Agentic AI Consulting
Custom AI agents that do the work — not tools that describe it.
Agentic AI consulting and custom AI agent development for mid-market and enterprise leadership teams. Strategy led by Jen Seregos. Built and deployed by a vetted engineering team. Designed with human-in-the-loop review from day one.
What agentic AI actually is.
An AI agent is not a chatbot. It's a system that reads from your data, makes a decision against your rules, takes a real action, and hands off to a human at the checkpoints you define.
A single agent replaces a recurring task. A system of agents replaces a recurring process. That's the shift executives are trying to make right now — from AI as a tool their teams use, to AI as infrastructure their organization runs on.
Most vendors sell you a tool and hope you figure out the workflow. We do the opposite: we redesign the workflow, then build only the agents the workflow actually needs.
What We Build
Six capabilities, one accountable relationship.
Multi-step workflow agents
Agents that read from your systems, make decisions against your rules, and take action across email, CRM, spreadsheets, and internal tools — not single-prompt chatbots.
Custom AI agent development
Purpose-built agents for regulated intake, sales operations, RFP response, translation review, and internal knowledge workflows — designed around your data and your compliance requirements.
AI operating systems
When one agent isn't enough: coordinated systems of agents that hand off to each other and escalate to humans at defined checkpoints.
Agent-readiness assessment
Before we build, we score whether your data, workflows, and team are ready. Where they aren't, we fix the pre-conditions — building on a broken foundation wastes the budget.
Human-in-the-loop by design
Every agent has explicit review points, audit trails, and rollback paths. This is what makes agentic systems safe for regulated industries and executive-visible operations.
Vetted engineering execution
Jen leads strategy and design; a vetted engineering team builds and deploys. You get one accountable relationship instead of managing a vendor stack.
How Engagements Work
Strategy first. Then we build.
Agent-readiness assessment
We score your data, workflows, and team against what agentic systems actually need. If the pre-conditions aren't there, we fix them first — no client has ever regretted this step.
Strategy & scope
Jen leads a working session to identify where agents create leverage, and — just as important — where they don't. You leave with a prioritized build list, not a wish list.
Design & build
A vetted engineering team builds against the defined scope. Every agent ships with audit trails, human-in-the-loop review points, and rollback paths.
Deploy & advise
Rollout happens against a real workflow, not a demo. Jen stays on as strategic advisor through the first operating cycle so the system survives contact with the org.
Frequently Asked
What executives ask before they build.
What is agentic AI, in plain terms?
Agentic AI is a system of AI agents that take multi-step actions on your behalf — reading data, making decisions, executing workflows, and handing off to humans when needed. It is different from a chatbot or a single-prompt tool. Done well, it replaces recurring operational work; done poorly, it creates confident-sounding mistakes at scale.
How is this different from buying an AI tool off the shelf?
Off-the-shelf tools solve the vendor's version of the problem. A custom AI agent is built around your data, your workflows, your compliance requirements, and the specific decision points where humans are the bottleneck. We build only where custom is the right answer — if a tool already exists that fits, we tell you.
Who is agentic AI actually right for?
Mid-market and enterprise organizations with (1) repeatable, high-volume operational work, (2) clean-enough data to act on, and (3) a leadership team willing to redesign the workflow — not just automate the mess. If any of those three are missing, we start with strategy or a readiness assessment before writing code.
What does a typical engagement look like?
It starts with a strategy engagement to identify where agents create leverage. From there, our vetted engineering partners build, test, and deploy custom AI agents against a defined scope. Jen stays on as strategic advisor through rollout. Timelines run 6–16 weeks depending on complexity.
Do you work with regulated industries?
Yes. Existing agentic builds include regulated chemical operations, medical translation, and property management intelligence. Compliance, auditability, and human-in-the-loop review are designed in from the start — not bolted on afterward.
How much does a custom AI agent cost?
Custom AI agent development is scoped per engagement. Simple single-agent systems start in the low five figures; multi-agent operating systems for enterprise workflows are larger. We do not sell templated packages — pricing follows scope after the strategy phase.
Ready to build agents that do the work?
I take on 3–4 new custom AI agent engagements per quarter.