The same ten questions, asked of every AI teammate for Slack or Teams we get compared with: which model answers, what a turn costs, where it runs, who holds the credentials, who may approve a write, and what you can audit afterwards. Each page quotes the other product’s own pages, dated, and says where ours answers in writing.
An AI coworker you @mention in Slack and Microsoft Teams, with its own computer in the cloud, connections to 3,200+ tools, and a pause for approval in the thread before sensitive actions.
“Not a tool. A hire.”
Viktor is sold as a hire; attest_tag is source you can read, a binary you can run, a model you choose per thread, approver tiers with no self-approval, an audit log you can export from the free plan, and the model and cost printed under every reply — written for the engineer who will review the PR, not the operator who would hire.
A platform for creating, sharing and running agents that connect your company knowledge, tools and teams, mentioned as @Dust in Slack or triggered from Slack workflows.
“Multiplayer AI for human-agent collaboration”
Dust is the better choice for rolling agents out to marketing and support. attest_tag lives in Slack and Microsoft Teams, holds every write for a Confirm by default and sends access grants to an approver who is never the requester, seals credentials under a key you can hold on a self-host, and ships the audit log, approval tiers and two-factor sign-in in the free plan and the MIT binary.
Lindy is an AI teammate that connects to your tools, knows about your company and does work for the whole team, from Slack DMs and channels or as scheduled routines.
“The AI teammate that will 3x your output.”
Lindy waits for a named approver before anything with outside impact, so the difference is in the mechanisms its pages do not describe: the model and cost printed under every reply, tiers where nobody approves their own request, an audit log in the free plan rather than under Enterprise, and a flat fee by team size rather than $29.99 a user.
Runbear puts AI teammates into Slack, Microsoft Teams and Discord channels, where they answer @mentions and direct messages and act through connected tools. It is priced by credits rather than seats.
“AI seats sit empty. AI teammates show up.”
Runbear sells “no engineering” to ops teams — its homepage’s words — and attest_tag is written for the engineer. The two bullets Runbear lists under Business at $399 a month, a model key of your own and an audit log of every prompt and tool call, are in the MIT binary you can run yourself; the audit log, approval tiers and budgets are in the free plan too, and every write is held for a Confirm in the thread by default.
Slack’s built-in AI features and agents, sold with paid Slack plans and working inside Slack: “a powerfully simple way to be more productive, built with knowledge from your company.”
“AI in Slack works where you do.”
Slack AI is already in the workspace — summaries, search and recaps on every paid plan, and a Slackbot that takes actions on Business+ and Enterprise+ — so the difference is what its pages leave unsaid: attest_tag lets you choose the model and prints each reply’s cost under it, routes access grants to an approver who is never the asker, seals each credential under a key you can hold, and ships as one MIT binary you can run yourself.
OpenAI’s app for chatting one-on-one with ChatGPT in a dedicated Slack sidebar — summarising threads, drafting replies, searching Slack — with a companion ChatGPT Agents app for channels.
“The ChatGPT app for Slack brings the power of ChatGPT into Slack.”
The ChatGPT app for Slack brings ChatGPT into a Slack sidebar, and ChatGPT’s workspace agents ask before a write by default, so the difference is everything its pages leave off: the model named and its cost printed under every reply, approvers who are never the asker, a stated home for the shared connection’s tokens and who may see them, an audit log in the free plan, and an MIT binary you can run yourself.
An AI software engineer that ships pull requests the way your team does; you tag it in Slack or assign it a ticket in Linear.
“Devin, the AI software engineer”
Devin is sold as an AI software engineer: hand it a ticket and it comes back with a pull request. attest_tag is a teammate in Slack and Microsoft Teams that holds writes for a Confirm by default, prints the model and cost under every reply, routes access requests to tiers where nobody approves their own, ships the audit log in the free plan, and is one MIT binary you can run yourself.
An enterprise AI platform that connects to a company's work apps and data sources to provide search, an assistant and agents across surfaces that include Slack and Microsoft Teams.
“Enterprise AI that understands your company”
Glean puts one search and assistant over a company's apps on every surface, so the difference is what happens once an agent acts inside Slack: attest_tag holds every write for a Confirm in the thread unless an admin's allow rule clearly covers it, routes a grant to an approver who is never the requester, prints model and cost under every reply, lets you change the model per thread, and ships as an MIT binary you can run for nothing.
An AI agent platform where anyone at a company builds, shares and controls agents that connect to their apps and run on triggers, deployable to Slack channels and Microsoft Teams.
“Build, share, optimize & control agents”
Gumloop is for building and sharing agents over 300+ connectors, with a live credit count in the chat header and a per-app hold on writes you can switch on, so the difference is the defaults and the tiers: a hold on every write that is on by default rather than an “Always allow” default set per app, approvers who are never the requester, an audit log in the free plan rather than under Enterprise, and an MIT binary you can read and run on your own machine for nothing.
Moveworks is an AI Assistant platform for an entire workforce to search and act across business applications, reached through chat, web, intranets, service portals and mobile.
“AI that gets work done.”
Moveworks is an assistant for an entire workforce, reached through chat, portals and intranets, hosted by the vendor and priced by quote; it holds access requests for named approvers and exports a SIEM log over SFTP. The difference is what attest_tag prints, holds and lets you run: the model and cost printed under every reply, a model you can change per thread, every write held for a Confirm by default, tiers where nobody approves their own request, an audit log you can export on the free plan, and an MIT binary on your own infrastructure.
Onyx is an open-source platform that connects to your enterprise knowledge and gives humans and agents context, with a chat and search UI, custom agents and a Slack bot.
“Complete Context for Your Humans and Agents”
Onyx puts a company’s knowledge in front of its people and agents — a chat UI, a Slack bot, connectors synced continuously — so the difference is what its pages leave unsaid: attest_tag holds every write for a Confirm in the thread by default, prints model and cost under each reply, routes access grants to an approver who is never the asker, and ships as one MIT binary you can run yourself.
A platform for building and running “specialist agents for every task”, which its site calls “The home of the AI Workforce”, with agents that answer an @mention in Slack.
“Specialist agents for every task”
Relevance AI is where a team builds its workforce of specialist agents, any of which can wait for approval before acting; the difference is what attest_tag prints, holds and lets you run: model and cost under every reply, every write held for a Confirm by default, a grant routed to an approver who is never the requester, an audit log in the free plan, and one MIT binary you can host yourself.
Zapier Agents lets you create AI teammates, equipped with company knowledge, that do work across 9,000+ apps on command and on triggers, from a web app, Chrome extension or Slack.
“Meet your new AI teammates”
Zapier Agents reaches 9,000+ apps through the Zapier directory and counts the month in activities, so the difference is what attest_tag prints and holds: the model and measured cost under every reply, every write held for a Confirm in the thread by default, approver tiers where nobody approves their own request, an audit log in the free plan, and an MIT binary you can run yourself.
Anthropic’s own Slack teammate: Claude, hosted for you, first-party inside Slack.
Written by architecture rather than by feature list: what follows from being hosted and first-party, against what follows from choosing the model, running the binary, capping the spend and putting a named person in front of every change.
Each answer below is a statement about this product that needs no claim about anybody else's to stand up, and each ends where the mechanism is shown.
Which model answers
Any endpoint, per thread
Any OpenAI-compatible endpoint — OpenRouter, a vendor API, or a model you host. Ships on google/gemini-flash, with a heavy model routed to automatically for code and long threads, and a per-thread override.
Metered per completion and printed under the reply beside the model that answered, with !usage for the month by channel. A monthly budget for the workspace, another per channel, and a per-user hourly rate limit — the bot pauses at the ceiling rather than reporting having crossed it.
Hosted by us, or one MIT-licensed Go binary with the console embedded on your own infrastructure — Docker, Cloud Run, Fargate, Container Apps or Kubernetes. The same code either way. Where HIPAA applies, run it yourself so nothing leaves your network, and we sign a business associate agreement with you.
The service, never the model. Sealed with AES-256-GCM at rest — under a key you hold, on a self-host — injected by a proxy at the network edge, and scrubbed back out of every response before it reaches the model or the thread.
Writes that grant access leave the thread and go to an approver’s DM. Nobody approves their own request — enforced three times over, once in SQL — and a request routes to the least powerful tier that covers every call in it.
Every turn, tool call, proxied request and completion — with tokens and cost — in a console you run, exportable as CSV. Self-hosted, it is a table in your own database.
Missing a product you are weighing against this one? Tell us and we will read their pages and write it up the same way.
/How these pages are written
Every sentence about the other product was read from its own public pages on the date printed beside it, and is either their words or the sentence “Not stated on their site.” That sentence is a finding about a page on a day, never a claim about the product: a vendor that answers the question in a call, or adds a line to their pricing page next quarter, has not been contradicted by us, and the page will change when we notice.
Every sentence about attest_tag is one this site makes elsewhere, with the mechanism shown — which is why each cell in our column ends in a link. If either column has something wrong, the contact form reaches the people who wrote it.
Run it beside whatever you have for a week.
It answers in threads, so it will not collide with the other one, and a week of your own questions settles this faster than any table.