
Built into the systems you already run.
AI Implementation is how we build AI into your business. Our engineers work inside your environment, alongside your team, and connect to the systems you run. Nothing is ripped out.
What you havewhen we are done.
Not a report and not a pilot. Working AI, inside the systems you already run, with the controls and the numbers to go with it.

A plan tied to the work
A practical implementation plan, tied to the work that matters first.

A managed AI environment
Access, approvals and reporting in place from the start.

Working agents and automations
Connected to the systems your team already uses, and tested on real work.

Results every month
Usage, time saved, issues and the next priorities.
What we build,and what it sits on.
Built for you
Integrations, workflows, screens, compliance
PRESHos
Permissions, digital twin, approvals, record
Connections
Connectors, connector SDK, plugins
Your systems
CRM, PSA, ITSM, project tools, email, files
Built for you
Integrations, workflows, screens, compliance
PRESHos
Permissions, digital twin, approvals, record
Connections
Connectors, connector SDK, plugins
Your systems
CRM, PSA, ITSM, project tools, email, files

Forward deployed
Our engineers work inside your environment, alongside your team.
Your stack stays
We connect to the systems you run. Nothing is ripped out.
Auditable
Compliance requirements are part of the build, so they can be audited.
What is insidean engagement.

Strategy and roadmap
We sit with your team, document how the work happens today and choose the first processes worth changing.

Integration
We link agents to your CRM, PSA, ITSM, project tools, email and files.

Deployment
We build it in your tools. Your team tries it on real work and approves live actions.

Forward deployed engineering
Engineers who work inside your environment, alongside your team, and own the build end to end.

Custom builds
Integrations, workflows and screens built for the way your business runs.

Training and adoption
We help people use it, watch what happens and adjust what underperforms.
From the first conversationto a capability you own.

Map
Show us the work. Agree one workflow, one owner, one measure.
You get a sequenced roadmap.

Connect
Link agents to the systems and data that run the business.
You get integrations that survive the pilot.

Deploy
Build it in your tools. Your team tries it on real work.
You get production-grade workflows.

Operate
Watch, report and keep improving as the business changes.
You get a capability your team relies on.

Transfer
Train your team and hand over what you want to own.
You get a team that can extend it.
The decisionsstay with you.
We do the work. In every phase there is one decision that is yours to make, and nothing moves on until you have made it.
- The first workflow, its owner and its measure
- What each agent may read and change
- When a workflow goes live
- What to extend next
- How much you run yourselves
Where teamsusually start.
A good first workflow has several steps, crosses more than one system and has a point where a person should approve. People keep the commercial and client-facing decisions.
- Ticket intake, classification, enrichment and routing
- Client updates drafted for a technician to approve
- Quarterly review preparation from PSA, ticket and project data
- New client onboarding tasks and evidence collection
- Security alert summaries and remediation plan drafts
- Discovery notes turned into a scope summary
- Quote packages assembled from CRM, vendor inputs and templates
- Proposals drafted for the rep and engineering to approve
- Vendor coordination and follow-up tracking
- The handoff from sales to implementation
Named beforework starts.
Every engagement names five things up front. There are no open-ended hourly retainers.

The workflow
One piece of work, described the way your team does it today.

The system of record
Where the data lives and stays. Agents work to it.

The measure
The operating number the workflow is meant to move.

The governance
What each agent may read and change, and what needs a person's approval.

The handoff
How much your team will run itself, named on day one, not at the end.

Our engineers workinside your environment.
Forward deployed engineers build alongside your team, in your tools and under your access rules. They surface blockers and integration risks early, and they stay until your people can run what was built.
Who doesthe work.
One team carries the work from identifying the opportunity through process design, implementation, team adoption and ongoing operation.

Business specialists
People who know how channel businesses run. They map the work with your team and speak for the people who will use it.

Solution architects
They design how agents, systems and approvals fit together, and what can be audited.

Forward deployed engineers
They build the integrations and agents inside your environment, lead working sessions with your team and train the people who take it over.
Built forthe IT channel.

MSPs and MSSPs
Customer experience, service operations and support.

Solution providers
Quoting, solution design and back-office automation.

Distributors
Agents and integrations that simplify channel commerce.

Manufacturers
Partner AI adoption using vendor agents, APIs and MCP tools.
Once it is running,we can keep it improving.
We manage your AI implementation and keep improving how your team puts it to work.
Relatedreading.
More on AI Implementation
AI Engineering
Connecting AI Agents to a PSA Without Replacing It
How to connect AI agents to your PSA while it stays the system of record: what syncs, what agents may read and change, and where a person approves the work.

AI & Automation
What Forward Deployed Engineering Looks Like Inside an MSP
What a forward deployed engineer does inside an MSP: where they work, what they build, what your team provides and how the build ends up in your hands.

AI & Automation
Handing an AI Workflow to Your Own Team
How to hand an AI workflow to your own team: what a handover contains, who should take it over, how to train them and how much you need to run yourselves.

Show us the work.
We start with one workflow, one owner and one measure. Tell us where AI is stalling and we will talk through what is practical to build.