What Is Appy.AI
A team of named AI specialists that works inside Slack and Microsoft Teams — not one chatbot.
$100 in free credits
No card required.Appy.AI deploys a team of named AI specialists into Slack and Microsoft Teams. Not one general-purpose chatbot — a team, where each specialist maps to a real business function. Violet directs the team and delegates work to the right specialist. Marcus handles brand strategy, Piper writes outreach drafts, Sage runs financial analysis, Sarah works as an executive assistant, Scout does competitive intelligence, Paige owns content, Hamilton builds websites, Lincoln handles SEO. You @mention one in a channel or DM them directly, and the work comes back in the thread.
If you landed here from a search about "Appy" and expected a different company — including one with a similar name — this is Appy.AI specifically: an AI team that works inside the chat tools your company already uses. To learn more about the team and investors behind Appy.AI, visit our About page.
Who it's for
Appy.AI is built for teams that want AI to do actual work — draft a report, research a competitor, build a financial model, write a blog post — without hiring a specialist for every function or routing everything through one overworked generalist AI chat window. It fits companies already running Slack or Teams, since that's where the agents live and where the output shows up.
Real teams running it today include Sanguine Strategic Advisors, a 15-person team using it for financial reconciliation and reporting; Imperial Cleaning, using it for territory mapping and RFP automation; and The Paper Tree House, a pediatric clinic using it to triage clinical backlog.
The specialist team
Appy.AI isn't one model with different prompts stapled on. Each named agent is a specialist with a defined function:
The reason for named specialists instead of one assistant is the same reason a company employs more than one person: a finance question and a brand question need different judgment, not the same general-purpose response reworded. Ask Sage about your burn rate and Marcus about your positioning, and you get an answer shaped by that specialty — not a single model guessing at both. To see what each specialist actually does across every business function, browse the full use cases hub.
What separates this from a chatbot
Three things, stated plainly rather than dressed up. (If you're still orienting to what this category even is, here's why the AI employee framing has the wrong shape — it explains what a team of specialists does that a single generalist can't.)
Organizational memory. The agents build context about your business over months of use, not one session at a time. Ask a follow-up question in month three and it benefits from what was established in month one — you don't re-explain who your customers are every time you open a new conversation.
Proof of adoption. An Admin Console shows per-user, per-team, per-agent usage and the credit cost of every execution. If someone has to justify AI spend to a budget owner, this is how — usage by person, not a vague sense that "people seem to be using it."
Named specialists, not a single bot. Function-shaped agents mean a finance lead and a marketing lead each get someone specific to their function, rather than sharing one general assistant that's equally mediocre at everything.
How it gets installed
In Slack, someone with app-install permission adds Appy from the App Directory or an install link — a few clicks and an OAuth approval. It's available to the workspace, or scoped to specific channels, right away. For more on running AI agents for Slack and what separates a working agent from a chat window, that post goes deeper.
In Microsoft Teams, an admin approves the app through the Teams Admin Center first, then adds it to specific teams or channels — a heavier process, driven by how Teams governs third-party apps rather than anything specific to Appy. If you want to understand the differences between Teams and Slack setup, that comparison covers each path in detail.
Either way, once it's in, using it looks the same: @mention the specialist you need, or send them a direct message, and the work comes back in that thread.
What it costs a team in effort
Installing the app is the fast part. The part that actually determines whether it's useful is connecting your real systems — your CRM, your calendar, your financial tools, whatever the relevant specialist needs to do real work instead of answering in the abstract. A team gets value from connecting its actual systems, not from watching a demo. Expect the first real session to involve pointing an agent at an actual task — a report that's due, a list that needs research, a page that needs copy — rather than a general "see what it can do" exploration.
What it doesn't do
Worth stating directly, because it builds more trust than a vague claim of capability: agents draft and don't auto-send outreach on your behalf. Finance agents build models and flag discrepancies; they don't move money or file taxes. And the platform doesn't replace the judgment of the people on your team — it gives specific specialists the ability to do defined work faster, with a record of what they did and why.
Appy.AI currently runs across 651 organizations, with 31,516 agent executions logged since March 2025.
One flat monthly fee. Named specialists in Slack and Teams. No per-seat pricing, no dashboards to manage.
$100 in free creditsNo card required.