The problem
Hiring is the slowest part of your roadmap.
The average time-to-fill for engineering roles is 62 days. Then a month of onboarding before they
ship anything meaningful. Meanwhile, priorities move, your team absorbs the gap, and the AI
initiatives leadership asked for stay on the backlog.
You need engineers who already work the way your team works.
We have them, vetted and ready to interview.
Embedded AI Teams: Two models
Two ways to add capacity.
You choose who runs the work.
You manage the work
Team Augmentation
Right talent, embedded into your team.
We source and recruit the senior profiles you need across our talent network, and
help you define them. Each professional joins your team directly, working within
your processes, tools, and culture. Onboarding, day-to-day management and
integration are yours.
Best for
Best for teams with strong engineering leadership that need more hands on a known
roadmap.
We manage the work
Team as a Service
A team that owns the outcome.
A cross-functional team that designs, builds, and ships what you prioritize, under
a clear Build, Operate, Transfer framework. A Delivery Manager owns delivery
health, backed by our Product, AI, Engineering, and PMO guilds. Scope is agreed
upfront and adapts as your priorities change.
Delivery stack with our IP:
Best for
Best for new products or AI initiatives that need a team running delivery end to end.
Embedded AI Teams
Senior, AI-native
engineers, hired in
20 days.
Add individual engineers your leads manage, or a full team we manage for you.
Same time zone, nearshore cost, productive in days instead of weeks.
01 · Senior only
02 · Hired in 20 days
03 · Onboarded in 4 days (for TaaS)
04 · US time-zone overlap
05 · 8 days to first candidate
Get Started
Ready to make AI useful?
Resources
