Senior engineering capacity
Add architects, AI engineers, software developers and DevOps specialists without building a new bench.
European teams help US partners deliver enterprise AI and software from architecture to production.
When a complex AI or software engagement needs more senior capacity, EnterIT joins as the accountable European engineering arm behind your client promise.
Add architects, AI engineers, software developers and DevOps specialists without building a new bench.
Start with a focused workstream and expand the team as scope, integrations and production responsibility grow.
Deliver across Azure, Microsoft Fabric, Power Platform, Microsoft 365, Business Central and the .NET ecosystem.
Move from a prototype to governed agents, data flows, human approvals, monitoring and measurable outcomes.
Architecture, security, integration, release management and production operations stay under one accountable team.
We can support one project, a portfolio of workstreams or continued delivery after the first production release.
The operating model is agreed before kickoff, so communication, ownership and security are never left to interpretation.
You retain commercial ownership and the client relationship. We define technical ownership, escalation paths and delivery responsibilities together.
One backlog, regular planning, visible progress and working demos. Delivery leads report against outcomes, risks and next decisions.
Least-privilege access, separated environments, audit trails and project-specific controls are part of architecture, not a final checklist.
Mutual NDA, confidentiality, intellectual property and handover expectations are agreed before engineers access client systems.
We agree practical overlap with the client team, then protect focused engineering time while keeping decisions and escalations responsive.
Monitoring, incident response, SLA, documentation and continued development can remain with the same team that built the solution.
We choose the stack around the enterprise environment, delivery risk and production requirements, not around a fixed product catalogue.
Selected engagements are anonymized. Each one starts with a business constraint and ends with a production outcome.
Low AI adoption and manual information lookup around Business Central.
A production AI layer over Business Central made trusted company data available in daily work.
Adoption grew from 17% to 78%, saving approximately 40 minutes per user every week.
Repetitive operational processes consumed thousands of team hours every year.
Copilot and n8n took over selected routine steps and routed exceptions to people.
A 3-month payback and approximately 1,420 team hours returned every year.
Manual retyping and fragmented data made project oversight difficult.
An internal application with APIs and Power BI unified data work and reporting.
Approximately 180 team hours returned every month and one shared project view.
A 75-person European team across enterprise software, AI engineering and product delivery. English-speaking leads stay accountable from kickoff to production.
Has advised 120+ companies and trained 800+ people. Owns strategy, product direction and partner alignment.
Nearly 20 years in C-level roles. Leads client delivery, operations and production ownership.
AI architecture, engineering quality and production deployment.
In 30 minutes, we will align on scope, engineering capacity, ownership and the right next step for your client engagement.