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Its own identity. Never a shared login or a person's credentials.
We design, connect, test and run AI agents that act in SAP and other business systems, with scoped permissions, human approvals and a full audit trail.
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Inputs, rule, decision and reversal path logged
A chat assistant answers questions. An agent changes records. That's why it needs the same six things you'd give any new colleague before day one.
Its own identity. Never a shared login or a person's credentials.
Least-privilege roles mapped to your SAP and system authorizations, with segregation of duties.
Policies, thresholds and exceptions written down before it acts.
A short list of actions with validated inputs. Nothing outside the list.
A named person who approves what is above its authority and owns the outcome.
What it saw, what it decided and what it changed, ready for audit.
We pick one bounded task with a clear owner and a measurable outcome, and set the autonomy target.
We connect the knowledge it may read and the actions it may take, through APIs your teams approve.
We set thresholds, approvals and segregation of duties, and decide which actions must be reversible.
We test it against real scenarios, edge cases and attempts to push it past its limits.
We monitor quality, cost and exceptions, review it on a schedule and keep a way to stop it instantly.
Prepares the fix with evidence and waits.
Policy check · explanation · approval queue
Approves or rejects in one click.
It acts on a wrong assumption
Validated tool inputs and a policy check before every action
It has more access than it needs
Its own identity with least-privilege roles and segregation of duties
It quietly gets worse
The test suite re-runs on every change; quality and drift are monitored
Nobody owns it
A named business owner and a technical owner, with a review schedule
Its action can't be undone
Reversible actions first, approvals for the rest, and a kill switch
See the full reference case: a vendor invoice exception handled by an agent, with SAP controls and audit.
The framework behind this method: business context, knowledge, reasoning, tools, systems, governance, human oversight and outcomes.
It requires business context, governed knowledge, authenticated tools, identity, human oversight, evaluation, observability and exception handling.
No. This page covers agent engineering across enterprise systems. AI for SAP focuses on bounded SAP processes, access and transactional controls.
Oversight is designed according to business risk, authorization, reversibility and the level of agent autonomy.
Enterprise Agent Architecture™ provides the research framework; an engineering engagement applies it to a bounded system and operating context.
We'll tell you whether an agent can do it, how far it should go alone, and what it takes to run it safely.