Multi-Model AI Orchestration: Routing Each Task to the Right Engine

No single model wins at everything. A reasoning model drafts your storyboard script, an image model renders the keyframes, and a video model animates them. Orchestration is the layer that decides which engine handles which step, passes context between them, and merges the results into one coherent output.

The practical wins are concrete: route cheap classification to a small fast model and save the expensive reasoning model for hard prompts, and you cut cost without losing quality. Add automatic fallback so a timeout on one provider retries on another, and your pipeline stops breaking when a single API has a bad day.

On B4AI you switch between chat, image, video, and storyboard models in one workspace, so a prompt can flow from idea to script to frames to finished clip without copy-pasting between five tools. Start by mapping each step to its best-fit model, set a fallback for each, and measure cost-per-output rather than per-token.