Strategy
The build-vs-buy decision most teams get backwards
The question isn't cost — it's who owns the failure mode a year from now.
// AI ADOPTION, MALAYSIA
Ship the boring AI pilot first Labcognia
A no-hype guide to build-vs-buy decisions, vendor evaluation, and the questions worth asking before an AI tool touches customer data. No demos, no sales calls.
Read build vs. buy
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Most failed AI pilots did not fail on the model — they failed on the exit clause nobody read before signing.
Before you sign
What actually matters before the contract
Not a feature checklist — the four things that cause the most regret later.
- Data residency & access Where does customer data actually sit, and who at the vendor can read it — not just what the marketing page claims.
- Exit path A documented, tested export format — asked for and confirmed before signing, not discovered while trying to leave.
- Pricing at 10x volume Per-seat and per-call pricing that looks reasonable at pilot scale can look very different at real usage.
- Human-in-the-loop fallback What happens, concretely, the first time the model is confidently wrong in front of a customer.
Deciding whether to build
Open the comparison
Build vs. buy, compared plainly
A dedicated page — timeline, cost shape, and who should own it, side by side.
Common questions
Before you keep reading
No. Labcognia is an independent guide — we don't sell software or take referral fees from vendors.
No — most of the content is written with small and mid-size teams in mind, where a bad vendor pick hurts more.
No — we describe questions and principles, not named products or rankings.
Good to know: Labcognia is a purely editorial resource. We do not sell software, resell vendor products, or accept referral fees here.