The same agents, the same approval discipline and the same audit record, from a family's groceries to an SAP estate. What changes at enterprise scale is what you own: the host, the model agreement, the knowledge and the limits.
Household Ledger, Groceries, Personal Health, Home Employer, Landlord, Stokvel Treasurer. In your family chat, on prepaid credit.
Accounts Payable and Receivable, Buyer, Supplier Vetting, Compliance Clock, Legal Documents, Marketing Desk, Website Keeper, Creator Desk.
Everything above, plus what an enterprise has to own: a dedicated host, your own model agreement, your organisation's knowledge, and limits your finance team sets.
Enterprises already hold an agreement with the model provider. Use it. We meter every call and stop before your budget does.
If your organisation already licenses Claude, your agents run on that agreement, whichever form it takes: a direct Anthropic account, or Claude through Microsoft Foundry, Google Vertex AI or Amazon Bedrock. No second bill, no markup on tokens, and your own provider console as the final reconciliation. If you do not, they run on ours at a published rate.
Either way you see the same picture: what each agent spent, on which day, on which piece of work, against limits your finance team set per day and per month. At 75 and 90 percent of a limit, the people who own it hear about it in their own channel. At 100 percent, the agent stops and says so; nothing is silently allowed through.
A monthly statement reconciles our meter against your provider's own usage report, line by line.
Daily and monthly ceilings per estate, and per agent if you want them. A hard stop is a hard stop.
Spend rolls up by agent, by day and by the work item it served, so a cost has an owner and a reason.
Routine steps run on smaller, cheaper models; judgement runs on the strongest. Caching keeps repeated context from being paid for twice.
Our numbers next to your provider's numbers. If they differ, you see by how much and why.
Agents should not re-learn your business on every question. We compile it once, with every fact traceable to its source.
Before an agent goes live, a forward-deployed engineer spends a week with your team building its knowledge: the questions people will actually ask, the documents and systems that answer them, the words your organisation uses and what they mean, and who may see what.
That knowledge becomes a versioned asset your agents query, inside your environment, with a citation on every answer and a date on every fact. It is refreshed as your documents change and as your people ask new questions; a fact that may have gone stale is checked before it is used, never assumed.
Thirty to a hundred real questions from the people who will use the agent.
Process documents, system extracts, runbooks, history; and who is allowed to see each.
What "period close", "release" or "approved" mean here, so the agent means the same thing you do.
The agent answers the questions from day one. We iterate until it passes, with sources.
Signed off, versioned, handed to the agents. Refreshed on a schedule after that.
Incidents resolved in the functional lane; code changes carried from requirement to a transport staged for Quality. Production is never written.
Most SAP incidents are knowledge, configuration, data or authorisation questions. A functional agent, read-only, answers them inside your team's chat and prepares the fix for a named consultant to apply. When the answer is a code change, a governed bench takes it from refinement through build, independent review and test to a transport in Development, staged for Quality. A human commits every mutating step, and the builder is never the checker.
Your weekly EarlyWatch report becomes a worked list: every red and yellow finding classified into the lane that can act on it, with the SAP Notes and transactions attached, tracked week over week until it clears. Everything is parsed inside your environment; nothing leaves it unredacted.
A named digital team member can live in your Microsoft Teams, read what is shared with it, answer in channels and join meetings, under its own identity and its own audit record.
Tell us which system, which team and which process hurts. We come back with a readiness scope, a running-cost model and a go or no-go.
MshenguX AI