Jason Hillary

You shouldn’t have to rebuild your work just to ship it. With Zerve Deployments, go from notebook → production without leaving your workspace. Deploy apps, APIs and reports alongside the work that created them. No context switching. No separate deployment platform. ↓

Every broken environment started with "just pip install it." Zerve environments let you define and version your Python, R, and Linux packages in one place. Upload a requirements.txt or pyproject.toml, reuse across projects, run multiple environments in one workflow, and go from dev to deployment without the usual mess. One less thing between you and the actual work. #Python #DataScience

Most notebooks die with the person who wrote them. Zerve changes that: → Drag and drop your notebook → Auto-parsed into a DAG → Run with full state and context → Deploy an API or app in minutes Already have notebooks? This is the fastest path forward.

Recurring work is where value compounds. Zerve scheduling: → Run on-demand or on a schedule → Auto-versioning so updates don't break prod → Completion + error notifications → Full cron support Set it once. Trust it. Iterate safely.

Every Zerve cell run is fully inspectable. Code that executed. Output produced. Errors. Runtime. No more guessing what broke or why. Just click back and see exactly what happened. Debugging and collaboration, fixed. #DataScience #DeveloperProductivity

The #1 frustration with AI agents isn't the model. It's losing context. Zerve persists execution state automatically. Outputs, variables, everything. So your agent always knows what already ran. No starting over. No re-running. Just momentum. #AIAgents #DataScience #AgenticDataWorkspace #DecisionGradeDataWork

Zerve + @arcee_ai We’re teaming up to bring automated, cost-efficient #AI model selection into your workflows—via Arcee Conductor on Zerve. Faster runtimes, lower costs, smarter pipelines. Join the livestream July 9 @ 12 noon ET: linkedin.com/events/73432633… #SLMs #LLMs