Tag Archive
Posts connected to the ai topic.
Most engines tell you the result. The inference trace tells you the reasoning — every firing in order, a green/red condition tree with the actual values, every context change, and a plain-language explanation on demand.
Why the expression language has no now() or random(), why re-fires key off real value changes, why AI results are remembered for unchanged inputs, and why an inference cascade still meters as one run. Determinism is what makes the rest trustworthy.
AI Rule Engine now includes native support for Azure OpenAI models, and when paired with our dedicated Azure hosting plan, your data never leaves your own tenant.
Token-maxing every decision sounds like a smart AI strategy until the bill arrives. Here's how to use AI where it earns its cost and let rule-based logic handle the rest.
AI Rule Engine now lets you create a new project by describing what you want to automate. The AI generates the rules, conditions, and actions that make up your workflow — no blank canvas required.
Different AI models excel at different tasks. AI Rule Engine lets you mix providers and models in one workflow so you can optimize for quality, speed, and cost at each step.
AI Rule Engine now includes native support for Anthropic AI models, making it easier to build governed workflows with Claude and other supported models.
AI Rule Engine now supports MCP so AI assistants can initiate workflows, read files, inspect ruleset run logs, and operate with per-instance permissions.
Why human oversight matters in AI processes, and how AI Rule Engine connects AI providers, governed workflows, and MCP-enabled assistants in one controlled system.