MAVEN — Model Administration, Variants & Execution Network — is a self-hosted AI platform that manages the complete environment surrounding your local models.
Choose your models, control your data, configure how your AI operates, and build an intelligent workspace that isn't dependent on a single model provider.
Most local AI applications focus on downloading models and generating responses. MAVEN manages everything around those models — conversations, knowledge, memory, research, tools, personalities, and integrations — in one cohesive platform.
The model provides the intelligence. MAVEN provides everything it needs to work.
AI models are advancing rapidly. Your platform should be able to advance with them. MAVEN is being designed to accommodate models with different capabilities, context windows, tool interfaces, generation controls, and hardware requirements.
A model you use today may be replaced by something dramatically more capable tomorrow. Your conversations, tools, knowledge, and AI environment shouldn't need to start over every time that happens.
Choose the intelligence. Keep the infrastructure.
MAVEN is built around local execution and locally managed data. Rather than relying entirely on remote AI services, it gives you an environment where models, conversations, and stored knowledge can operate on your own hardware.
Online research is available when enabled, while offline mode provides a local-only interaction path. Control which models you use, how conversations are managed, whether memory is applied, and when external services are involved.
Your hardware. Your models. Your environment.
When an answer is wrong, you shouldn't have to guess what happened. MAVEN's execution tracing system records observable stages of response generation — research decisions, retrieved evidence, model calls, calculator executions, verification events, and timing information.
Explore execution traces to understand how the application assembled and delivered a response. It's visibility into the system's actual execution — not a claim to expose a model's private internal reasoning.
Better visibility. Better debugging. Better AI infrastructure.
MAVEN's architecture is built around several core principles.
The platform should adapt to compatible models rather than depend on a single model family.
Keep your AI environment and locally stored data under your control.
Make tools, integrations, and new capabilities part of a modular foundation.
Provide insight into execution, research, tool use, and performance.
Configure the intelligence and the experience around how you work.
Improve the surrounding platform without abandoning your existing AI environment.
One place to manage your intelligence, your memory, your tools, and your AI-powered workflows.
