Sophizo / Agentic AI Team
Governed AI teams are groups of agents with defined jobs, named human owners and approval boundaries. Sophizo builds them around existing systems in sales, marketing, finance, HR and client success. Start with one team and expand through evidence, with R1 to R4 rules deciding who checks the work. See agent review capacity.
Scoped access. Human approvals. Every action logged.
01 / The team, not another tool
Pick a business unit. See the roles an agent team can cover, and the decisions that stay with your people.
Sales / scoped roles
Pricing and contract terms: an agent prepares, a person decides and executes.
One unit, then the next
Start with one business unit. Prove a bounded workflow, name its owner, then add the next team when review evidence supports it. R1 reads and drafts, R2 changes internal records, R3 acts externally only with approval, and R4 prepares while a human decides and executes.
02 / Learning you can inspect
Not a mysterious self-improving system. A visible correction, a human-approved change, and a better next attempt. Try this fictional collections example.
01 / Before
“Your invoice is overdue. Please arrange payment.”
A generic draft misses the context: this invoice is disputed.
02 / Human feedback
“Check for a dispute first. If one exists, hold the reminder and ask the account owner.”
A proposed change. Not active until a person approves.
03 / Proposed next draft
A better draft is waiting for your approval.
Use the approval control to see what changes and what stays protected.
Better work, not broader permissions. Learning cannot increase access or authority. Only a person can approve a rule change. R4 decisions and execution always stay human. Illustrative example only.
03 / Authority by risk
The AI vendors themselves now list prompt injection and hallucination as known agent risks. R1 reads, R2 updates, R3 speaks for you and R4 moves money, and each level has its own approval rule.
Example work item / R3
Prepare a payment reminder for a named approver.
Human review has limits
Human reviewers may experience alert fatigue, may lack sufficient context to evaluate agent decisions, or may not review agent actions in time to prevent harm.
a recent public AI company IPO filing
04 / A clear scope. A named owner.
Four team sizes. One 12-month minimum term. Setup builds the team. The monthly retainer keeps it governed and maintained. John Utley leads every engagement.
For early-stage startups (pre-seed to Series A) and small businesses under $5M revenue.
+ $500/mo
12-month minimum. Booking opens Calendly in a new tab.
For mid-stage startups (Series A to B) and growing businesses with $5M to $25M revenue.
+ $1,500/mo
12-month minimum. Booking opens Calendly in a new tab.
For late-stage startups (Series C to pre-IPO) and mid-size companies with $25M to $200M revenue.
+ $4,000/mo
12-month minimum. Booking opens Calendly in a new tab.
Need to scope the work first? Start with the $2,500 Diagnostic Sprint.
Explore the Diagnostic SprintFrom rulebook to routine
Launch Team: live in two weeks from the signed rulebook. Broader teams are scoped to the systems and approvals involved.
We work with the tools you already own where they fit. Platform-agnostic, with no vendor resale or markup.
We list what you want handled, what it may touch and what stays human. You sign the rulebook.
We connect the systems, configure the agents at Level 0 or 1, and train your team.
Autonomy changes only after human review of clean logs. Learning alone never changes permissions, and R4 remains human-decided and human-executed.
We review the log, fix what drifted and add the next job.
Before you decide
Agentic AI Team packages carry a 12-month minimum. Advisory and fractional leadership engagements are month-to-month after the first quarter.
Yes, and many owners start that way. The agent is the cheap part. Deciding what it may touch, connecting it to your books and CRM, writing the approval rules and checking its work every month is the job we do.
Anything involving money, contracts, hiring or data leaving your systems, and anything sent under your name until you approve that specific pattern. Those stay human.
Your AI platform and usage fees, billed to you directly or passed through at cost. For most small teams that is a small fraction of the retainer.
John Utley leads every engagement and is accountable for it.
Receptionist services handle one channel. An Agentic AI Team covers whole business units, with governance, a named owner and a monthly audit.
A four-level scale Sophizo applies to every agent and every action it can take. R1 is internal reading and drafting. R2 is internal, reversible changes. R3 is anything that reaches a customer, candidate or employee. R4 is money, contracts, legal exposure, hiring decisions, sensitive personal data and access changes.
No. Approvals belong to named people. R3 actions need a person's approval, or a written pre-approved pattern after 30 days of clean logs. R4 actions are always decided and taken by a person.
Every action at every level, with what changed, when and, from R3 up, who approved it. The log is reviewed in a monthly audit.
No. It is platform-agnostic and applies the same way on any agent platform.
R1 and R2 actions can be undone. The owner can stop any agent at any time. Every incident is reviewed, the rulebook is updated, and the agent's level can be lowered.
In AI research it means a system that helps build a better version of itself. We apply the idea to the business: every person, team and business unit runs a learning loop, all feeding one company-wide loop, so the business learns from its own decisions and outcomes. A person approves every change to the rules, at the loop matching its risk level.
Less busywork. No blank checks.
Book 30 minutes. Leave with the three jobs an agent team should take first, whether or not you work with us.