01
Which multi-step process is suitable for agentic execution?
Identify workflows where coordination and tool use create value without handing uncontrolled authority to the model.
AI, automation and optimization
Agentic AI
Move from models that answer questions to systems that can coordinate steps, use tools and act within explicit boundaries.
Agentic AI introduces a different operating problem from a conventional assistant. Once an AI system can plan tasks, call tools, update systems or coordinate other agents, the organization needs explicit limits on authority, approvals, retries, escalation, identity and auditability.
We design agentic systems around the business process first, deciding which steps may be autonomous, which require deterministic workflow logic and where a person must remain accountable.
NoèmeX perspectiveMake the system intelligible first: reveal the structure, constraints and variables that determine where change can produce the intended outcome.
Related leadership priorities
AI priorities depend on who owns the decision, risk and operating outcome.
Use these pathways to connect AI, automation and optimization work to the executives responsible for governance, foundations and business performance.
Questions we address
The decisions that shape the agentic ai work
We start with the business process, decision, information and operating controls around the use case before selecting models, platforms or automation technologies.
02
What actions may an agent perform?
Define tool permissions, transaction limits, data access and approval thresholds for every system action.
03
Where should deterministic workflow remain in control?
Separate flexible reasoning from rules, validations, approvals and controls that should not depend on model behavior.
04
How will agent activity be audited and recovered?
Design logs, state, checkpoints, retries, rollback, escalation and human intervention for production operation.
What we deliver
A production-minded capability, not an isolated experiment
The exact scope depends on the organization and use case, but the work typically produces a combination of these outputs.
01
Agentic-process design
Task decomposition, autonomy boundaries, tool calls, roles and human checkpoints mapped to the business process.
02
Agent and tool architecture
Agent responsibilities, orchestration pattern, APIs, credentials and system-action boundaries.
03
State and workflow design
Persistent state, deterministic controls, queues, approvals and recovery paths around model-driven steps.
04
Evaluation framework
Task completion, action correctness, tool-use accuracy, policy adherence and failure-recovery testing.
05
Security and audit controls
Identity, permissions, logs, traceability and review for every consequential action.
06
Production operating model
Monitoring, incidents, model changes, tool changes, versioning and human ownership over time.
Relevant enterprise context
Evidence and operating context from enterprise transformation work
The portfolio does not document a production agentic-AI implementation. The global safety platform below demonstrates the kind of multi-step, role-based, approval-sensitive workflow that agentic automation must respect.
Governed multi-step workflows40 countries100+ plants · Safety-critical operations
Designing automation around roles, approvals and local/global controls
The safety platform standardized complex LOTO workflows across 40 countries with role-based access, multiple approval steps, configurable local requirements and global governance. This documented environment illustrates the process and control architecture that any future agentic automation would need to operate within; it is not presented as an agentic-AI implementation.
Read the related caseRelated services
Continue into the adjacent capability.
AI, automation and optimization often intersect with data, analytics, process and governance work. These pages keep each capability focused while making those relationships explicit.
How we work
Use the engagement model that fits the problem.
Work can begin as focused advisory and continue into implementation, embedded support, managed operations or run-and-maintenance depending on the maturity and criticality of the capability.
Advisory
Assess whether a process is appropriate for agentic automation and define autonomy boundaries.
Read more →Project delivery
Engineer agents, tools, deterministic controls, evaluations and human checkpoints.
Read more →Run & maintenance
Monitor agent behavior, tool integrations, incidents and model changes in production.
Read more →Your Contact Persons
Connect directly with the people responsible for this work. Explore their experience and contact options.
Zahra Fathisalout
Founder · Eng., CSP, CMLAI
Corporate governance · ASC-C.Dir. candidate
Works across strategy, enterprise transformation, data, AI and governance, bringing operational engineering experience to complex transformation decisions.
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Brendan Young
B.Com, Director of Operations
Connects transformation design with operating discipline, drawing on logistics, fulfillment and high-throughput operational leadership.
View profile →
Agentic AI
Start with the business problem, the workflow and the decision that needs to improve.
Share the process, systems, decisions, actions, approvals and risks involved. Our teams can determine where agentic behavior is useful, where deterministic automation is safer and how to govern the combined system.