Connect your applications to Fusion Plane
Applications send AI requests to Fusion Plane instead of calling model providers directly. Your team gets one consistent gateway for AI traffic across products, environments, tenants, and workflows.
How It Works
A simple control layer for your AI stack.
Fusion Plane sits between your applications and the AI providers you already use, turning scattered model calls into a managed layer for prompts, routing, observability, cost control, evaluations, and governance.
Manage prompts and routing centrally
Store prompt templates, version changes, configure model rules, define fallbacks, and control how requests are handled without duplicating logic across every codebase.
Monitor, evaluate, and improve
Track usage, latency, errors, responses, and cost. Compare prompts and models before rollout, then optimize for quality, reliability, and spend over time.
Govern behavior across teams
Give engineering, product, and leadership teams shared visibility into how AI is being used, who can change behavior, what changed, and how those changes affect production systems.
Architecture shift
From scattered provider calls to one managed AI layer.
Without a control plane, each application tends to own its own prompts, provider integrations, logging, fallback logic, and cost tracking. Fusion Plane centralizes those concerns so teams can reuse patterns, enforce controls, and improve AI behavior without rewriting every integration.
Before Fusion Plane
- Prompts live inside application code
- Each app calls model providers directly
- Logging and error handling vary by team
- Cost attribution is limited or manual
- Model changes require code changes
- Governance depends on scattered processes
With Fusion Plane
- Prompts are managed and versioned centrally
- Applications route AI traffic through one gateway
- Usage, latency, errors, and cost are observable
- Routing and fallback rules are configurable
- Evaluations happen before production rollout
- Governance becomes part of the AI workflow
Shared outcomes
What changes when AI runs through a control plane.
01
Less duplicated AI infrastructure
Teams stop rebuilding prompt storage, provider integrations, routing logic, logging, and fallback patterns inside every application.
02
Clearer cost and usage visibility
Engineering and product teams can see how AI traffic behaves across products, environments, customers, and use cases.
03
Safer production changes
Prompts, models, and routing rules can be tested, reviewed, and governed before they affect real users.
04
More flexibility across providers
Teams can evaluate and route across models without tying every application directly to one provider's API.
Closed beta
Bring us your real AI operations workflow.
The closed beta is designed for teams with live or near-production AI workflows and measurable goals around quality, cost, observability, routing, or governance.