PRESHai stands up the strategy, the platform, the integrations, the controls, and the team ownership that put AI to work inside your channel business.
WHAT WE DO
PRESHai is the team that takes AI from idea to a system your business actually runs on. We design the strategy, stand up the platform on PRESHos, integrate it with the systems you already operate, build the governance that lets it run in production, and train the people who own it after we leave.
By the time we are done, AI is not a deck or a pilot. It is part of how your channel business works, with named owners, audited controls, and a roadmap leadership can defend.
WHAT TO EXPECT
These are the phases of our AI implementation process. Each phase produces a defined deliverable, sets up the next phase, and contributes to the operational system you exit with. Skim here. Read deeper below.
01
Channel ontology, workflow inventory, phase-one scope.
02
PRESHos tenant configured, agent factory templates ready.
03
Connectors specced, invoker-on-log audit, MCP plus deterministic patterns.
04
Approval routing, evaluation rubrics, escalation runbooks.
05
Champions trained, role curricula delivered, ownership transferred.
Every AI implementation that survives in production starts with a strategy phase that maps the business, not the model. We inventory the workflows that touch revenue or risk, score them by AI fit and impact, and translate that into a sequenced phase-one scope leadership can fund.
The deliverable from strategy is not a deck. It is a channel ontology that defines how the business actually works in entities and relationships, so every later stage builds on the same map. Without the ontology, agents end up answering questions the business does not ask in language the business does not use.
PRESHos is the platform agents run on. It is the substrate every later stage builds on. Where a generic AI consultancy hands you a stack of vendors and walks away, PRESHai stands up your tenant of PRESHos and configures the agent factory, runtime, observability, and integration layer to your business.
Inside the platform, agents are built (factory), orchestrated against your workflows (runtime), evaluated against business outcomes (observability), and connected to your operating systems (integration). One platform, one evaluation harness, one observability layer. The eleventh agent costs less than the second.
Agents are only as useful as the data and tools they can reach. The integrations stage connects the stack you already operate, PSA, RMM, CRM, ITSM, SIEM, ticketing, and the system of record, so agents read context, reason, and act through governed paths.
Every connector is scoped before it lights up. Read versus write paths reviewed, the human invoker recorded on every agent action inside PRESHos, and the actor identity that hits the upstream system inheriting the invoker's permissions. If the human cannot create a deal in ConnectWise, the agent cannot either. Org data mirrored into a digital twin where the agent runs at full speed, with the HITL gate initiating any create, update, or delete against the real system.
Production agents need approval routing per risk class, evaluation rubrics tied to business outcomes, audit logs that survive a CFO question, and escalation paths the CIO can defend. Governance is the discipline that prevents agents from doing things to your business no one signed off on.
ROUTING
Low-risk decisions auto-execute. Higher-risk decisions route to the right human with the context they need to decide. Defined per workflow before launch, not retrofitted after the first incident.
EVALUATION
Every governed workflow gets an evaluation rubric written in business language, not model-quality jargon. We measure agents against the operational outcome they should produce, not against vibes.
AUDIT
Every agent action logged to your existing IT and compliance tooling. Replayable. Decision rationale captured. The auditor's first question has an answer before they ask it.
ESCALATION
When agents disagree with a human or hit edge cases, escalation paths route to the right team with context. Rollback procedures defined, tested, and on file before the agent touches a customer.
AI implementation does not stick because the platform is good. It sticks because the team using it is ready to own it. The enablement stage runs alongside the back half of build so that by launch, internal champions are identified, workflows are redesigned around agents, and the curriculum that keeps the team current is in place.
Training is role-based and hands-on. Engineering learns the agent build patterns. Operations learns the evaluation and rollout cadence. Practice leads learn workflow ownership. IT and legal learn the governance operations. The team you train is the team that runs the system after the engagement closes.
When the implementation engagement closes, your team owns a working AI operation. From there, many clients retain PRESHai to keep the platform, the controls, and the agent roadmap current as the AI landscape moves, brief leadership on what should ship next, and run the operational disciplines so the system gets sharper, not stale.
We manage the PRESHos tenant, run the controls, keep building and optimizing agents, and brief your execs on the recommendations and changes the platform should ship next.
INSIGHTS
How AI and automation are reshaping operations, workflows, and growth strategies across the IT channel.
Tell us where AI is stalling. We will tell you which stage to start with.
