AI & Automation
Workflow automation and AI systems that survive production: versioned flows, eval gates, audit logs, and runbooks your own team operates.
An 18-control diagnostic for Microsoft 365-heavy teams: readiness verdict, risk register, first safe use case and a 90-day plan.
What this covers
Workflow engineering on n8n, Power Automate, Make and Zapier, private RAG on your own documents, and AI integrations with evals and audit logs. Copilot readiness included.
Who it is for
Teams automating repetitive work or piloting AI who need it to hold up in production and in front of a board, not only in a demo.
Where to start
Start free with the AI readiness scan, or book the €499 Architecture Workshop: a 2-hour live session and a written deliverable in 5 days.
How it ends
Every engagement closes with an Exit Kit: flow definitions in your source control, prompt and eval library in your repo, runbooks in your hands.
Automation and AI fail the same way: quietly. A flow breaks and nobody notices until a customer does. A model demos well and falls apart on real data.
Automations that broke months ago and nobody noticed until a customer complained. No monitoring, no owner, no alert.
Every flow instrumented with an SLO and a named owner; broken flows get same-day triage on the operate tier.
Monitoring dashboard with an SLO per flow
Flows built ad hoc in Power Automate, Make or Zapier by citizen developers that nobody can audit, transfer or recover.
Flow definitions exported, versioned and reviewed like the rest of your code.
Versioned flow definitions in your source control
AI pilots that look impressive in a demo and fall apart on real data, with no way to measure whether the next change makes them better or worse.
An evaluation harness with a golden dataset gates every change before it reaches users.
Prompt and eval library committed to your repo
Solution narratives
2 narratives: full pitch with deliverables, scope and case context
Services in this pillar
2 discrete engagements: fixed scope, written deliverables
Service desk AI
Tier-1 access requests moved out of the engineer queue.
Jira Service Management, n8n, Slack approval, and internal APIs turned repeat access tickets into a controlled self-service path.
Anonymised outcomes from the founder's prior operating roles in regulated industry, stated as such, not ITSailor client engagements.
On the record- 45% lower L1 ticket volume
- 14 hours to 12 seconds MTTR for simple access requests
Four steps, one destination.
The same sequence on every engagement. It starts read-only and it ends with the Exit Kit in your hands, so the exit is designed before the work begins.
- AuditRead-only discovery in your tenant. Findings arrive in writing, with sources.
- DecideThe €499 Architecture Workshop: a 2-hour live session and a written deliverable in 5 days. You own the plan.
- BuildFixed scope, agreed change windows, evidence recorded as the work lands.
- Hand overExit Kit within 24 hours. Runbooks, source, credentials inventory, architecture record.
How is this different from a one-off automation project?
We instrument every flow, version it, and assign a named owner. The optional operate tier keeps them alive with same-day triage on broken flows, so a failure surfaces in hours instead of months later through a customer complaint.
n8n self-hosted or cloud?
Self-hosted by default, for sovereignty and cost. n8n Cloud only when the operational overhead of self-hosting is not justified by the use case. We run n8n in production ourselves, so we know where the trade-offs are.
Which AI provider do you prefer?
The one that matches your constraints. We benchmark before committing and design for portability, so switching providers is a configuration change rather than a rebuild.
Is our data ready for Copilot?
That is the first thing to verify, because Copilot inherits your permission model. An oversharing and data-hygiene review runs before any licence order, so the rollout does not become an incident report.
Do you cover Power Platform governance?
Yes. Center of Excellence baseline, environment strategy, DLP policies and ALM patterns are included when Power Platform is in scope, deployed from the Microsoft CoE Starter Kit with a documented baseline checklist.
Who maintains the automations after handover?
Your team, by design. The Exit Kit contains the flow source, the runbooks and the monitoring setup. If you want ITSailor to operate them, that is a separate, cancellable retainer.