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Autonomous agents Governed Managed

Autonomous AI Agents — Deployed, Governed, Managed

Outcomes-first agents that use your apps, escalate to humans, and leave an audit trail. Start with Discovery $99, then Consulting $499, Starter $2,500, or Growth $8,000/mo — not another chatbot demo. When the workflow is already named, pay or Consulte on /plans/.

Map one process before you fund the build.

Map your first agent — Discovery $99 Contact

The problem

FAQ chatbots stall on real work

Help-center bots answer questions. They do not update the CRM, open a ticket with context, or wait for a human when the action is irreversible.

No owner after the demo

A prototype without a named operator, allowed tools, and a kill switch becomes shadow IT. Zion will not leave an agent without an owner.

No cost controls

Unbounded model calls and tool retries show up as surprise invoices. Agent work needs a spend envelope — see FinOps consulting.

No SLA, no audit trail

Production agents need retries, idempotency, human escalation, and a log of what the model was allowed to do. Demos skip that on purpose.

Agent vs chatbot

DimensionTypical chatbotAutonomous agent (Zion)
JobAnswer from a knowledge baseComplete a named workflow with tools
SystemsChat widget onlyCRM, ITSM, email, Slack, WhatsApp, internal APIs
GuardrailsPrompt textAllowed tools, approvals, data boundaries
OwnershipVendor demo accountNamed operator + written runbook
CostSeat or unbounded tokensScoped after Discovery; spend visible
SLABest effortWritten on Growth

Use cases we scope

Sales ops

Lead routing, CRM hygiene, and follow-up drafts with a human send. No invented pipeline metrics — we map the one motion you already run.

Support & IT

Ticket triage, knowledge retrieval with citations, and escalation when confidence or policy says stop.

Finance & ops

Exception queues, close checklists, and invoice routing — with approvals on anything that moves money.

Internal enablement

Policy Q&A grounded in your documents, onboarding checklists, and “where do I click” loops that stay inside your stack.

Controls before autonomy

Autonomy without controls is shadow IT. The five points below are the production minimum — write them before the first unattended tool call. CIO/CISO questions — data, actions, spend, audit, and ownership — are expanded in Enterprise AI agent governance & risk. No fake compliance badges on this page.

  1. Named owner — a human who can pause the agent and change the allowed-tool list.
  2. Allowed tools only — the agent cannot invent a new integration at runtime.
  3. Human approval — irreversible or high-cost actions wait for a person.
  4. Audit log — tool calls, inputs, and outcomes are written down.
  5. Kill switch & rollback — disable the agent without taking the rest of the stack down.

First workflow via Discovery

Do not start with a platform rollout. Map one workflow in Discovery $99: the system of record, the allowed tools, the human gate, and whether an agent is even in scope. If Discovery says wait or do-not-build, that is the deliverable — not a failed sale.

What Discovery writes

One process, data/action/spend boundary, ROI sketch (order of magnitude — not a guarantee), and a 30-minute readout. Offer details stay on /discovery/.

When to Consulte

Multi-tenant, regulated, or unclear enterprise scope — use Consulte before Starter. Growth and SLA are scoped after the first agent is governed.

Controls first. Then one workflow. Then autonomy.

Discovery $99 Consulte (enterprise) Plans

Enterprise AI agent governance & risk

A demo that can call tools is not a production agent. Governance is the written answer to five CIO/CISO questions: what data the agent may see, which actions it may take, what it may spend, what the audit trail contains, and who owns the kill switch. Human-in-the-loop (HITL) is the default on irreversible or high-cost steps — not an optional extra after go-live. Longer write-up: enterprise AI agent risk checklist.

Data

Name the systems, fields, and tenants the agent may read. Retrieval stays inside that boundary. Consumer plugins and unsanctioned paste-into-chat are out of scope until a control owner says otherwise.

Actions

The allowed-tool list is the product. Draft and classify by default; writes, refunds, access changes, and anything irreversible wait for a person. The agent cannot invent a new integration at runtime.

Spend

Model calls, retries, and tool loops need an envelope and a named owner. Unbounded tokens are a FinOps incident, not an AI feature. Pair this page with FinOps consulting when the bill is the constraint.

Audit & ownership

Every tool call, input, output, and stop reason is written down. A named human can pause the agent and change the tool list without taking the rest of the stack down. If you cannot name that person, you do not have an agent — you have shadow IT.

Regulated patterns — not fake certs

We use process language you can show to a control owner: least privilege, HITL, step logs, and a kill switch. That is not a SOC 2, HIPAA, or ISO badge on this page. Payments and banking-adjacent stacks start on industry solutions. Clinical or PHI work starts on healthcare IT. Your counsel and auditor decide what is “enough.”

Sequence before you scale

  1. Discovery ($99) — one process, data boundary, and whether an agent is even in scope.
  2. Consulting ($499) — ROI order, HITL gates, and build / wait / do-not-build.
  3. Starter ($2,500) — first production agent for that process, with the five-point checklist live.
  4. Growth ($8,000/mo) — change control, spend envelope, written SLA. More agents after the first one is governed.

Map data, actions, spend, and ownership before you fund the build.

Map your first agent — Discovery $99 Contact

AI automation for MSPs

MSPs do not have a chatbot problem. They have a queue problem: repetitive intake, missing fields, and after-hours noise that still needs a human on anything irreversible. Ticket load drops when intake is classified, enriched, and routed — not when an unsupervised agent closes work. Longer write-up: enterprise AI agent risk checklist. The operating layer those tickets sit on is managed IT.

Where agents help

Intake, classify and route, draft (don’t send), and after-hours capture. If you cannot point to a queue, a system of record, and a person who owns exceptions, you have a chatbot — keep it that way until the workflow is written.

Triage that stops

Password, device, and access requests: gather identity, complete the form, stop before changing production access. Alert noise: group duplicates, attach the payload, leave priority to a tech when the pattern is new. We will not invent a percentage of tickets “deflected.”

Multi-tenant isolation

Per-tenant tools, no shared prompt memory across customers, least privilege (read and draft by default), a step log, and a kill switch that does not take down the PSA or RMM. Isolation is a design rule, not a slogan.

Cost model

Usage (model calls) and the managed layer (design, tenant-safe integration, exception queue) are two bills. Map one agent in Discovery $99 before you buy a platform. We do not quote a fake “tickets reduced” figure.

AI helpdesk / IT support automation

Helpdesk automation is triage, enrich, and route — not an unsupervised closer. The agent reads the ticket, completes missing fields, attaches context, and stops or escalates when policy or confidence says so. A human remains the gate on access changes, production remediations, and anything irreversible. Longer write-up: RPA vs autonomous AI agents.

Triage

Classify request vs incident, severity, and queue. Password, device, and access intake: gather identity, complete the form, stop before changing production access. We will not invent a percentage of tickets “deflected.”

Enrich

Pull the user, asset, and recent changes from the system of record you already run. Attach the monitor payload or the knowledge citation. If the SOP is missing or conflicts, escalate — do not invent a fix.

Route & draft

Send the ticket to the right queue and draft an internal note or reply a technician can check. After-hours capture gathers context and pages a human when the severity rule says so. Closing customer-facing work without a stop rule is how you create incidents.

Enterprise vs MSP

Internal IT support uses the same gates: allowed tools, HITL, audit log, kill switch. Multi-tenant MSP queues add isolation — no shared prompt memory across customers. The operating layer those tickets sit on is managed IT. MSP-specific patterns stay in the section above and in enterprise AI agent risk checklist.

Map one queue before you buy a helpdesk bot.

Map your first agent — Discovery $99 Contact

Install, configure, maintain — official path

Discovery maps the first workflow. When that workflow is named, install, configure, and maintain sit on the public ladder — Discovery $99, Consulting $499, Starter $2,500, Growth $8,000/mo. Checkout lives on /plans/. There is no separate Governance or packaged-install SKU on this page.

Discovery $99

Map one process: tools, HITL, runbook, kill switch. Start here when the workflow is still unnamed.

Discovery hub →

Consulting $499 · Starter $2,500

ROI order, allowlist, envelope, audit log. First production agent for that process — five-point checklist live.

Official plans →

Growth $8,000/mo

Change control, spend envelope, written SLA. More agents after the first one is governed. Consulte when scope is multi-tenant or regulated.

Consulte →

Use the public ladder. Pay or Consulte on Plans.

Discovery $99 Consulte Plans

Path from Discovery to Growth

StepPriceWhat you get
Discovery$99One process mapped, ROI sketch, data/action/spend boundary, 30-min readout
Consulting$499Roadmap, ROI order, HITL gates, build / wait / do-not-build
Starter$2,500First production agent for that process — five-point checklist live
Growth$8,000/moManaged agents, change control, spend envelope, written SLA

Discovery $99 Consulting $499 Starter $2,500 Growth $8,000/mo Response within 24h

FAQ

How are agents different from chatbots?

A chatbot answers. An agent is allowed to use a short list of tools to finish a workflow — then stop or escalate. If the job is only FAQ, you do not need an agent. We will say so in Discovery.

Where do agents run on Growth?

On Growth we operate the agents in your environment (or a Zion-managed loop you approve): monitoring, change control, and a written SLA. Hosting is part of the retainer conversation — not a surprise SKU.

How do you control GenAI spend?

We set a spend envelope, log model and tool calls, and treat retries as a cost event. For cloud and model invoices, pair this page with FinOps consulting.

What does Discovery include?

One process, an ROI sketch (order of magnitude — not a guarantee), an executive report, and a 30-minute session. Details live on /discovery/.

How fast do you respond?

We respond within 24 hours to Discovery and consulting requests sent via /contact/ or kleber@ziontechgroup.com.

Do we have to start with a platform rollout?

No. Start with one process. If Discovery shows the process is a bad first agent, we will recommend consulting, a smaller automation, or waiting.

Can you automate an MSP helpdesk?

We map one queue first: classify, enrich, draft, and route — with tenant isolation and a human gate on production access. Closing customer-facing tickets without a stop rule is how you create incidents. See enterprise AI agent risk checklist and AI helpdesk / IT support automation.

What is enterprise AI agent governance?

A written answer to data, actions, spend, audit, and ownership — plus HITL on irreversible steps and a kill switch. The five-point checklist above is the production minimum. The CIO/CISO expansion is Enterprise AI agent governance & risk. Longer write-up: enterprise AI agent risk checklist.

Are you SOC 2 or HIPAA certified for agent work?

No. This page does not claim SOC 2, HIPAA, ISO, or any other certification. We use process language: least privilege, HITL, step logs, kill switch. Regulated stacks start on industry solutions or healthcare IT. Your counsel and auditor decide what is enough.

Do you automate an internal IT helpdesk?

Yes — as triage, enrich, and route with a human gate, not as an unsupervised closer. Map one queue in Discovery $99. Detail: AI helpdesk / IT support automation and RPA vs autonomous AI agents.

Is there a separate URL for governance or helpdesk?

Governance and helpdesk deepen this same page — there is no /ai-agent-governance/ or /ai-helpdesk/ SKU. Install, configure, and maintain follow the official ladder on /plans/ — Discovery $99, Consulting $499, Starter $2,500, Growth $8,000/mo. Blogs remain the longer write-ups. Discovery → Consulting → Starter → Growth stays the path when the first process is unmapped.

How do FinOps and managed IT fit?

Spend envelopes and model/tool retries belong on FinOps consulting. The operating layer under the ticket queue is managed IT. Agents do not replace either.

Map your first agent before you buy a platform.

Map your first agent — Discovery $99 Or write Zion

See also: Discovery $99 · Plans · AI consulting services · FinOps consulting · Managed IT · Solutions · Healthcare · Enterprise governance · Helpdesk automation · Install, configure, maintain · Enterprise AI agent risk checklist · RPA vs autonomous AI agents · Controls before autonomy · First workflow