Technical Delivery Network
The build capability portfolio companies cannot hire for themselves.
What we do
Senior AI and data engineers are expensive, slow to recruit, and hard to hold onto inside a business that does not have a deep technical bench. Most portfolio companies need that capability in bursts, which makes permanent headcount the wrong instrument.
So we run a founder-led core team that scales through a vetted delivery network. Every engineer is technically screened before they touch client work. You scale up within 3-4 weeks and scale back without ongoing commitment.
The core team stays constant across the engagement, which is what keeps context and quality intact while the surrounding capacity flexes with the work.
A founder or director personally leads every engagement.
How it works
- A founder-led core team owns the engagement end to end
- Capacity scales through a vetted delivery network
- Every engineer technically screened before client work
- Scale up within 3-4 weeks
- Scale back without ongoing commitment
- A founder or director personally leads every engagement
Four capabilities
Automation
n8n, Python and API pipelines across CRM, scraping and alerting.
Agentic AI
LLM, RAG and agent pipelines wired into production systems.
Data and ML
Forecasting, modelling and pipelines decisions can rely on.
Full-stack
Internal tools and AI dashboards, front end through back end.
Common questions
How is this different from hiring a contractor or an agency bench?
Every engineer in the network is technically screened before they touch client work, and a founder or director personally leads every engagement. You are not handed a project manager and an unknown team. The core team stays constant and the network flexes around it.
How quickly can you scale up?
Within 3-4 weeks. That covers matching the right skills to the work and getting people onboarded into your systems properly rather than dropping unfamiliar engineers into a live codebase.
What happens when the work finishes?
You scale back without ongoing commitment. That is the point of the model: portfolio companies get access to senior build capability for the period they need it, without carrying permanent headcount for a capability they only need in bursts.
Why not just hire this team in-house?
This is the build capability most portfolio companies cannot hire for themselves. Senior AI and data engineers are expensive, slow to recruit, and hard to retain in a business that does not have a deep technical bench to keep them interested. The network gives access to that skill set without the recruitment risk.
Ready to put AI to work on your P&L?
Book a free discovery call. We'll map your highest-ROI opportunities in under 30 minutes, and tell you honestly if we're not the right fit.