Run it inside your MSP
Use Agent Aech for ticket triage, customer follow-up, documentation, QBR prep, renewals, and service coordination.
MSPs
MSP Software Factory
Agent Aech MSP helps managed service providers turn trusted customer relationships into a practical AI services line. Use it inside your own operations, then host Agent Aech and build agents for customer workflows.
Distribution Strategy
MSPs are the natural AI delivery channel for SMBs.
Customers already trust their MSP to understand systems, security, users, and operational context. Agent Aech gives MSPs a way to turn that trust into hosted AI workflows, recurring service revenue, and deeper customer engagements.
Host it for customers
Operate Agent Aech as part of your managed service, with customer-specific agents, scoped tools, review gates, and runtime visibility.
Build repeatable services
Turn the agent builder into a repeatable delivery motion instead of custom one-off AI projects for every account.
Own Operations First
Prove the value in the MSP before selling it outward.
Agent Aech can help an MSP reduce coordination load across the work it already runs every day. That internal proof becomes the operating story customers can understand.
- Triage service requests and prepare next-step summaries.
- Draft customer updates, escalation notes, and handoff packages.
- Prepare QBR inputs from tickets, meetings, documents, and account context.
- Track procurement, renewals, onboarding, and policy exceptions.
- Keep human approval for customer-facing commitments and sensitive changes.
- Leave a reviewable audit trail for work that moved or stalled.
Customer AI Services
Build customer AI solutions without starting from scratch every time.
Agent Aech is the hosted agent layer. The MSP brings the customer relationship, systems knowledge, service discipline, and ongoing operating model.
AI workflow discovery
Use your customer trust and operational knowledge to identify workflows worth automating.
Agent build and deployment
Build customer-specific agents with the right prompts, tools, identity, permissions, and review gates.
Hosted runtime operations
Provide the operating layer: monitoring, spend visibility, updates, exception handling, and improvement cycles.
Recurring managed AI service
Package agent operation, tuning, reporting, and new workflow delivery as recurring services.
MSP Economics
A better reason to call every customer.
New customers
Lead with practical AI workflow outcomes instead of another infrastructure offer.
More revenue per customer
Add agent builds, hosting, operations, and improvement cycles to existing managed service accounts.
Deeper service
Move closer to customer operations by helping actual work run, not only keeping systems online.
Stickier relationships
Customer-specific agents, review patterns, and operational reporting become part of the service relationship.
Factory Model
A repeatable motion for customer workflow agents.
The point is not a one-off AI build. The point is a repeatable MSP service motion: find the workflow, build the agent, host it, monitor it, and expand when it works.
- 1
Find the workflow
Start from customer work you already understand: service, finance, sales, operations, document, or approval processes.
- 2
Scope the agent
Define what the agent can read, which tools it can use, where humans review, and how success will be measured.
- 3
Build with the agent builder
Create the prompts, capabilities, runtime settings, identity, and handoff behavior for the customer workflow.
- 4
Run and monitor
Track sessions, cost, tokens, approvals, tool activity, outcomes, errors, and improvement opportunities.
- 5
Package and expand
Turn proven patterns into repeatable service packages and expand into the next workflow or customer segment.
Operating Controls
The MSP needs a real operating surface, not a demo bot.
Agent Aech is built around the controls customers and providers need to run agents in production workflows.
Customer-specific agents and permissions.
Microsoft 365 and business-system capability scoping.
Human review for external actions and important decisions.
Spend, token, cache, session, and runtime visibility.
Audit trails for source context, tool activity, approvers, and outcomes.
Private, on-prem, or dedicated hardware paths when the customer needs them.
Next Step
Build the first MSP AI service package.
Bring one internal MSP workflow or one customer workflow that is painful, repeated, and valuable enough to operate as a service.