---
title: Enterprise AI Agents — plan, act, audit | Zentavor
description: Enterprise AI agents that plan, use tools and act across your business processes end-to-end, with governance and audit built in.
canonical: https://zentavor.com/solution-ai-agents.html
---

# Enterprise AI Agents — plan, act, audit | Zentavor

> Enterprise AI agents that plan, use tools and act across your business processes end-to-end, with governance and audit built in.

Solutions / AI Agents

AI agents that run the work, not just answer it

Autonomous systems that plan actions, call your tools, analyze data and make decisions across complex business processes, well beyond chatbots and RPA scripts
Plans & actsTool & API callsHuman-in-the-loopAudited & governed
9:41
Agent Operationsautonomous workflowsOn-premise
Enterprise support · in production
0%
Running
planning the next step…
run #48213 · autonomous
“Paid yesterday, where's my order?”
Recent runs
autonomous agents12.4k runs / day
45%resolved without escalation
3×faster first response
−33%cost per ticket
What we do

## One request, resolved end to end

Watch a single ticket travel through the agent, each step explained as it happens
ticket #48213 · email
"Paid yesterday, where's my order?"
Autonomous agentperceives · plans · acts
verify paymentcheck fulfillmentreply + update
crm.lookup(order #48213)ops.check_fulfillment()draft_reply()
expedite > policy: waits for analyst approval approved
CRMupdatedERPorderTicketingclosed
resolved · 0 escalation · every step logged & approvable
Autonomy

### Decides the next step, not a script

From the goal and live context, the agent plans its own path. No brittle if-then flow to maintain.
Acts through your tools

### Reads and writes your real systems

API calls, database lookups, write-back to CRM, ERP and ticketing, not just an answer in a chat window.
Human in the loop

### Sensitive actions wait for approval

Anything past a policy threshold pauses for a person: autonomy you can actually trust in production.
Audited & adaptive

### Every step logged, and it learns

Every action leaves a full, reviewable trail; outcomes feed back so the agent improves over time.
How we deliver

## From discovery to production, no black box

Discovery & strategy

Map processes and KPIs, agree the ROI hypothesis before a line of code.

Architecture design

Agent roles, orchestration logic, data flows and security boundaries.

Implementation

LLM integration, tool calling, write-back to your systems, rigorous testing.

Production & optimization

Deploy with monitoring, feedback loops, audit trail and continuous improvement.
Where agents work

## One pattern, every department

The same loop (perceive, plan, act, learn) plugged into each team. Pick one to see where it lands
The challenge

## Why most automation stalls

Today

Work waits in human queues, 9-to-5.
Decisions stall when data lives in disconnected systems.
Each tool is automated in isolation, no end-to-end flow.
Chatbots and RPA break the moment a process needs judgement.

With Zentavor

Agents resolve end-to-end, 24/7.
They read and write across CRM, ERP and ticketing.
One orchestrator spans your whole stack.
They handle judgement, with a human gate where it matters.
Proof

## Agents already running in production

Not demos: agents that resolve tickets, triage incidents and write back to core systems today
Support automationAI Agents
−33%
cost per ticket
Knowledge-grounded ticket triage: 45% resolved without escalation, 3× faster first response.
In productionNDA
ETL incident triageAI Agents
85%
root-cause auto-classified
Incident copilot: 3× faster diagnostics and −60% manual incidents across data pipelines.
In productionNDA
Trader copilotAI Agents
200+
active traders served
GenAI assistant over incident and near-miss corpora on a Fortune 500 trading floor.
In productionNDA
Selected case studies available under NDA. Contact us for examples in your industry.
FAQ

## Your frequently asked questions

**
How is this different from a chatbot or RPA?**

Chatbots answer questions; RPA follows fixed scripts. Agents plan, call tools and adapt to context, and they act across your systems, with guardrails, instead of just replying.

**
Can agents act in our core systems safely?**

Yes. Every action runs through scopes, approval flows and a full audit trail. Sensitive steps require human approval, and everything is logged for compliance.

**
How long until first production value?**

Typically weeks. We start with a discovery and an ROI hypothesis, ship a scoped agent into one process, then expand once it proves itself.

**
Do we have to send data to third parties?**

No. Agents can run inside your perimeter using on-prem or private-cloud models, so sensitive data never leaves your environment.
Let's talk

## Put AI agents into your workflows

Tell us the process you want to automate: we'll propose the agent design, integrations and a realistic delivery plan
Request a demo