An API-based multi-model orchestration platform that routes each request to the model or collection of models best suited to the task
Provide a simple virtual model endpoint that hides model selection and orchestration from users. The platform can combine existing models, replace unavailable models, and route different parts of a request to different models. This can provide resilience when models change, although output quality becomes less predictable.
online BOTH AI Agents & Automation
From IBM Technology — New AI models, token minimization and IBM’s new sub-1nm chip at 15:48
Problem: Users otherwise have to choose among rapidly changing models and repeatedly move workloads to whichever model is currently considered best. Individual models may also be strong at different tasks, while enterprises need resilience when a model becomes unavailable or changes.
For: Enterprises and developers that want frontier-like capabilities without managing individual models, model changes, or routing decisions themselves
Examples
- Sakana Fugu: the panel said it performs particularly well on coding tasks and can exceed individual models at perfectly routed settings, but its quality may vary substantially depending on routing.
Behind this: 12 build steps · 2 tools and how each is used · how to validate demand · 1 more real example · 6 things the video never answers.
Other takes on AI agent platforms and compute access
- Autonomous AI agents that perform administrative labor for underserved small businesses, starting with dental practices
- A personal, open-source AI agent that can be operated through messaging channels such as WhatsApp and Discord
- Enterprise AI concierge for customer, sales, and operational workflows
- AI appointment-scheduling assistant for healthcare providers
- Production-ready inference hosting for open AI models
- A cloud-hosted AI co-founder club that gives each member a personal, containerized AI agent