Blueprint Architecture & Technical Specs

Describe your automation in plain English and Blueprint's AI Workflow Generator turns it into a production-ready workflow definition — trigger, nodes, edges, and error handling included.

What you get back:

• A complete workflow: name, description, trigger configuration, and the full node/edge graph
• A confidence score (0.0–1.0) reflecting how complete and well-formed the generated workflow is
• Suggestions for improving low-confidence generations
• Warnings about potential issues in the generated workflow
• Which AI provider and model produced the result

Generation Pipeline:

1. Provider Discovery: Checks which AI providers are configured for your tenant. If none are reachable, generation automatically falls back to a supported default (OpenAI, Anthropic, Google AI, Groq, or DeepSeek) so it never blocks on a single vendor.

1. Context Building: Assembles everything the AI needs to generate a correct workflow — the available triggers (event, schedule, webhook, manual), the 50+ actions available across your Aeion OS modules, a handful of realistic example workflows, and the required output format.

1. Prompt Composition: Adds your natural-language description along with requirements for appropriate triggers, necessary actions, conditional logic, and descriptive labels.

1. Generation: Calls the selected AI provider with a low-temperature setting tuned for consistent, structured output.

1. Parsing & Validation: Extracts the workflow definition from the response and validates it — the trigger type is valid, there's at least one node, every edge connects real nodes, there are no duplicate node IDs, every action reference is valid, and conditional logic nodes have their conditions configured.

1. Confidence Scoring: Scores the result based on how complete the workflow is (nodes, edges, labels), how quickly it was generated, and how many (if any) validation issues came up.

1. Logging: Every generation is logged for observability — provider, model, duration, and node count.

Graceful Degradation: If your preferred AI provider is unavailable, generation automatically continues on a fallback provider. If a response can't be parsed or fails validation, you get a clear, specific error — never a silent failure.

Every AI generation is automatically saved, so nothing is ever lost.

What's tracked for each generation: the original prompt, which provider and model produced it, the full workflow, its confidence score, any suggestions or warnings, how long it took to generate, how many times it's been regenerated, whether it's been deployed, and whether you've marked it a favorite.

Limits & Cleanup: Blueprint keeps your most recent 50 generations per user — once you cross that count, the oldest non-favorite generations are pruned to make room. Favorited generations are exempt, so nothing you've starred ever disappears.

What you can do:

• Browse & search your history with pagination and a favorites filter
• Favorite any generation to protect it from auto-cleanup
• Replay any past generation — optionally with a modified prompt, a different provider, or a different model
• Delete a generation you no longer need