Understanding your company data
Praxeum starts with what your team already does: your messages, docs, and tickets. Read-only, and only the spaces you choose.
What it learns becomes skills: small, reviewable procedures your agents can follow. Each one starts as a draft your team approves before any agent uses it.
Finding the patterns
Your policies and documented procedures are the foundation. On top of them, Praxeum finds how the work actually happens: the recurring steps, the exceptions, the rules that never reached a doc.
'No, do it this way.' The corrections are where the real procedure lives.
Opening a pattern
Doc vs practice
Your policy says 30 days. Your team has refunded annual plans up to 60 days, 12 times since January. Which is right?
annual plans → refunds up to 45 days
You decide where the doc is wrong, on purpose.
No conflict? Praxeum still builds the skill from your policy, ready for your AI to run.
One human approval
This is a skill: the actual file an agent reads and follows. Review it, edit if you need to, then approve. Nothing reaches an agent until you do.
# refund-exceptions
Decide a customer refund from the plan and timing.
## steps
## tools
stripe · refunds.create
Added to your catalog
Served over MCP
No new AI to buy. Praxeum serves the skill over MCP to the licensed AI your team already runs, so it acts the way your company does.
The skill interpreter
Skills are Markdown, the format the big AI platforms are standardising on. But a model can read Markdown and still improvise. To make sure it runs the skill as intended, Praxeum's skill interpreter binds the parts that must never vary to reviewed, tested code.
# refund-exceptions
Decide a customer refund from the plan and timing.
## steps
## tools
stripe · refunds.create
// the parts that must never vary const WINDOW = { annual: 45, monthly: 30 } function inWindow(days, plan) { return days <= WINDOW[plan] }
Skills become a co-worker
Approved skills group into a co-worker: a named agent with a job, reachable where your team already works.
Reach them in Slack, Teams, or email, or from Claude and ChatGPT with a command.
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:
audit onboarding-runbook@v5 · executed by Jeff · 3 steps · $0.03 · #4131
Your company brain
The same reading that builds your skills also builds a brain your team can just ask, in Claude, ChatGPT, Slack, or Teams. Every answer is scoped to what that person can see. A real time saver, from day one.
Drift detected
Praxeum keeps reading. When the way of working moves, it notices, and it does not quietly average the change in.
“We’ve been holding annual refunds to 30 days since September. 45 was too generous.”
seen 8× · 3 people · since Sep#support-opsWhen reality moves, the skill goes back for review. Never silently averaged.
Re-review
You decide, not an average. Here is what changed, and why, before anything ships.
annual plans → refunds up to 45 days
annual plans → refunds up to 30 days
Approved as v4. Back in service, and your co-workers pick it up.
Until a human rules, the agent holds off on the part in doubt.
Now your AI does, too. Verified, audited, and yours.
Private beta, a few teams at a time. Bring your most painful repeated workflow. We’ll turn it into a skill your AI actually follows.
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Where knowledge becomes action.