Build in-house when AI is your core product and you'll be shipping models for years. Hire a partner when you need production AI soon, can't yet justify a permanent senior team, or your own team has never taken a model to production before. Most companies need both over time, just not at the same time.

One Line

What we build

The TCO Most CTOs Underestimate.

Hiring takes months

A senior ML engineer or platform lead can take 3 to 6 months to find and land in this market , and that's time your initiative isn't moving.

What we build

RAG (retrieval)

Gives the model your knowledge at answer time. Retrieve the relevant documents and hand them over so it answers from your truth, not its training. Right when the model needs facts specific to your business, especially ones that change.

What we build

Management load

The management load of a new AI team falls on you and your leads.

What we build

The failed first project

First AI projects fail not because the idea was bad, but because nobody had shipped production AI before , lessons learned on your budget and your timeline.

What we build

Overview

Side By Side.

Cost / factor	Build in-house	Hire a partner
Time to first value	4–9 months (hire, ramp, first ship)	Weeks to first working output
Senior talent	You compete for it in a tight market	Already on the team, day one
Cost shape	Fixed: salaries, benefits, equity, ongoing	Variable: scoped to the work, scales down when done
Risk of a failed first project	Higher: learning on your time and budget	Lower: patterns proven on prior builds
Management overhead	Falls on you and your leads	Engagement lead carries it
Long-term ownership	Full, in-house from the start	Transfers to you as part of the engagement
Best when	AI is your core product, multi-year roadmap	You need production AI soon, or to de-risk the first build

Highlights

The Honest Case For Building In-House.

AI is your core product

What it meansIf AI is core to your product and requires years of development, an in-house team is more cost-effective long term.

You have senior shippers

What it meansIf you already have senior people who've shipped production AI, you may not need outside help at all.

Capability stays internal

What it meansSome teams simply prefer to keep all capability internal, which is a legitimate strategic choice.

The status quo

How We De-risk The Partner Path.

When teams work with us, the model is built to avoid the usual fear of an outside vendor. We embed senior engineers as an extension of your team, you keep the code and the architecture, and we transfer the capability so you're stronger when we leave, not dependent. A first engagement is scoped to prove value fast, before you commit to more.

↳ The status quo

De-risk

↳ The status quo

Questions

Frequently Asked Questions.

Per month, often yes. Per outcome, usually no, once you count hiring time, ramp, management load, and the cost of a failed first attempt. That's the number the worksheet below actually compares.

Isn't a partner more expensive per month?

That's the most common path. Use a partner to ship the first production AI and prove the value, then hire against a roadmap you've de-risked, with patterns the partner helped establish.

Can we start with a partner and build in-house later?

Then a partner can fill the gap now while your hires land and ramp, so the initiative doesn't stall for two quarters waiting on headcount.

What if we already started hiring?

Resources

Insights for tech leaders.

Whitepaper · PDF

Build vs Buy in the AI Era

Whitepaper · PDF

HIPAA and AI: The PHI Exposure Problem Your Engineering Team Does Not Know It Has

Let's build

Ready to See the Real Numbers?.

Bring your actual numbers. We'll walk through a real total-cost-of-ownership comparison for your situation, including an honest read on whether building in-house is the better call.

Talk through your TCO with us

Build An In-House AI Team, Or Hire A Partner?.

See Logiciel in action.

The Decision In One Line.

The TCO Most CTOs Underestimate.

Hiring takes months

RAG (retrieval)

Management load

The failed first project

Side By Side.

The Honest Case For Building In-House.

AI is your core product

You have senior shippers

Capability stays internal

How We De-risk The Partner Path.

Frequently Asked Questions.

Insights for tech leaders.

Build vs Buy in the AI Era

HIPAA and AI: The PHI Exposure Problem Your Engineering Team Does Not Know It Has

Ready to See the Real Numbers?.