Configure providers once
Set up OpenAI, Anthropic, Gemini, local models, or other providers from one shared layer.
Feature
One OS. All your models. No lock-in.
WizeOS lets you connect multiple providers and local models, then assign the right model to the right workflow without making the team switch products.
Assign by workflow
Use different models for research, drafting, classification, or sensitive internal work.
Stay flexible
Change providers when pricing, performance, or policy changes without moving the team to a new product.
Problem
The best model changes by task, cost, and data sensitivity.
Different workflows need different trade-offs: reasoning vs speed, cost vs accuracy, cloud vs local. Juggling multiple frontends and API keys makes consistency and UX impossible.
Solution
Central model routing behind a single workspace.
In WizeOS, you configure providers once at the OS level, then assign models to agents and workflows. Your team just works in one place. WizeOS picks the right engine under the hood.
How it works
Configure once, assign by workflow, adapt when conditions change.
Step 1
Configure providers
Configure providers such as OpenAI, Anthropic, Gemini, or local models in one shared setup view.
Step 2
Map default models
Assign default models per agent type, whether the work is research, analysis, drafting, or classification.
Step 3
Override when needed
Override model selection per project or workspace when sensitivity, performance, or cost requirements change.
Use cases
Keep model strategy flexible without forcing your team to relearn the product.
Central provider management means pricing, performance, and policy changes can be absorbed without breaking everyday work.
Use high-end reasoning models for orchestrator agents and cheaper models for workers.
Run sensitive workflows on self-hosted or local models, while creative tasks use cloud models.
Switch providers without retraining the entire team on new tools.
WizeOS core
WizeOS keeps your model strategy flexible.
Adapt to pricing, performance, and policy changes without rebuilding your workflows or retraining the team on new tools.