Ogment AI - Your AI coworker, in Slack. Just tag @O.
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@O is the ultimate AI coworker that lives natively in Slack.
Tag @O like a colleague, to ask anything or delegate daily tasks in plain English. It connects to 1,000+ tools your business runs on, does work while you sleep, and shares memory and skills across your whole team right in Slack, on any model you choose, including your own.
One-click install, and everyone is AI-enabled in under 5min, not just your power users. Zero friction, maximum adoption.
Replies
how does pricing scale when a whole team starts tagging @o constantly throughout the day, does it balloon fast?
@O - AI coworker in Slack
@glerioqv - honestly, with Opus 4.8 it could add up fast at high volume. But Sonnet just landed about 3x cheaper with basically the same performance for this kind of work, so the math changed a lot, we're getting to genuinely competitive pricing even at scale now. And since you can point @O at different models, you've got a real lever to tune cost vs power per use case rather than paying top-tier for everything.
BetterClaw
the zero-friction adoption point is the real insight here. most AI tools fail not because the AI is bad but because nobody on the team actually uses them. meeting people where they already work instead of asking them to learn a new app is why this has a shot at real adoption beyond just the power users\
@O - AI coworker in Slack
@tina_chhabra thanks Tina, that's exactly it, and you put it better than our landing page does ;) The graveyard is full of genuinely good AI tools that lost to "yet another app to open, yet another behavior to change." We bet the whole product on adoption being a distribution problem, not a capability one. Tag it like a colleague, no new surface, no new habit, and suddenly it's the non-power-users driving it.
Tagged @O in a channel and it pulled the right data from Notion without me explaining anything. The shared memory across teammates is the real standout, no one has to repeat context.
@O - AI coworker in Slack
@tayfunabik5641 - love this, that "without explaining anything" moment is exactly what we were chasing 🙂 The context living where the work happens means nobody's re-briefing the bot every time. Thanks for giving it a real spin on launch day, means a lot
How does the shared memory actually work between teammates, like can I keep certain context private to just me or does @O sync everything across the whole workspace?
@O - AI coworker in Slack
@alisennecl99142 You can absolutely keep context private to just you, that's the default. @O doesn't sync everything across the workspace. Two layers: personal memory that's yours alone (learned from your own tasks) and an org-level layer an admin shares team-wide on purpose. So your stuff stays yours, shared context is deliberate.
Meeting people where they already work instead of adding another tab — smart. Slack-native is underrated as a distribution strategy. What's the most unexpected task users have thrown at @O so far?
tagging @o in slack feels weirdly natural, like adding a teammate who never sleeps. loved that it actually pulled data from our google sheets without me configuring anything first.
@O - AI coworker in Slack
@helin786446 - love it. Thanks for trying it out, means a lot to us!
How does the shared memory actually work across teammates — does my data stay private to my own prompts or does it get pooled into a team-wide knowledge base?
@O - AI coworker in Slack
@yldzzk2x your data stays private to you by default, it doesn't get pooled. Two layers: personal memory that's yours alone (learned from your own prompts) and an org-level layer an admin deliberately shares team-wide. So nothing you ask gets swept into a shared knowledge base automatically, the team-wide stuff is curated on purpose.
Putting the agent where work already happens is the right adoption move. The next trust layer is ownership: who asked it to do what, which tool it touched, and how a teammate can inspect or stop a task before it becomes invisible automation.
@O - AI coworker in Slack
@krekeltronics thank you Patrick! We actually started to work on this already!
how does pricing work as the team grows, is it per user or per active usage?
@O - AI coworker in Slack
@bernahru8 Good q! It's usage-based, not per-seat, so you're not paying for people who barely touch it. You can add your whole team without seat math, and cost tracks actual work done. And since @O is model-agnostic, you've got a real lever there, point it at a cheaper or local model to tune cost per use case. Happy to ballpark real numbers if you tell me rough team size and how heavily you'd use it
Tagged @O in a test channel and it pulled a report from our CRM in seconds, no setup headache. The shared memory across teammates is a nice touch too.
@O - AI coworker in Slack
@huriyedarka awesome to hear! Next step might be to ask O to create a skill so it processes the data exactly like you want every time? :)