Agents that carry the load.
A System Foundry agent isn't a prompt with a wrapper around it. It's a station on a line: scoped responsibility, supplied context, a defined tolerance, and a gate it can't pass without clearance.
The decision layer
Where judgment happens, and where it's held to account.
Custom agents
Agents scoped to a single process — weighing a case, committing to an outcome, and keeping the basis for it.
Process orchestration
Long-running work sequenced across many steps, surviving restarts and partial failure without losing its place.
Retrieval and context
Decisions grounded in the organisation's own records rather than in a model's recollection.
The surfaces
What people actually touch — operators, staff, and customers.
Review interfaces
Operator surfaces where a person sees the case, the evidence, and the recommendation — then clears or rejects it.
Mobile applications
Native-quality applications on iOS and Android for the people who work away from a desk.
Embedded widgets and tools
Purpose-built components that drop into an existing site or portal and do real work, not just display it.
The connective tissue
What ties it to the business, and what holds it up underneath.
CRM integration
Bidirectional connection to the systems a business already runs on, without asking it to change how it works.
Marketing and lead systems
Capture, qualification, routing, and follow-through — automated end to end and measurable at every step.
Secure cloud architecture
Private networking throughout. No public data plane, no ambient credentials, least privilege by default.
Precision comes from context, not cleverness.
A general model reasons well about the world. It knows nothing about how your industry actually decides — the norms, the exceptions, the deals that went wrong and why. That knowledge is what separates a plausible answer from a correct one, and it is the thing every System Foundry agent is built on.
Industry-specific
The vocabulary, the underwriting norms, the edge cases, and the failure modes of one domain — not general knowledge stretched to fit it.
Historical
Years of real decisions and what they actually produced. The agent reasons from precedent in the same domain, not from first principles each time.
Applied at the point of judgment
Context is retrieved per station and scoped to what that specific decision needs. Precision comes as much from what an agent is denied as from what it is given.
A model that has read everything still has not read your last four hundred deals. That is where accuracy actually lives.
This is why retrieval is not a feature bolted onto the agents — it is the ground they stand on. Every consequential judgment is traceable to the records that informed it, which is what makes the decision reviewable, defensible, and worth automating in the first place.
Where the industry says trust it, we say check it.
Knowledge, not recall
An agent operating on a model's memory is guessing with confidence. Ours reason from retrieved context — your actual documents, records, and prior decisions — so any output can be traced back to a source.
Bounded, not open
Agents get a scope and the tools to act inside it, and nothing beyond. The boundary is part of the specification, not a guardrail bolted on afterwards.
Gated, not supervised
Supervision means someone watching. Gating means the process cannot advance past a defined point until a person clears it. One depends on attention; the other holds when attention lapses.
Recorded, not reported
Every consequential decision leaves a durable trail — what was decided, on what evidence, under whose authority. Reporting is a view over that record, never a substitute for it.
Engineered to a tolerance.
See how manufacturing discipline translates into software that holds up.