IDE For LLMs
Build, Fine-tune and Deploy like never beforeData Science & AI Development Platform
Build, manage and deploy all your AI and data workflows to empower code first data teams to reduce cycle times.
There is too much friction for code first data teams delivering Data Science and AI projects
Fragmented tech stack and local development lead to a lack of visibility and unreliable reproducibility
There are significant bottlenecks from requesting compute to relying on others for deployment.
Data science projects require a variety of skillsets but siloes hinder collaboration
A unified Data Science and AI platform
Zerve is a cloud-native solution that removes barriers and friction across all roles and cloud environments. With operations streamlined by proving one unified platform, Zerve removes the need to piece together fragmented tools.
Orchestration
Run anywhere at any scale with no DevOps or IT bottlenecks. Easily configure optimal compute and unlock the benefit of distributed computing for any task.
Deploy Zerve directly within your VPC, so your data never leaves your environment
With flexible options across all major clouds, Zerve ensures code, results, and data remain under your control. By adhering to the principle of least privilege, Zerve strikes the right balance between access and security.
A serverless data science platform built on modular, DAG-based workflows
Centralize your code so everyone can contribute and use Zerve’s orchestration engine to unlock distributed computing.
Data experts take on Zerve
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Zerve at AI and Big Data Expo Global 2025
Join Zerve at the AI & Big Data Expo Global 2025 on 5-6 February at Olympia, London. Visit us at Booth 72 and hear our CPO, Greg, speak on enterprise AI innovation (Day 1, 2:05 PM) and join the 9:55 AM panel on Gen AI's future.

Mastering Model Validation: Effective Train-Test Splits and Cross-Validation Strategies
Learn effective model validation techniques like train-test splits and cross-validation strategies to build robust predictive models. Discover AI best practices and insights tailored for high-stakes industries like banking.
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Optimizing Performance: A Hands-On Guide to Hyperparameter Tuning
Discover how hyperparameter tuning transforms model performance in data science. Explore grid search, random search, and Bayesian optimization techniques with real-world examples from industries like banking. Learn AI best practices for tuning and validation.
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