Build an agent team.
Keep your people in charge.
We build agent teams that work alongside your people, inside your security and governance.
Three roles.
One line of authority.
Watch the line hold.
Everyone can buy the same AI. The return shows up where it's built into how the work runs.
The shopper chose financing.
IBM i decided.
At an agent's checkout, Silver Lake's credit decision runs where it always ran: the lender's own rule on IBM i. Only an id and the amount cross, no Social Security number and no date of birth. The shopper accepts the terms, not the agent. Nothing on IBM i was rewritten. A door was put in front of it.
See the proof →A live credit decision at an agent's checkout, written once to the record. 275 of 275 automated tests pass.
The agent filled the cart.
The shopper made the call.
Shopping a demonstration store for a shopper, an AI agent built a $4,980 cart. With $1,899 already spent, it would have put the shopper over a $5,000 limit. The store said no; the shopper raised the limit and made the call. The agent proposes the cart. A person commits, every time.
See the crossing end to end →Would have broken the shopper's limit. The store held the line; a person moved it.
Five agents work a home loan.
Four people make the calls that bind.
Silver Lake Financial Group, a demonstration lender, runs this on IBM i. Scoped agents chase a dozen parties across a 20-day loan while named people decide at each gate.
Follow the loan →Every call that binds the lender waits for a named person.
Alder & Pine Home and Silver Lake Financial Group are fictitious demonstration companies. Nothing is really sold or lent.
Where does your team stand?
Four questions, about a minute.
Every agent team we build answers these four before it touches production. Your answers carry into the workspace.
More inside: the Agent-Ready Read, Silver Lake's desks, Ask the Work and Model Watch.
Start with one workflow and one small team.
Ninety days, while today's systems keep running. You sign the benchmarks before we build, and success is measured by one number: how often your people need to override the agents, falling over time.
Built by people who've run the seat: a decade as CTO of a billion-dollar consumer-finance enterprise, forty years of regulated IBM i.
Built In.
One idea, one proof, one next step. Every two weeks, three minutes. Agent-ready IBM i and agent-native commerce from Pegasus4i.