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Private beta

Your AI agents don't know how your company actually handles refunds.

Your real processes aren't in your policies. They're in your conversations. Praxeum reads how your team actually works and turns it into skills your AI follows, with a person approving every one.

Request early accessSee the demo

Humans decide, AI co-workers do the steps

One team. Some of them are AI co-workers.

Four examples of how that looks, each in the tool its team already uses. The names and cases are made up; the way the work moves is how Praxeum runs.

  1. Priya asks in #support-ops.
  2. Carmen checks the skill and works out the refund.
  3. Sarah signs off, because money moves.
  4. The record keeps who did what, and what it cost.

Example co-workers and cases

Fernhill · Slack
# support-ops12 · Refunds, escalations, customer ops
Today

Priya Nair9:41 AM

@Carmen a customer wants a refund, annual plan, 41 days in. Can we do it?

CarmenAPP9:41 AM

Checked refund-exceptions@v3: annual plan, 41 days in, inside the 45-day window. The refund is $240. Refunds need a human OK before the money goes out, so I’ve asked Sarah to sign off.

Sign-off needed · refund-exceptions@v3

Refund $240 to a customer on the annual plan (41 days). Requested of Sarah Chen.

Approved by Sarah Chen · 9:42 AM

CarmenAPP9:42 AM

Done. $240 refunded on the annual plan. Logged to the audit trail.

Message #support-ops
Mail

New hire: Marco Reyes starts Monday

You to jeff@fernhill9:12 AM

Hi Jeff, Marco Reyes joins the support team on Monday. Can you get him set up before then?

Re: New hire: Marco Reyes starts Monday

Jeff AI co-worker jeff@fernhill9:14 AM

to you

Done, Marco’s ready for Monday. I ran onboarding-runbook@v5:

  • Provisioned accounts and access Workspace
  • Sent the welcome and first-week plan Slack
  • Booked the kickoff call Notion

Reply if anything’s off and I’ll adjust.

Copilot
CopilotWork

@Sam Northwind wants 15% off their renewal. Can you draft the follow-up?

Sam AI co-worker

Drafted with renewal-followup@v2. Northwind renews in 30 days on the annual plan:

Re: your renewal

Thanks for three good years. For the renewal we can offer 15% on the annual plan, confirmed by our team this week.

Sign-off needed · pricing-exceptions@v1

15% is above the 10% Sam can give. Requested of Tom Baker, head of sales.

ApproveDecline

Approved by Tom Baker

Sent to Northwind with the 15% offer.

Message Copilot
Claude
ClaudeNoor · Support and ops

Payments are failing since 02:14. What do we do?

Running incident-runbook@v4: checkout errors at 38%, started with the 02:10 deploy. Rolling back needs the on-call lead, so I’ve asked Ines to sign off.

Sign-off needed · escalations@v2

Roll back the 02:10 deploy and page the payments team. Requested of Ines Moreau, on-call lead.

ApproveDecline

Approved by Ines Moreau

Rolled back. Checkout errors are back under 1%, and the status page is updated.

Reply to Claude…

Illustrative examples. Every step runs on a skill a person approved.

  • A person approves every skill before a co-worker can use it.
  • A person signs off before money moves.
  • Every run is on the record, with its cost.

Where the real process lives

Your company already knows how it works.

A brain formed from thousands of small points

  • Conversations

    Chat threads: the exceptions, the corrections, the "no, do it this way".

  • Docs

    Wikis and shared drives: the policies and runbooks, cited back to the page.

  • Meetings

    Call transcripts, for the meeting series an organiser chooses to include.

Read-only, and only the spaces you choose. What Praxeum finds becomes skills: small, reviewable procedures a person approves before any AI can follow them.

The idea behind Praxeum

From approved skills to a team

Meet your AI co-workers.

Approved skills group into an AI co-worker: a named bundle of approved skills with a job, reachable where your team already works. Carmen handles refunds in #support-ops and asks Sarah before money moves. Jeff onboards Marco by email and logs every step.

CCarmenFinance
  • refund-exceptionssign-off
  • billing-exceptionssign-off
  • invoicingexecute
Runs on Claude · your connection@carmen · carmen@fernhill
SSamSales
  • renewal-followupexecute
  • pricing-exceptionssign-off
  • lead-qualificationsuggest
Runs on Copilot · your connection@sam · sam@fernhill
JJeffHR
  • onboarding-runbookexecute
  • leave-requestssign-off
Runs on ChatGPT · your connection@jeff · jeff@fernhill
NNoorSupport and ops
  • escalationssign-off
  • ticket-triageexecute
  • incident-runbookexecute
Runs on Claude · your connection@noor · noor@fernhill

Four examples. Yours will look like your team.

  • Claude
  • ChatGPT
  • Cursor
  • Copilot
  • Gemini

They run on the AI you already license, on your connection. Praxeum gives them the skills and the rules. It never sells you another agent.

Connectors

Works with the tools your team already uses.

Connect a source in minutes, read-only and scoped to the channels, folders, and spaces you pick. Permissions travel with the knowledge, so everyone sees exactly what they could see before.

  • Slack
  • Google Meet
  • GmailBuilding
  • JiraBuilding
  • LinearBuilding
  • IntercomBuilding
  • SalesforceBuilding
  • Microsoft TeamsBuilding
  • SharePointBuilding
  • Google Drive
  • Notion
  • Google CalendarBuilding
  • ConfluenceBuilding
  • ZendeskBuilding
  • HubSpotBuilding
  • GitHubBuilding
  • OutlookBuilding

Missing yours? Request a connector

How it works

How a co-worker learns your way of working.

  • Doc vs practice

    Your policy says 30 days. Your team refunded up to 60, twelve times since January. Praxeum shows you the conflict with the evidence, and you decide, on purpose.

    See the conflict

  • Tested on past cases

    Before anyone approves a skill, it is replayed on real past cases and graded against how your team decided them. The approver sees every miss.

    See the replay test

  • One human approval

    A skill is the actual file your AI reads. Review it, edit it, approve it. Nothing reaches a co-worker until you do.

    See the skill

  • Served over MCP

    No new AI to buy. The approved skill goes to the AI you already run, which carries the version it ran.

    See the serving step

  • The skill interpreter

    A skill is Markdown the model reads. The parts that must never vary run as reviewed, tested code.

    See the interpreter

  • Ask your company brain

    The same reading builds a brain your team can just ask, in Claude, ChatGPT, Slack, or Teams. Every answer is scoped to what that person can see, cited, and marked unverified unless it comes from an approved skill.

    See the brain

  • Drift detected

    When the way of working moves, the skill goes back for review, never silently averaged. Until a human rules, the contested step is served as ask-a-human.

    See drift

Governance

The rules are set by people, once.

Every AI co-worker runs under the same workspace rules, and a person sets them.

  • Only approved skills reach an AI co-worker
  • Human sign-off before money movesSarah Chen
  • Every action audited, your AI and agents over MCP included
  • Cost tracked on every run
  • Where your data livesEU-hosted
The rules are set once, by people, and every co-worker runs under them.

Straight answers

Isn’t this just enterprise search?
Retrieval finds docs; we mine the exhaust into executable, verified skills. Retrieval structurally can’t surface the workarounds that never reached a wiki.
Do co-workers replace my agents?
No. A co-worker is a bundle of approved skills with a name and a job, running on the AI you already have, on your connection.
Are you reading everything?
Read-only, you scope every source, scoping is employee-visible, and permissions travel with the knowledge. For Google Workspace, Praxeum asks for read-only Google Drive access and reads only the shared drives and folders your organization selects, to draft cited skills a person in your team approves. How we handle Google user data, including the Google API Limited Use requirements, is in our Privacy Policy. See also Security.
Will it be accurate?
Nothing is used until a human approves it, and every claim is cited. When reality moves, the skill goes back for review, never silently averaged.

Private beta

Your company already knows how it works. Now your AI does, too.

Verified, audited, and yours. Private beta, a few teams at a time. Be an early user: bring your most painful repeated workflow and we'll turn it into a skill your AI actually follows.

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