Sharpe is a Data Science agent, built for time-series and financial analysis. Execute complete studies in Jupyter Notebooks on your data: hosted, on your machine, or on your cloud.
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Sharpe is a Jupyter-native agent that takes a research request and delivers a completed notebook, ready for you to review and iterate. It connects to your data, plans multi-step analyses, writes and executes code, and iterates until the work is done.
Designed from the ground up for quantitative analysis — not a chatbot with a code interpreter bolted on.
Learns your preferred data sources, analysis patterns, and formatting conventions. No prompt engineering required.
Reference Confluence pages, datasets, or notebooks and Sharpe pulls in the relevant context automatically.
Sharpe is leverage on your analytical expertise. Purpose built to provide exactly the context you need to maintain methodological rigor and understanding, Sharpe traces results and assumptions deterministically, for provably correct and reproducible studies.
Preferred data sources, analysis patterns, formatting conventions — Sharpe learns from your team's notebooks and applies those patterns to new studies. No prompt engineering required.
These memories are shared across your team with granular permissions, so best practices accrete naturally as people use the tool. New team members get the benefit of institutional knowledge from day one.
Reference a Confluence page, a Dremio dataset, or another notebook with @ and Sharpe pulls in the relevant context automatically.
Connectors sync incrementally, so the agent always works with current data. The framework is extensible — connect internal tools, wikis, and data catalogs specific to your organization.
Sharpe can work autonomously in a hosted environment, or fully integrate with your existing Jupyter setup. Every notebook is a familiar .ipynbfile, that can run locally, or via your organization's JupyterHub.
You can step through Sharpe's execution, see every cell it writes, every data source it reads, every API it calls, logged with timestamps and diffs. You get a complete record of what happened and why. Add approvals to gate sensitive operations based on your environment and your organization's requirements.
Sharpe supports BYOC, and can be deployed into your VPC, using your pre-existing JupyterHub and Data Infrastructure. Offer Sharpe to your team, in place with your existing tools. Nothing leaves your network boundary.
Try Sharpe for Free.
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$200/ month
All of Sharpe, in a Hosted Environment.
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For Organizations that have Custom Deployment Requirements.
Sharpe is built by a team of engineers and researchers who understand that high performing Data Scientists need a purpose built tool to raise the ceiling on their output. Sharpe understands the full analytical workflow, and is designed to be a force multiplier for your team.