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 the setup handle different permission levels across departments? Separate access controls with clear visibility could keep sensitive work protected without slowing collaboration.
@O - AI coworker in Slack
@darly_selby Good q, and this is core to how we think about it. Permissions are set per employee, and each person's @O mirrors their own access, it can only reach what they're already allowed to reach. So someone in finance and someone in support get agents scoped to their own permissions, nothing leaks across departments by default. You get the collaboration without opening up sensitive work to people who shouldn't see it. Admins keep visibility over it all 🙂
tagged @O to summarize a long thread and it actually pulled the key decisions plus action items in seconds, way cleaner than the bots we tried before.
@O - AI coworker in Slack
@erifeergveynbd great! Would love to hear about your next use cases!
This is sick. What are your top 3 use cases? Just tried the sales use case and it is amazing. Great job.
@O - AI coworker in Slack
@christianpev Thanks so much - stoked you tried it and that the sales one landed!
Top 3 we see:
Sales - the one you tried. Draft follow-ups from call notes, research accounts, update the CRM, prep before meetings. All from the deal channel.
Ops / Admin glue work - the cross-tool busywork nobody owns. Pull from one tool, update another, send the weekly report - on a schedule while you sleep.
Team knowledge - because @O lives in shared channels with shared memory, it becomes the teammate who always knows the answer. New folks ask it instead of pinging five people.
The common thread: it all happens right in Slack, so people actually use it. Thanks again for the kind words! 🙌
Tagged @O in a channel to draft a quick meeting recap and it pulled everything together faster than my usual routine, the Slack-native feel really does make it feel like another teammate on the team.
@O - AI coworker in Slack
@ecrindaler - glad O found new job in your org! :D
Tagged @O to pull a quick report from our CRM and it actually got it right the first time, including the bit I forgot to mention.
@O - AI coworker in Slack
@durmumnda - good job O :) Glad it worked out for you!
The native Slack integration is really well executed, tagging it like a teammate instead of opening another tab makes it feel less like another AI toy and more like an actual coworker.
@O - AI coworker in Slack
@nihalkalenkuqg glad you like it Nihal. It's a surprisingly small UX change, with a surprisingly high difference!
"Any model you choose, including your own" is an interesting claim for a Slack app. If someone brings their own model, where does the conversation data go, does it still route through Ogment's infrastructure before hitting their model endpoint, or is there a deployment option where nothing touches your servers at all? For teams that care about data residency that's not a minor detail.
@O - AI coworker in Slack
@ansari_adin - a question we are actively thinking about!
Today: yes, the conversation routes through our agent system / harness before it hits any model endpoint. So "bring your own model" right now is about model privacy (your prompts/completions aren't going to a shared frontier provider) and, honestly, cost, that's the biggest driver we see, teams pointing at their own or cheaper endpoints to control spend.
What you're describing, nothing touching our servers at all, is a VPC/on-prem deployment, and it's on our longer term radar for teams with hard residency requirements.
@teoborschberg Good to know where it actually sits today versus where it's heading, that's a more useful answer than most teams get before they ask the question.
Love that you can tag it like a teammate instead of opening yet another tab. The shared memory across the whole team is a really smart call, that's what usually breaks with these tools.
@O - AI coworker in Slack
@cemrebfmt - thanks for your comment. Hope you get to try O with your team!
Love that it just lives in Slack as a tagged coworker, no separate app or tab to babysit. The shared team memory angle is the smart move, that's usually where these tools fall apart.
@O - AI coworker in Slack
@birglanvl - shared memory is one, and also we find that the shared context with all the agent's output directly in multi people threads is definitely a great asset!
Tagged @O in our team Slack to draft a quick project update and it pulled the info straight from Notion without me explaining anything. Felt like onboarding a new teammate who already knew the stack.
@O - AI coworker in Slack
@zgefwrz - that's awesome. Exactly the UX we're striving for! Thanks Ozge!