autonomous Deepnote AI

By Gabor Szalai

Updated on July 31, 2023

Deepnote's autonomous AI assistant is reshaping data workflows by independently handling complex tasks, from start to finish.

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In today's data landscape, generative AI has emerged as a game-changer. AI assistants are no longer a distant fantasy, they're already helping us in composing complex analytical code from natural language, fixing errors, writing SQL queries, creating visualizations, and condensing findings into succinct reports.

These developments are impressive, indeed, making exploratory data analysis more accessible for novices while vastly enhancing the productivity of seasoned data professionals. However, they all share a common shortfall: each solution is confined to one specific segment of your workflow, always requiring your keen oversight to review, refine, and modify the results.

What if AI could be more than just a diligent intern? What if it could be an autonomous collaborator? Envision a virtual team member who doesn't just take orders but understands complex tasks, breaks them down into actionable steps, and autonomously executes them. Such an AI agent represents the next frontier in AI development.

We're excited to introduce an upcoming capability that will embed this powerful potential directly into the world of data notebooks. For an early glimpse of what’s to come, take a look at the video below. It was a truly rewarding moment for our team to see it in action for the first time.

AI as your collaborator

Deepnote’s autonomous assistant isn't merely a tool for increasing productivity; it has the power to fundamentally transform your daily work processes. Picture this: you arrive at work to find four pressing data queries waiting for you. Three of these tasks are relatively routine, but as we know, 'routine' doesn't necessarily mean 'quick.' Instead of spending your valuable time ticking off these standard tasks before delving into the more complex problem, you can now delegate them to Deepnote AI.

All you need to do is open a new notebook and provide a basic initial instruction. From there, Deepnote AI will construct a strategic plan to tackle the question at hand. Its actions might include writing SQL queries to extract the necessary data, implementing a range of data transformations, and carrying out visualization operations using Python. Once it's completed these steps, it doesn't stop there: it summarizes the findings for you and, if needed, suggests potential next steps. In essence, it's not just doing your work - it's thinking along with you.

The magic behind the scenes

Several crucial elements within Deepnote make it a perfect setting for an autonomous assistant to handle your data tasks.

Context-Aware Intelligence. Deepnote AI isn't navigating in the dark: it has a comprehensive understanding of your workspace, integration schemas, and file systems. It employs your organizational knowledge and data structures in devising effective execution plans, so it's as in sync with your organization as you are.

Dynamic Interaction with Outputs. As a computational medium, a notebook allows the autonomous assistant to run and evaluate code in a fluid manner. This functionality creates a feedback loop, enabling Deepnote AI to self-correct, resolve potential errors, and adapt its plans according to the results.

Transparency and Reproducibility. Deepnote AI is an open book, not a black box. The notebook structure - where code and outputs live side-by-side - guarantees the full transparency and reproducibility of the autonomous assistant's work.

Continuous Operation. Need to step away from your notebook? No problem - Deepnote AI continues to labor in the background. When you return, your results will be waiting. Plus, you can deploy Deepnote AI across multiple notebooks at once, giving your productivity an exponential boost.

Coming soon

We are currently fine-tuning our autonomous AI to ensure it becomes a reliable companion while working in Deepnote notebooks. We are excited to roll out these capabilities soon, with our Team and Enterprise customers given priority access.

We’d also love to hear your feedback! If the idea of an autonomous assistant sparks your interest, please visit our Product Portal, cast your vote on this feature and leave us a message.

Gabor Szalai

Head of Product Management

Gabor is the Head of Product Management at Deepnote, where he loves tackling challenging problems with a team of engineers who always outsmart him. A technology enthusiast and sci-fi fan, he's highly optimistic about the future of AI. Beyond his professional life, he's a compulsive reader, enjoys lifting heavy objects, and juggles far too many interests.

Follow Gabor on LinkedIn


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