Make vs buy
Eazyware vs building an in-house AI team
Hire vs partner — hiring speed, expertise, and cost breakdown.
/ Our verdict
Use us to ship v1. Hire in-house to own v2+ if AI is core.
3
Eazyware wins
1
Ties
2
In-house team wins
Side by side
How they compare, dimension by dimension.
Dimension
Eazyware
In-house team
Time to first production ship
6-14 weeks
6+ months (hire + ramp)
True cost of one AI engineer (loaded)
N/A
$250k+/year in US
Specialization depth
Day 1
Build over months
Long-term ownership
Hand-off required
Native
Flexibility / ramping down
Engagement ends cleanly
Layoffs are expensive
Institutional knowledge retention
Documented at handoff
Lives with your team
/ Pick Eazyware when
- AI is new to your org — needs a working example
- You need production AI in 1 quarter
- You have uncertain demand (not sure if AI is strategic)
- You want to learn what "good" looks like
/ Pick In-house team when
- AI is core to your company strategy
- You have 12+ months and budget to hire
- Long-term ownership is non-negotiable
- You can attract senior AI talent at US salary scales
Our take
We often run in parallel with client teams. Partner with us for v1, upskill your team alongside us during the engagement, then run v2+ internally. Best of both approaches.
/ Next step
Still not sure which to pick?
A 30-minute call with our team is often faster than more research. Let's talk through your specific context.
~4h
avg response
Q2 '26
next slot
100%
NDA on request