One thing I’d add to this comparison is the quality of human handoff. Even a good AI won’t solve everything. When it needs to escalate, having the full conversation and context available to the agent makes a huge difference.

I’ve been using Intercom for a while, so Fin was the obvious option for us. The downside is that I think it makes more sense when Intercom is already part of your support stack rather than starting from scratch.

For me, the biggest change is that I now expect SaaS tools to understand context. Just answering a question isn’t enough anymore. If the system already has access to my data, I expect it to use that context and actually do something useful with it.
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This is something I didn’t really think about until seeing agents used in real workflows. Automation gets all the attention, but consistency is probably easier to appreciate over time. The agent doesn’t get tired, forget a step, or decide to handle the process differently because it’s a busy day.
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‎I think this becomes more useful as the agent gets bigger. When you’re managing one small bot, clicking through settings isn’t a big deal. But once you have lots of knowledge, workflows, conversations and ongoing changes, having an assistant handle the operational side starts making a lot more sense.
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I’d lean toward starting simple. Build one agent around the most valuable use case, learn what users actually ask for, then introduce specialized agents when the data shows there’s a real need. I wouldn’t design a whole multi-agent system just because it sounds impressive.
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Something around sales operations would interest me. There’s so much information spread across emails, calls, CRMs and spreadsheets. An AI that turns all that into actual next steps could be genuinely useful.
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The first 100 always seem harder than the next 1,000. You can’t really hide behind ads or a huge brand at that stage. You have to talk to people, show them the product, hear why they don’t want it, and keep adjusting. Not glamorous, but probably one of the best learning stages.

For me, it would come down to how much maintenance the system needs. If I’m constantly fixing prompts, updating workflows, and correcting the AI, then I’m not sure I’ve actually saved much time. The best setup should feel like it’s taking work off the team, not creating a different kind of work.

Honestly, I can see why this would be appealing. Having one agent instead of trying to keep a bunch of separate bots updated sounds like a lot less work. But I think the real test is what happens when things get messy. A customer starts on WhatsApp, switches to email, then ends up with a human agent, if the context follows them properly, that’s a big win. If it doesn’t, then you’re probably just moving the maintenance headache somewhere else.

Yeah, I’ve noticed this too. It’s really easy to keep adding custom stuff when you’re trying to make the AI fit perfectly, then later you realize you’ve created a lot of things you now have to babysit. I think keeping the core simple and only customising where it actually makes a difference is probably the safer approach long term.

Honestly, I think I’d just launch. A waitlist sounds nice, but having actual people use the product and tell you what’s confusing or not working feels way more useful. You can always build the hype later, but that early feedback is hard to replace.

Set it up on our store about a month ago. Order lookup is genuinely the killer feature WISMO tickets dropped noticeably since customers get real tracking info instead of check your email. Setup itself took maybe an hour, most of the time was tweaking the product recommendation prompts so it didn’t push random items. Cart recovery piece hasn’t done much for us yet, still testing it.

Been running Fin (Intercom) for about a year. Resolution rates look great in demos, then drop once you hit real edge cases like billing exceptions or account merges ended up building our own guardrails. Haven’t used Chatbase in production, but I’d push back a bit on all in one more complete. Usually means fine at everything, best at nothing. Worth asking if the native help desk actually holds up under volume or if people quietly route around it.

Switched from live chat to an AI agent on our pricing page 8 months ago. Conversions went up, mostly because it’s always on a lot of our traffic hits at night/weekends when nobody’s watching a chat widget anyway. Falls apart on bigger deals though; once it’s enterprise pricing or custom contracts, people want a human fast, and the AI needs to hand off cleanly or you lose them. So it’s less AI vs live chat and more AI as the first filter, human on standby for anything complex.