Our Mission

Elevating The Impact of Data Science & AI

Zerve platform supports the Data Science & AI community around the world to build better together

Interactive but safe

Refuse to be single threaded

Autonomous & collaborative

Embrace the cloud

Code first

Be portable

Build better

Zerve supports experts to create, discover and collaborate

Reduce time to value

Reduce time to value

Zerve’s underlying stability means data science and ML teams can truly collaborate, iterate quicker and execute faster

Seamless deployment

Seamless deployment

Find the option for deployment that fits you or your team the best

Elevate potential & impact

Elevate potential & impact

Increase your teams potential and elevate their overall impact through coaching and effectively working with them in Zerve

Transparency

Transparency

Zerve enables teams to transparently understand each other’s work, progress towards their goals and to stay on track

A Foundational Shift

Where stable data science meets a collaborative user experience:
Step change architecture — decoupling compute from storage
No more sacrifices — stable and interactive
Coding collaboration — not huddles, meetings or Zooms
Step change architecture — decoupling compute from storage
No more sacrifices — stable and interactive
Coding collaboration — not huddles, meetings or Zooms
Change Log

What’s New

We are continuously improving and enhancing our product to support the data science & AI development community.

Scheduled jobs

Each canvas in Zerve now has its own inbuilt scheduler, making super seamless to run workflows at scheduled intervals.

May 6, 2024

Public canvases

Zerve users can now make their canvases available to be shared publicly

April 30, 2024

AWS Bedrock Prompt v1

v1 of Zerve's bedrock prompt block allows users to select to any of the LLMs hosted on Bedrock and pass prompts within the block to generate output. The prompt block can also be connected to a Python block, which allows variables from the Python block to be passed as inputs to the prompt block.

April 18, 2024

GPU support

Users can now configure code blocks to be run on GPUs, as well as CPUs and lambdas that were already available

April 18, 2024

Hugging Face and AWS Bedrock

Our new integrations with Hugging Face and Bedrock enable users to seamlessly import any model or dataset from Hugging Face and Bedrock into their canvas.

April 18, 2024

Linux & Environment Variables

We've updated our requirements section to support both Linux and environment variables during the requirements build. We've also added logs which will appear when you build custom requirements.

March 25, 2024

Code complete

Using GPT4 and Claude, we've also added code completion copilot

March 18, 2024

SQL on DataFrames

SQL query dataframes directly in Zerve, with true language interoperability

March 8, 2024

AWS Marketplace

Zerve is now available for purchase through AWS Marketplace

February 13, 2024

SQL Connections

Use SQL blocks to query database from within the Zerve and connect to python blocks for further analysis.

January 29, 2024

GitHub Integration

Sync code changes from a canvas to a GitHub repo.

January 27, 2024

Requirements management update

Install linux and environmental variables into your environment manager

January 25, 2023

Collaboration on data industry benchmark report

Zerve showcase video

52%

Overall time savings over seven months

1k hours

Time spent recoding on a single project

2 FTEs

Per project saved on average

6,258

Total collaborative project hours

Ready?

Explore, collaborate, build and deploy with Zerve