AI Agents Built for MSP Operations

Custom AI systems designed around your workflows, your ticketing structure, and your escalation logic.

WHAT ARE AI AGENTS

AI Agents That Do the Work.
Not Just Suggest It.

AI agents are purpose-built systems designed to handle specific operational tasks inside your MSP. They sit inside your PSA, your communication tools, and your service desk workflows. They read tickets, route calls, flag problems, follow up on SLAs, update clients, and handle dispatch. They do this continuously, consistently, and without the variability that comes with manual processes.

Our AI agents are custom-built systems designed around how your MSP actually operates. Your ticketing structure. Your escalation logic. Your client communication standards. Your SLA requirements. Every agent is scoped, designed, and implemented for a specific workflow inside your specific environment.

AI agents don't replace your team. They handle the repetitive, high-volume, pattern-based work that eats up engineering time and introduces inconsistency. Your team stays focused on the complex problem-solving and client relationships that actually require human judgment.

CORE CAPABILITIES

Six Core Capabilities Inside MSP Operations

Every AI agent we build falls into one or more of these operational categories. Each one targets a specific workflow where manual processes create bottlenecks, inconsistency, or wasted time.
01 Ticket Triage
02 Intelligent Routing
03 Sentiment Analysis
04 SLA-Based Follow-Ups
05 Automated Ticket Updates
06 Dispatch Automation
agent.itbd / runtime
LIVE

FEATURED AGENTS

Purpose-Built Agent Ready to Deploy

We’ve built a library of 25+ purpose-built AI agents that solve the operational problems eating the most time inside MSPs. Some are flagship products you can deploy directly. Others are part of a broader catalog you can mix and match based on where you’d see the biggest lift.
26+ Agents
6 Categories
1 Native to Your PSA
01

Ticketing & Service Desk

07
01

Digital Dispatcher. AI reads new tickets and automatically categorizes, prioritizes, and routes them.

02

Digital Troubleshooting Assistant. Suggests troubleshooting steps using your KB and past tickets.

03

AI Ticket Categorization. Analyzes ticket details and assigns the correct category.

04

AI Ticket Sentiment Analysis. Detects frustration and escalates urgent tickets automatically.

05

AI Suggested Ticket Responses. Generates troubleshooting guidance for L1 technicians.

06

AI Skill-Based Ticket Assignment. Routes tickets to technicians based on expertise.

07

QA Agent. Reviews 100% of tickets for SLA compliance and documentation quality.

02

Finance & Revenue

04
01

Revenue Leakage Agent. Compares PSA data, agreements, and licensing to detect missed billing.

02

Client Profitability Analysis. Analyzes PSA financial data to surface margin issues.

03

Finance & Billing Automation. Detects discrepancies between PSA and billing systems.

04

License Optimization Automation. Identifies unused SaaS licenses across your client base.

03

Security & Compliance

05
01

Conditional Access Monitoring. Detects and summarizes security policy changes.

02

Compromised User Response. Disables compromised accounts and revokes sessions.

03

Security Alert Triage. Prioritizes SOC alerts by risk and context.

04

Cybersecurity Report Generation. Builds executive-ready security reports automatically.

05

Security Incident Intelligence. Detects patterns across incidents for proactive defense.

04

Client Reporting & Experience

03
01

QBR Intelligence Agent. Compiles service metrics and recommendations into client-ready decks.

02

Self-Service AI Portal. Lets clients run common automated workflows without opening a ticket.

03

Website Voice Agent. AI-powered voice chat for clients and prospects on your site.

05

Automation Development

06
01

Automated SOP Generation. Generates operational documentation automatically.

02

AI Workflow Troubleshooting. Analyzes logs and suggests fixes for broken automations.

03

Natural Language Automation Builder. Builds workflows from plain language prompts.

04

AI Jinja Copilot. Generates workflow scripting for complex automations.

05

AI Workflow Documentation. Documents automation workflows as they're built or changed.

06

Automation Recommendation Engine. Surfaces high-impact automation opportunities from ticket data.

06

Agentic Operations

01
01

Agentic AI Workflow Orchestration. AI agents trigger and coordinate workflows autonomously.

USE CASES

Where AI Agents Make the Biggest Difference

AI agents aren’t theoretical. They solve specific, measurable problems inside MSP operations. Here are the scenarios where agents produce the most immediate impact.

High-Volume Service Desks

High-Volume Service Desks Hundreds of tickets a day means engineers spend more time sorting than solving.

How agents solve it: Triage and intelligent routing handle intake automatically, every ticket arrives categorized, prioritized, and assigned. Nothing sits unattended.

Multi-Tier Client Environments

Different SLA tiers need different treatment, but manual processes treat everything the same until someone escalates.

How agents solve it: Routing agents factor in client tier and SLA requirements automatically. Proactive escalation before thresholds are breached.

Client Retention Risk

Dissatisfaction builds quietly across slow responses and missed updates before anyone notices.

How agents solve it: Sentiment analysis runs continuously across all client communication and flags tone shifts early. Service managers get the signal before the client makes the call.

Scaling Without Adding Headcount

More clients and more tickets without hiring at the same rate requires operational leverage.

How agents solve it: Triage, routing, dispatch, updates, and SLA follow-ups all handled by agents. Your team’s time goes to resolution, not overhead.

Sentiment analysis — live
Monitored
847
Flags
6
At risk
2
Resolved
4
Harbour Logistics
90 Positive
Acosta Medical
58 Warning
Stonebridge IT
35 At risk
Clearpath Networks
74 Neutral

HOW WE BUILD THEM

How are AI agents built for MSPs?

Every AI agent’s engagement follows a structured process. We don’t drop in a pre-built tool and hope it fits. We start with your operation, understand the workflow you want to improve, and build the agent specifically for how your environment works.

BUILD PIPELINE · LIVE
AUTO · CYCLING
P-01
01
Workflow Mapping
P-02
02
Agent Design
P-03
03
Build & Integration
P-04
04
Testing & Validation
P-05
05
Deployment & Monitoring
STEP · 01 OF 05 01 / 05
Workflow Mapping

We map how work actually flows today, where the manual steps are, where time gets wasted, and where inconsistency happens.

Discovery · 5–7 days

After deployment, AI Dedicated Engineers can be engaged for ongoing maintenance, optimization, and expansion. Professional Services builds the agent and gets it into production. Dedicated Engineers keep it running and growing over time.

WORKFLOW · MAPPING 6 NODES · 8 EDGES
INTAKE DISPATCH TRIAGE CLIENT ROUTE RESOLVE
MANUAL STEPS
23
WAIT TIME
4.7h
VARIANCE
±34%
AGENT · LOGIC 3/4 TRIGGERS · ARMED
TICKET·NEW SLA·THRES SENTIMENT TIME·PHASE AND ACTION ROUTE · L2 HUMAN · REVIEW
INTEGRATION · NATIVE 4 LIVE · 0 EXTERNAL
CONNECTWISE AUTOTASK HALOPSA NINJAONE AGENT CORE 0% · BUILT
VALIDATION · GATE 244 / 248 TESTS
98.4% PASSING
LIVE TEST FEED
EDGE CASES
47
FAILURES
4
GO · LIVE
READY
PRODUCTION · LIVE UPTIME 99.97%   ● LIVE
AGENT CORE OK
PSA · CONN OK
MONITORING OK
SLA WATCH OK
5-PHASE BUILD · GOVERNANCE EMBEDDED · NATIVE TO YOUR PSA
Step
1
Workflow Mapping
We map how work actually flows today, where the manual steps are, where time gets wasted, and where inconsistency happens.
Step
2
Agent Design
We design the agent logic: what it monitors, what triggers it, what actions it takes, and where human review is required. Governance rules are built in from the start.
Step
3
Build and Integration
Engineers build the agent inside your environment using your PSA, communication tools, and existing data. No separate platforms. No disconnected systems.
Step
4
Testing and Validation
The agent is tested against real scenarios from your environment. Edge cases, error handling, and output quality are all validated before anything goes live.
Step
5
Deployment and Monitoring
The agent goes into production with monitoring, documentation, and defined ownership. Performance is tracked against the outcomes defined during design.

After deployment, AI Dedicated Engineers can be engaged for ongoing maintenance, optimization, and expansion. Professional Services builds the agent and gets it into production. Dedicated Engineers keep it running and growing over time.

GOVERNANCE AND OVERSIGHT

AI With Boundaries, Not Just Capability

AI agents inside MSP operations touch client data, ticketing systems, and communication channels. Governance isn’t nice to have. It’s built into every agent from the design phase forward.
Every agent has a defined scope of autonomy: what it can do independently, what requires human review, and what it escalates automatically. These boundaries are documented, agreed upon before deployment, and enforced through the agent’s own logic.

Defined Autonomy Boundaries

Every agent has a clearly defined scope of what it handles independently and where it escalates to a human.

Human Oversight by Design

Your MSP retains responsibility for oversight of AI-generated outputs in client-facing environments. Human review stays where it matters most.

Documented Governance

Covers data handling, access automation, accountability, and human oversight requirements for every agent deployed.

Secure Delivery Environment

All AI engineering happens from ITBD-owned secure offices within SOC 2 Type II certified facilities.

BUSINESS IMPACT

What Changes When Agents Do the Work

AI agents are measured by what they change about your operation, not by how many you deploy. The value shows up in time recovered, SLAs protected, client experience improved, and capacity created without adding headcount.

40% Manual Workflows Automated

AI automation eliminates repetitive manual processes across dispatch, ticketing, routing, and back-office operations.

Measurable Cost Reduction

Lower dispatch costs, reduced engineering time on routine tasks, and more efficient resource utilization across your operation.

Faster Resolution and Response

AI-powered triage, routing, and automation accelerate time to resolution and reduce the number of touches per ticket.

Higher Margins at Scale

Automation that scales without adding headcount at the same rate. More clients, more tickets, and more revenue without proportional cost increases.

"IT By Design's AI team automated 40% of our manual workflows. Real AI impact."
- Sean Francis, CEO, Technology Assurance Group

PLATFORMS WE WORK WITH

Built Inside Your Existing Tools

AI agents are built to work inside the tools your MSP already runs. No separate platforms, no disconnected systems, no additional tools your team has to learn from scratch.

Agents integrate directly with your PSA for ticket data, your RMM for endpoint context, and your communication tools for client interaction. The integration is designed to feel native to your existing workflow, not bolted on.

ENTERPRISE TRUST

Trusted by Growth-Focused MSPs

40%
Manual Workflows automated

30%
Lower Dispatch Cost

50%
Faster Resolution

SOC 2
Type II Certified

900+
Engineers

Trusted by 400+
Growth-Stage MSPs

We've been doing a lot of AI services for the past three years. The experience brought structure and best practices.

Ahmad Mehmood
Founder & CEO
in

AI is evolving fast. It’s critical for peers to bring back ideas that actually work.

Bill McLaughlin
CEO
in

Everything we’ve done has been high quality, with the right people and content.

Habib Malik
CEO
in

AI innovation must be paired with strong governance and security.

Sarin Regmi
CTO
in

40% of our workflows automated. – That's real AI impact.

Sean Francis
CEO
in

The AI Accelerator sessions were practical and to the point. I left with a better framework for thinking about AI and a few things I can put to work right away.

Steven B. Plumlee
Certified CIO
in

Ready to Put AI Agents to Work Inside Your MSP?

Tell us which workflows are eating up the most time and we’ll show you where agents make the biggest impact.

FAQs

Common Questions About AI Agents

What's the difference between an AI agent and a chatbot?

A chatbot is a conversational interface that responds to questions. An AI agent is a system that takes action inside your operational workflow. It triages tickets, routes calls, monitors SLAs, generates updates, and handles dispatch. Agents do work. Chatbots answer questions.

Do AI agents work inside our existing PSA?

Yes. Agents are built and deployed inside your existing PSA, RMM, and communication tools. We support ConnectWise, HaloPSA, Autotask, and other platforms MSPs use. No separate systems required.

How long does it take to build and deploy an agent?

It depends on scope and complexity. A targeted agent for a single workflow like ticket triage can be designed, built, tested, and deployed in weeks. A broader agent ecosystem covering multiple workflows takes longer. Timeline expectations are established during scoping before any build work begins.

Can we start with one agent and add more later?

Yes. Most MSPs start with one or two agents targeting their biggest pain point and expand from there. The architecture is designed to scale, and each additional agent builds on the data and logic already in place.

Who is responsible for what the AI produces?

We design, build, implement, and maintain AI agents. Your MSP retains responsibility for oversight of AI-generated outputs in client-facing environments. Our governance framework defines where agents operate autonomously and where human review is required. Those boundaries are documented and agreed upon before deployment.

What happens if something goes wrong?

Every agent includes error handling, fallback logic, and escalation paths. If the agent encounters a scenario outside its defined scope, it escalates to a human rather than guessing. Monitoring is in place from day one so issues are caught and addressed quickly.

How do AI agents connect to the Digital Dispatcher?

The Digital Dispatcher is a production-ready AI agent product focused on dispatch: call handling, ticket creation, and initial routing. It uses the same underlying capabilities (triage, routing, sentiment analysis) applied specifically to the dispatch workflow. It can be deployed as a standalone product or as part of a broader agent ecosystem.

What is the QBR Creator?

The QBR Creator is a production-ready AI agent that connects to your PSA and RMM, pulls live operational data, and builds client-ready QBR presentation decks in Gamma automatically. It eliminates the manual data gathering and slide assembly that makes QBR prep one of the biggest time sinks in MSP operations.

What's the difference between AI Agents and AI Automation?

AI Agents are intelligent systems that handle specific operational tasks with decision-making capability, like triage, routing, and sentiment analysis. AI Automation focuses on eliminating repetitive manual processes like data entry, status updates, and reporting. Agents think and decide. Automation executes defined sequences. They work together inside the same AI Professional Services practice.

Who maintains the agents after deployment?

AI Professional Services builds and deploys. For ongoing maintenance, optimization, and expansion, AI Dedicated Engineers provide continuous engineering capacity. The handoff is clean and documented.

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