Trusted by data users and teams at
You translate between business needs and data. But most of your day is spent wrangling, not advising.
Stakeholders need answers yesterday, but data prep takes hours
Reports rebuilt from scratch every quarter
Requirements change mid-analysis, restarting the workflow
Time spent formatting instead of interpreting results
Tribal knowledge locked in spreadsheets and email threads
Zerve automates the data gathering and formatting so you can deliver the business insight faster.
Requirements to results, without the runaround
Translate stakeholder questions into structured queries and get answers without chasing data owners.
- Natural language to structured query
- Cross-source data joins
- Automated data validation
- Stakeholder-ready formatting
Reports that update themselves
Build once, refresh automatically. Quarterly business reviews, KPI dashboards, and executive summaries stay current.
Analysis that adapts to changing requirements
When stakeholders shift priorities, extend existing workflows instead of starting over.
Business logic preserved across projects
Revenue definitions, customer segments, and KPI calculations live in reusable, governed workflows.
From data translator to strategic advisor
Spend less time pulling and formatting, more time recommending actions and influencing strategy.
Why data scientists choose Zerve
Why data scientists choose Zerve
Real stories from teams building with Zerve every day
Zerve feels different because it was built for data scientists from the ground up. It understands context, adapts as you work, and lets you iterate without crashes or lost work.
Gen AI Lead at AWS
Zerve finally feels like the cursor for data scientists. It understands that schemas live in your files, not in your head.
Founder/CEO at AlphaSignal
I gave it a churn analysis task and it pulled data, handled missing values, ran segmentation, and scheduled the workflow automatically using context from my past work.
AI Engineer at Stealth
We were working with a 4.3 billion-row dataset, and a high-end notebook instance could only handle 18 million-rows at a time without going out of memory due to the nature of preprocessing to be done on the data. That meant running the same call 24 times in a row. With Zerve, we could run all 24 in parallel. That shift alone saved us a huge amount of time and let us move faster on model development.
Head of Data Science at Sun King
The Zerve agent has transformed our data science workflow. Backlogs are vanishing and we're experimenting faster than ever.
Founder/CEO at Ascendr.org
As we advance our AI and Data standardization initiatives, Zerve provides the robust foundation we need to scale with confidence and be a force multiplier for meaningful outcomes.
Director of Data at Cubic
The Cursor for Data Science is here.
Data & AI Lead at DataBricks
Zerve represents a step-change for data science development.
Former EVP of Engineering at DataRobot
Zerve's Agentic code assistance is easily among the best I've seen
Technologist at HPE
I used Zerve AI, and it honestly felt like a cheat code for data science.
I use other AI when the answer already exists and I need to surface it. I use Zerve when the answer doesn't yet exist so I need to build it.
Applied AI Consultant at Commercial Outcomes