Patricia, an AI teammate in Slack
The AI business assistant that works inside Slack
Most tools sold as an AI assistant for business stop at drafts and answers. Patricia executes. She joins your Slack, connects to the tools you already pay for, and finishes the work: the recap posted, the CRM updated, the report built, the invoice chased. Anything that leaves the building waits for your yes.
She is built for startups and small teams that run on Slack, from a solo founder to about fifty people, and she works like a teammate rather than a tool: you delegate in plain language, she comes back with the work done.
How it works
Connect your tools once. Then just ask.
No workflow builder, no prompt courses, no six-week rollout. Patricia works the way a good new hire does: you show her where the work lives, she starts doing it, and she checks in before anything important goes out.
Step 01
Connect your tools once
Add Patricia to your Slack workspace and invite her to the channels where the work already happens. Connect the tools she should work in, from your CRM and calendar to Google Ads and GA4, through the dashboard. Each connection is a scoped grant you control: you decide what she can see and what she can touch. It takes minutes, there is nothing to host, and your team does not have to learn a new app, because the interface is the Slack they already live in.
Step 02
Then just ask
Ask in plain language, in the channel: recap this call, update the deal, build the monthly report, chase that invoice. No prompt engineering, no trigger diagrams, no picking the right template from a library. She also volunteers. She sits in on meetings, notices what needs doing, and offers a first stab before anyone gets around to assigning it. Over time she learns your voice and your standards from your edits, so the second draft of anything is closer than the first.
Step 03
She proposes, you approve, she executes
Patricia shows you exactly what she wants to do before she does it. Reading and drafting run on their own. Anything that sends, posts, spends, or changes a setting waits for a yes from someone on your team, right there in the thread. After the yes, she executes, confirms what happened, and writes it to the audit log. You keep the judgment. She does the clicking.
That is the whole setup. By the end of week one, the pattern settles in: the meeting recap is waiting when you get back to your desk, the follow-up is drafted before you remembered to write it, and the approval requests arrive in the thread where the work lives. Nobody on your team had to change how they work. The work just started coming back finished.
Across the business
One assistant for the whole company, not one tool per chore.
Point solutions each take a slice: a notetaker for meetings, an automation for the CRM, a dashboard for reporting. Each one is another subscription, another login, another place context goes to die. Patricia is one teammate who carries the work across all of it, and she keeps the context between tasks, so the call she recapped this morning informs the follow-up she drafts this afternoon.
Meetings and recaps
Patricia joins the call, posts a TLDR in Slack with the full notes in the thread, and puts action items on the right to-do list with owners attached, in Notion, Asana, or wherever your team tracks work. Decisions land in her memory of your company, so next quarter nobody argues about what was agreed. And when an action item is work she can do herself, she offers a first draft before the meeting is cold, which is where a notetaker stops and an assistant begins.
CRM updates and follow-ups
The deal gets updated the moment the call ends: stage, notes, next step. Follow-up emails get drafted while the conversation is still fresh, and nothing goes out until someone on your team approves it. Renewals and check-ins get prepared before anyone remembers to ask. Your CRM stops being three weeks behind reality, because keeping it current stopped being anyone's chore.
Reporting from your connected tools
Ask for the monthly report and she pulls real numbers from GA4, Google Ads, Search Console, and the rest of your stack, then writes the story behind them in your voice: what moved, why, and what to do next. No more screenshot-and-paste Fridays, and no dashboard nobody opens. The report arrives in Slack, where the discussion about it actually happens.
Marketing execution
Budget pacing watched daily, competitor ads flagged when they change, search terms reviewed, ad variants and content drafted for approval. She runs the recurring marketing work in the same channels your team already runs it in, and ships after your yes. The founder who never had time to be the marketer finally has one on staff.
Ops and finance chores
Invoices chased politely and on time, status reports compiled from what actually happened, weekly updates written before anyone asks. She handles the admin that never makes it into anyone's job description but always ends up in someone's evening. The polite nudge on day seven goes out every time, because she never feels awkward about sending it.
And the rest of the week's work
Celebrations remembered, proposals drafted, customer onboarding run, weekly updates written. Every published use case, with real examples, lives on the hub.
Integrations
Works in the tools you already pay for.
An assistant is only as useful as what it can reach. Patricia connects to 1,000+ tools, with native depth on Google Ads, Meta Ads, Google Analytics 4, Google Search Console, HubSpot, Mercury, and Stripe. She reads from them to answer with real numbers instead of confident guesses, writes to them after your approval, and keeps the whole thread in Slack where your team can see it.
That is the point of an assistant over another app: no new tab to check, no new login to roll out, no data to migrate. She comes to where the work already is. Patricia works in Slack today, with Microsoft Teams support coming next.
The connections stay yours. She borrows the keys rather than holding them: credentials are encrypted and kept server-side, every use of a connection lands in the audit log, and disconnecting a tool in the dashboard cuts off her access in one click. A read scope stays a read scope, and writing to a connected tool is gated behind an approval on top of that.
Trust
An AI assistant for business that answers the trust questions.
Handing real work to an assistant only makes sense if you can answer three questions: what can it touch, who can see it, and what happens when it acts. Here are the answers, in plain language.
Approval gates on anything that matters
An audit log that cannot be edited
Data stored in the US
SOC 2 Type II audited
Never trains someone else's model
The full mechanics, including the honest list of what we have not built yet, are on the security page.
None of this is a marketing promise. The no-training commitment is written into the Data Processing Agreement, the subprocessors are published by name, and the audit reports are available to any prospect who asks. If your counsel or your client has a harder question, bring it to the demo. The hard ones are the ones we like.
Pricing
One workspace price. Every seat included.
Patricia costs $45 a month for your whole workspace, with 20,000 credits for finished work included. Everyone on the team can ask her for anything, so there is no quiet math about who deserves a license and who does not. Adding your tenth teammate costs exactly what adding your first did: nothing.
What do the credits buy? Finished work. A typical month of 5 client reports, 12 content briefs, and 40 ad variants fits inside the plan, and the pricing page shows what each kind of task costs on average, so you can estimate your own month before you spend anything.
Compare the alternatives. Per-seat copilots multiply by headcount, so the price of AI for the team quietly becomes a second payroll line. A human assistant is wonderful, and starts around $50,000 a year before benefits. Patricia is metered to the work she actually finishes: retries are free, credits roll over, and the spend cap is on by default, so a busy month never surprises you.
Start with 7,500 free credits, no card. See the full pricing breakdown
The honest comparison
Where Patricia fits, and where she does not.
Every vendor's comparison table awards itself green checkmarks down the whole column. Here is the version we would want to read: different tools solve different problems, one honest line each.
| Option | What it is | Pricing model | Best when |
|---|---|---|---|
| Patricia | Executes work across your connected tools, in Slack, behind approval gates | $45 a month for the workspace, every seat included | You want the work finished, not just answered |
| Microsoft Copilot, Gemini | Knowledge copilots: answer questions and draft inside your docs and email | Per seat, per month | You mainly need help inside documents |
| Lindy and other agent builders | Build-your-own automations from triggers, steps, and conditions | Per user, usage-capped tiers | Someone on the team enjoys building and maintaining automations |
| A human assistant | A real person, with real judgment, one task at a time | $50,000+ a year in salary | The work needs a person in the room |
If what you need is a chat window over your documents, a copilot is cheaper. If someone on your team loves building automations, a builder gives them more knobs. And the edge cases run the other way too: Patricia does not travel to the conference or read the room in a board meeting. For everything that happens inside your tools, though, she is the assistant who never sleeps, never forgets, and never resents the invoice chasing. Patricia is for teams that want that work done without becoming automation engineers.
FAQ
The questions teams ask before they hand over real work.
What does an AI business assistant do?
An AI business assistant handles the recurring work that surrounds a team: meeting recaps, CRM updates, reports, follow-ups, and the chores nobody owns. The useful distinction is between assistants that answer and assistants that act. Patricia is the second kind. She connects to your tools and executes the work in Slack, proposes the action before taking it, and anything that sends, posts, or spends waits for your approval first.
How much does an AI assistant for business cost?
It depends on the pricing model more than the tool. Knowledge copilots usually charge per seat, so the bill grows with headcount, and a human assistant starts around $50,000 a year. Patricia costs $45 a month for the whole workspace, every seat included, with 20,000 credits for finished work each month. You can start with 7,500 free credits, no card needed.
Can it access private company documents?
Only what you connect. Patricia sees the Slack channels you invite her to and the tools you link, and nothing else. She is not a workspace-wide crawler that indexes everything it can reach: you choose what each connection can see and do, a read scope stays a read scope, and disconnecting a tool cuts off her access in one click. If a document lives somewhere you never connected, she cannot touch it.
How does it handle confidential information?
Your data is stored in the United States, encrypted in transit and at rest, and never used to train models served to anyone else. What she learns from your team stays inside your account. Patricia is SOC 2 Type II audited and GDPR compliant, every action she takes lands in an append-only audit log, and EU transfers are covered by Standard Contractual Clauses. The commitments live in the DPA, not just on this page.
How long does setup take?
Minutes, not weeks. Add Patricia to a Slack channel, connect the tools you want her working in, and ask for the first task. There is nothing to host, no workflow builder to learn, and no prompt training for your team, because everyone already knows how to write a Slack message. She works in Slack today, with Microsoft Teams support coming.
What is the difference between an AI business assistant and ChatGPT or Copilot?
ChatGPT and Copilot answer questions and draft text, then hand the work back to you to finish: you still update the CRM, send the email, and paste the numbers into the report. Patricia takes the task end to end. She works inside Slack, reads and writes through your connected tools, proposes the action, and executes it after your approval. She also remembers your company between tasks, so context never has to be re-explained. The difference is who does the clicking afterwards.
What happens if it gets something wrong?
Nothing irreversible. Risky actions wait behind an approval gate, so a wrong draft gets corrected in the thread before it reaches a client or a ledger, the same way you would redline a junior teammate's first attempt. Retries are free and only finished work counts against your credits, so a redo never costs you twice. Corrections stick, because she learns your standards from your edits. And every action is in the audit log, so you can always see exactly what happened and who approved it.
Meet the assistant who finishes the work.
Connect your tools once. Then just ask. Book a demo and watch Patricia run a real task from your week, live.