Ari just lives in Slack and Gmail where I'm already working, so there was nothing new to learn. It plugs into everything we use (Google Calendar, Zoom, HubSpot, etc.) and I haven't found a connector it couldn't handle. The speed is actually ridiculous. When I ping Ari, she responds nearly instantaneously. As a founder, it's really difficult for me to keep up with everything that is going on. Ari sends me messages every day with things that weren't even on my radar...that should be on my radar. It's shockingly intelligent. The Ari team is extremely responsive and is one of the highest velocity product development teams that we've seen.

I use Ari for To Do List and daily updates, and I really like how it helps me with less context switch and protecting my focus. I enjoy the meeting summary feature too, which is quite beneficial. Additionally, the initial setup of Ari was easy, making it convenient to get started.

Most AI tools make the individual faster. Ari makes the operation smarter. That's a meaningful distinction for anyone running teams at speed. What I've found valuable is that Ari doesn't just respond to prompts, it builds context over time. It lives in Slack, which means it meets people where they already work. And because it pulls from meetings, email, and docs, it actually has enough signal to be useful when it matters: before a call, after a chaotic week, when you're trying to figure out what dropped. But what genuinely surprised me was the security architecture. For an AI tool that sits inside your most sensitive workflows [messages, meeting transcripts, personal reflections, credentials] this matters more than most vendors acknowledge. Ariso built cryptographic isolation at three levels: organization, user, and session. Your data isn't just access-controlled, it's mathematically separated. Session-level encryption means ephemeral conversations can't be retroactively decrypted once a session ends. For anyone serious about deploying AI inside a real business, that's not a nice-to-have, it's the bar. The team behind it is sharp. They've clearly lived the problems they're solving, and that shows in both the product and the infrastructure decisions underneath it.