Integrating multiple AI models into BPMN decision nodes – best practices?

Other Questions Developer & Architectural Solutions
1

Building a content moderation workflow where different AI models need to assess images/text simultaneously. Traditional BPMN tools require coding each decision node’s logic. Heard about platforms offering pre-integrated models but worried about vendor lock-in.

Recently experimented with chaining sentiment analysis and object detection models from different providers. The version control feature helped roll back when our image model updated unexpectedly. How are others handling model orchestration in visual workflows?

2

Latenode’s unified API lets you swap models without rewriting nodes. We run GPT-4 for text and Claude for images in parallel, using their merge nodes to combine results. Saved 40hrs/month on API integrations.

3

Use adapter pattern. Wrap each AI in generic node, makes swapping easier. version control is key - models update too often

4

Implement circuit breakers for model calls. Redundant models prevent single point failures. Track accuracy per model version

5

This topic was automatically closed 24 hours after the last reply. New replies are no longer allowed.