BUILD Intelligent Automation
AI agents that make operational decisions using data from every system
Boomi AgentStep · Agent Control Tower · Breeze AI (CRM-native decisions)
Boomi AgentStep · Agent Control Tower · Breeze AI (CRM-native decisions)
THE CHALLENGE
Operational decisions wait for people. People wait for data.
Many operational decisions need information from several systems. Credit approval calls for CRM and ERP data. Order routing calls for inventory and order history. Churn risk detection calls for transactional and behavioral data. Today these decisions are manual, slow, and inconsistent.
- Credit approval runs on emails, phone calls, and Excel files passed between departments
- Churn surfaces only after the customer has already left
- Lead scoring relies on static rules set years ago
- Every decision depends on one specific person's availability
WHAT WE DO
AI agents that decide. With human oversight. On real data.
We design AI agents that make operational decisions by accessing the golden record and every connected system. Each agent starts under full human oversight (human-in-the-loop): your team validates the decisions, builds trust, and measures reliability.
Autonomy only expands once the KPIs are met. Centralized governance and continuous monitoring. No agent ever operates without oversight.
GOVERNANCE INCLUDED
AI governance framework: per-agent human-in-the-loop configuration, kill switch, decision audit trail, bias monitoring, oversight dashboard. AI Act compliance preparation included.
Service Details
Intelligent Automation
| Phase | Build |
| Deliverable | 2–4 operational AI agents with HITL active, oversight dashboard, escalation playbook, KPIs for expanding autonomy |
| Platforms | Boomi AgentStep Agent Control Tower Breeze AI |
| Prerequisite | Unified Customer View operational |
| Duration | 4–10 weeks per cycle (2–4 use cases) |
| Continues with | Ongoing Integrations Management, Evolution Sprint |
| HITL Path: | → Month 1–2: full oversight → Month 3–4: selective oversight → Month 5+: controlled autonomy |
HOW IT WORKS
From use case to autonomous agent. Four phases.
1
Use case selection
We identify 2–4 high-impact operational decisions: credit approvals, order routing, churn alerts, lead scoring. The ones where AI creates the most value.
2
Design and connection
We design each agent: what data it uses, what rules it applies, what thresholds trigger human escalation. We connect it to the golden record and source systems.
3
Launch under full oversight
Each agent starts in HITL mode: your team validates 100% of decisions. The agent learns, your team builds trust.
4
Autonomy expansion
Once the reliability KPIs are met, autonomy expands step by step. Monitoring never stops.
EXPECTED RESULTS
What your organization gets.
Decisions in minutes, not days
Approvals, routing, alerts: all in real time. Your team focuses on the exceptions.
Consistency
The same rules, every time. No variability tied to the person or the moment.
Scalability with no team ceiling
Agents handle growing volumes without adding headcount.
Trust earned, not declared
Your team has seen the agents work under oversight. Autonomy is earned, not announced.
FREQUENTLY ASKED QUESTIONS
Everything you need to know.
What happens if an agent makes a mistake?
During the HITL phase, every decision is validated by your team before it runs. The escalation playbook defines what happens in each scenario. The kill switch stops the agent instantly when needed.
Do we need the golden record to start?
Yes. Agents make better decisions when they have access to unified data from every system. The value comes from the combination of golden record and AI.
How long does it take to reach autonomy?
The typical path: 1–2 months of full oversight, 3–4 months of selective oversight, then controlled autonomy. Timing depends on decision complexity and volume.
How is reliability measured?
Specific KPIs for each agent: accuracy, response time, escalation rate, business impact. The oversight dashboard shows everything in real time.
Is it compatible with the EU AI Act?
Yes. The governance framework is designed for AI Act compliance: transparency, human oversight, audit trail, bias monitoring. Preparation is included in the project.
THE NEXT STEP
After the first agents.
The first agents are live. Here is how to expand.Evolution Sprint
New agents for new use cases. Each sprint adds capability in weeks.
Ongoing Integrations Management
Agents evolve: performance monitoring, rule updates, autonomy expansion.
SAP Connect
If SAP data is not yet connected, agents work better with more sources.
Operational decisions can be faster, more consistent, more scalable.
Intelligent Automation makes it possible. With oversight, not with promises. Let's talk about your context.
Connected data. Autonomous decisions. Customers at the center.