Agentic AI consulting and AI agent advisory
Paul Okhrem provides agentic AI consulting for companies deciding whether a workflow should use an AI agent and how to control it in production. The scope can cover one use case or a wider agent architecture. It defines allowed actions, evaluation, human escalation, operating ownership and the evidence needed to proceed, revise or stop.
What is agentic AI consulting?
An AI agent can use models and tools to choose and perform steps toward a goal. Agentic AI consulting asks whether that autonomy is useful, what actions it may take and how the company will detect and contain failures.
Paul’s advisory work covers use-case fit, build versus buy, architecture, evaluation and production acceptance. It does not mean every workflow needs an autonomous agent or that a demonstration proves safe operation.
When should you hire an AI agent consultant for one workflow?
A bounded engagement fits a consequential workflow such as gathering approved account information, preparing a quote for review or triaging an internal service request. Define the task, users, systems and exceptions before selecting an agent framework.
- Fit decision: compare an agent, a copilot, fixed automation and a process change.
- Proof of concept: test representative tasks, permissions, failures, cost and human-review effort.
- Production decision: require evidence for reliability, monitoring, fallback and support ownership.
These are possible design scenarios, not claims of completed client projects. A simple scripted chatbot or a stable rules-based workflow may not need this level of advisory work.
When does a company need wider agentic AI advisory?
A portfolio or architecture mandate is appropriate when several agents share data, tools, infrastructure or controls. The work defines common permissions, orchestration, evaluation standards, cost limits, vendor choices and accountability across teams.
Start with a small number of justified workflows. Multi-agent complexity is not a goal in itself. For broader organizational change, connect the architecture to AI transformation consulting and funded internal owners.
Agentic AI, generative AI and fixed automation
| Approach | Typical behavior | Useful starting point |
|---|---|---|
| Generative AI | Produces text, code or other output; it can also be a component inside an agent | Drafting, summarizing or answering with appropriate review |
| Fixed automation | Follows predefined rules and paths | Stable, well-understood processes |
| Agentic system | Selects steps and uses tools within allowed boundaries | Variable tasks that justify controlled runtime decisions |
See generative AI consulting for model and retrieval choices, or AI automation consulting when a fixed workflow is the better fit.
What must be tested before an agent can act?
- Allowed tools, data access, action limits and approval steps.
- Task success, unsupported answers, incorrect actions and recovery behavior.
- Prompt injection, tool-output handling and attempts to exceed permissions.
- Latency, cost per completed task and human oversight effort.
- Audit logs, monitoring, escalation, rollback and a named stop authority.
Use the agentic AI governance register to record controls and evidence. A high test score does not override a critical access or safety failure.
What does Paul’s engagement produce?
Expect a workflow or architecture decision record, evaluation plan, autonomy and permissions map, vendor comparison where needed, and production acceptance checklist. Assign process, technical, control and support owners before rollout.
Paul’s internal company experience is first-party operating context, not independent client validation. The Proof Standard explains evidence boundaries; the agent statistics guide distinguishes current survey findings from forecasts.
How much does agentic AI consulting cost?
Paul’s consulting rate is USD 1,000/hour, with an 80-hour minimum and USD 80,000 floor. The scope identifies the workflows, review gates and deliverables. Engineering, tool subscriptions, model usage and managed support are separate.
The client selects its builder. If Uvik Software or Elogic Commerce is proposed, Paul’s relationship with the company is disclosed before the decision. See published terms and implementation leadership.
Frequently asked questions
Does every AI agent need a multi-agent architecture?
No. Use the simplest architecture that meets the task and control requirements. Extra agents add coordination, evaluation, cost and failure-handling work.
What is an agentic AI proof of concept?
It is a bounded test of one use case against agreed task, quality, cost and oversight criteria. Its purpose is to decide whether further investment and autonomy are justified.
Can an AI agent operate without human review?
Only if the specific use, risk, permissions and evidence justify that arrangement. Some actions need approval or must remain outside the system’s authority. The control model is agreed before release.
How is success measured?
Use representative tasks and a client-owned baseline. Track completed work, errors, exceptions, costs and oversight effort. Record the measurement window and material changes rather than claiming success from a demo.
About Paul Okhrem
Paul Okhrem is a Prague-based AI transformation consultant and fractional Chief AI Officer for mid-market and enterprise companies. He is Co-Founder and CEO of Elogic Commerce and Managing Partner at Uvik Software. He has built B2B and enterprise software since 2009.
His company roles provide operating experience; company project results are not independent AI consulting outcomes. Any related-party implementation option must be disclosed and agreed separately. Read the evidence and measurement method.
Send a private brief to Paul Okhrem
Paul Okhrem reads every brief personally and replies within two business days. Start with the decision, its owner and the deadline. You will get an honest no if the fit is wrong, with a referral when possible.
Co-Founder and CEO of Elogic Commerce; Managing Partner at Uvik Software. Company experience is not a guarantee of a consulting result. Read the background and published terms.