Dynamics 365 AMS without an SI — your in-house team steers, AI executes
You want to exit the SI model without recruiting a full in-house X++ team. No intermediate solution until now.
Dynamics 365 F&O application maintenance without an SI: 1 in-house FTE + Skalp AI = full autonomy. €120-140k/year total vs €150-300k classic AMS.
Pure D365 internalization stays out of reach for most CIOs
- ✗A senior D365 architect costs €110-180k loaded annually if hired in-house (or €1,500-2,000/day if you go through an SI) — for one person, on a single D365 domain.
- ✗Expertise depth (Finance + SCM + Production + HR) requires several FTEs: one cannot cover everything.
- ✗Senior X++ profile turnover is high: your training investment may evaporate in 18 months.
- ✗Service continuity during a single senior's leave / absence is risky.
A lean in-house team (1-2 FTEs) that steers, and Skalp AI that produces
- ✓Your in-house D365 architect or lead submits tickets, validates Pull Requests, applies your standards.
- ✓Skalp AI handles X++ production: extensions, classes, workflows, reports — no dependency on a single senior.
- ✓Total cost controlled: 1 in-house FTE (~€90k/year loaded) + €30-50k/year Skalp AI = full autonomy at €120-140k/year.
- ✓You capitalize code and documentation in your repo — your in-house team builds skill on every review.
How it works
Submit your ticket
Describe the business or technical need in a few lines. No 50-page spec required.
AI generates the extension
X++ code, unit tests and documentation produced in under 48 hours.
Validation on your Azure DevOps
Pull request submitted on your repository. Your IT lead reviews and validates before merge.
Delivered — you pay €200
Once merged, it's delivered. No billing if the ticket isn't resolved.
The process applied to this case
- 01
Azure DevOps setup if not yet in place
Azure DevOps project provisioning, Git repo setup, branch policies, first CI build and LCS release pipelines. Skalp AI delivers pipelines per ticket if needed.
- 02
Identification of the in-house lead profile
1 FTE on the IT side is enough to steer the flow: a D365 architect or experienced D365 developer who can read and validate X++. No need to write code, just review and approve.
- 03
First tickets on non-critical matters
Start with 10-20 tickets on low-risk matters (table extensions, reports, UI customizations). This lets your in-house team calibrate its validation pace.
- 04
Progressive ramp-up
Once cadence is established, ramp up to 20-40 tickets/month. Your in-house team steers prioritization with business users; Skalp AI absorbs peaks.
- 05
Full D365 autonomy
At 6-12 months, you have exited your historical AMS. Your in-house team masters the functional scope, Skalp AI produces the code, and all history is in YOUR Azure DevOps.
Frequently asked questions
What in-house profile should we recruit?+
What volume can a single in-house person steer?+
What if my in-house person leaves?+
Related pages
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