A Unified Multi-Agent OS for Distributed Data Integration
Seamlessly combine data sources, scale processing tasks, and deliver APIs to empower robust analytics workflows.
Accelerate Your Data-Driven Future
Break down data silos, orchestrate complex workflows, and thrive in a world of agile, serverless computation.
AI-powered solutions enhancing efficiency
The Surging Adoption of Multi-Agent Systems and AI-Driven Data Integration
These statistics underscore how enterprises leverage AI agents, multi-agent platforms, and integrated data strategies to drive growth, efficiency, and revenue.
Enterprise Adoption of AI Agents
Large Enterprises Planning to Integrate AI Agents
Percent of Day-to-Day Work Decisions made Autonomously
Global Distributed Computing Market
Seamlessly unify disparate data sources into normalized models, enabling smooth and flexible data management.
Scale computations across a cluster of workers, ensuring efficient, real-time processing for evolving workloads.
Expose all functionalities, datasets, and commands through secure, well-documented APIs for easy downstream consumption.
Orchestrate tasks and schedules with a serverless, self-managing system that adapts to changing demands effortlessly.
Leveraging Popular Technologies You Already Trust
Powered by Open Source
Building off established ecosystems to drive secure, AI-powered knowledge management and automated research across industries.
Flexible, Efficient, and Extensible Data Integration
Modular, Extensible Architecture
Easily integrate diverse data sources with a pluggable, modular system that allows you to build and extend capabilities without complex rewrites.
Unified Data Models
Leverage integrated, dynamically generated data models that enable consistent, normalized data access without writing complex SQL queries.
Automated Distributed Processing
Scale horizontally with distributed task queues and workers, automating complex ETL pipelines, machine learning tasks, and scheduled operations.
Secure, Scalable Data Access
Provide secure and scalable access to processed and curated data via robust APIs, ensuring data integrity, role-based permissions, and encryption.
Adaptive, Agent-Driven and Serverless Processing
Event-Driven Scaling
Automatically scale processing capacity based on incoming workload, seamlessly adapting to spikes in data volume with zero manual intervention.
Agent-Based Orchestration
Orchestrate complex workflows with intelligent agents that distribute tasks, manage dependencies, and streamline execution across the entire stack.
On-Demand Serverless Execution
Run tasks only when needed, eliminating idle resource usage. Quickly spin up and tear down worker nodes to minimize costs and maximize efficiency.
Dynamic Resource Optimization
Allocate CPU, memory, and storage dynamically for each task, ensuring optimal resource usage and stable performance under varying load conditions.
Seamless Data and Command Interactions
Unified Data Access
Access all integrated data sources through a single, OpenAPI-compliant Data API, eliminating the need for custom integrations or manual queries.
Powerful Search & Filtering
Effortlessly query nested relationships and apply complex filters, enabling precise data retrieval and efficient generation of dynamic datasets.
Live, Streaming Command Execution
Run commands remotely and receive continuous, real-time output streams, improving responsiveness and enabling interactive troubleshooting.
Scheduled & Queued Operations
Queue commands for asynchronous processing, schedule periodic tasks, and manage workloads with ease, ensuring reliable and timely execution.
Getting started
Bring the platform online in your environment with a guided rollout.
Scope the modules
Align on the knowledge, agent, and interface components you need first and define governance controls.
Deploy with accelerators
Use infrastructure-as-code and CI/CD templates to stand up environments in days, not quarters.
Operate & evolve
Train your teams, monitor usage, and expand to new workflows with reusable patterns.
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Get Started Today
Unlock the full potential of your data with effortless integration and automated orchestration.
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How does Zimagi handle large-scale data integration?
Zimagi uses Kubernetes and serverless technologies to scale horizontally, handling massive datasets efficiently.
Can I customize data models and workflows?
Yes, Zimagi’s modular framework allows you to plug in and override data models or command structures easily.
Is it possible to process data in real-time?
Absolutely. Zimagi supports both scheduled tasks and on-demand commands for real-time processing.
How secure is my data on Zimagi?
Zimagi integrates robust security measures including role-based access controls and auditing features.
Can I deploy Zimagi on-premises?
Yes, Zimagi’s containerized architecture runs seamlessly on-premises or in any cloud environment.
Does Zimagi integrate with my existing analytics tools?
Zimagi’s API-first approach ensures seamless integration with popular BI and analytics platforms.
What about the learning curve for my team?
Zimagi abstracts complexity with a command-driven interface and unified APIs, reducing time-to-adoption.
Can I automate deployment and updates?
Yes, Zimagi supports CI/CD workflows, allowing you to automate deployments and software updates effortlessly.
How does Zimagi manage scaling and updates?
The controller automates orchestration, ensuring self-managing scalability and smooth updates.