n8n and Zapier are great until you hit actual enterprise complexity, then they kind of fall apart
Spent way too long fighting Zapier's "if this then that" logic on workflows that needed actual decision-making and yeah, it doesn't scale.
The thing nobody tells you is that the bottleneck isn't connectors, it's that these tools can't reason. They route stuff around but they can't look at a weird invoice, figure out why the three-way match failed, and decide what to do about it. A human ends up rescuing the workflow every other run. n8n's better since it's flexible and self-hostable, but it's still deterministic under the hood.
Read this blog arguing the next step is embedding AI agents directly into the workflow nodes instead of bolting an LLM on as a plugin. It's pitched around Indian enterprises specifically (RBI compliance, data localization, population-scale volumes) which is a context most foreign-built tools weren't designed for. Made-in-India framing but they're upfront that it's about contextual design, not flag-waving.
Their litmus test for any workflow builder is decent though: does it handle exceptions without a human babysitting it, is the AI native to the execution node or a laggy add-on, and does it scale with governance instead of despite it.
idk if "intelligent orchestration" is a real category or just automation with an LLM stapled on. could be wrong. curious what people who've run this stuff at scale think.
Posted Jun 15, 2026, 6:48 AM UTC