LIVE WEBINAR

Build, Buy or Hire for AI

How to decide whether to build in-house, buy off-the-shelf, or hire for AI — before your AI roadmap costs you six figures.

Duration
30-45 min + Q&A
Format
Live, interactive
Cost
Free
Limited to 50 seats — register to hold yours
Register Free

No spam. No sharing your details. Unsubscribe anytime.

You're registered.

Confirmation is on its way to your inbox. See you there.

What You'll Learn

✓
Why 32–68% of ML projects fail to reach production — and the #1 reason they fail (89% cite unclear problem definition).
✓
The real cost of building AI in-house — $180K–$240K/year fully loaded per ML engineer, before infrastructure and data pipeline costs.
✓
When to buy vs when to build — Stripe built fraud detection in-house. Slack bought the OpenAI API. Which decision are you facing?
✓
The 5% trap — ML code is only 5% of a production ML system. The other 95% is configuration, data pipelines, and monitoring infrastructure.
✓
A 2-week decision framework — How to evaluate build/buy/hire so you have a decision, not a debate, by day 10.
SaaS founders & CTOs
AI/ML product managers
Engineering leaders evaluating AI roadmaps

Your Host

JM

Jake McMahon

Founder, ProductQuant
Product analytics and GTM specialist for B2B SaaS with deep experience in AI product strategy. Jake has worked with scale-ups and VC-backed companies on AI roadmap evaluation, build-vs-buy decisions, and product-led go-to-market.

Event Details

Duration
30-45 min
Format
Live + Q&A
Seats
50
Cost
Free

Ready to move?

Register now to secure your seat. You'll get the Zoom link and a pre-work packet before the session.

Register Free