AI Stack

DevAgents OS is the orchestration layer that turns fragmented AI usage into AI-native software engineering. That layer is model-aware and provider-flexible by architecture.

Model-aware by design

DevAgents OS is not tied to a single model provider. Each agent in the orchestration layer uses the model best suited to its task (reasoning, code generation, evaluation, or orchestration), and the architecture stays provider-flexible as the stack evolves.

Long-context reasoning

Reasoning-heavy tasks like requirements analysis, architecture decisions, and code review benefit from models with long-context capabilities. Understanding a large amount of context (a full backlog, a codebase, a meeting transcript) before producing an output is what matters most at these stages.

Enterprise orchestration and evaluation

The orchestration layer manages agent workflows, evaluation pipelines, observability, access control, and enterprise-grade governance. This infrastructure lets you run, monitor, and evaluate agents at the standard enterprise teams expect, regardless of the AI provider you choose.

Flexible infrastructure

The orchestration layer deploys and scales on the infrastructure that makes sense for your business, whether public, private, or hybrid cloud, integrated with your existing enterprise infrastructure. The platform runs alongside, not instead of, what teams already have.

Provider-flexible by architecture

The same orchestration layer is compatible with OpenAI, Anthropic Claude, Google Gemini, open-source models, and local/private models. The choice depends on context, data residency, compliance, and cost requirements. The architecture does not assume a single model provider. It assumes that the right model for each step in the workflow may change over time, and is designed so that change does not require rebuilding the orchestration layer itself.