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Applied AI, Without the Decks: How ElevenLabs Turned Localization From Cost-Center to AI Growth Engine

1 - Why?

I’ve sat through enough “AI transformation” meetings to know the ending: Big Vision -> Impressive Slides -> “Let’s form a task force” -> Death by committee. Here’s what pisses me off: everyone’s debating strategy some teams are just shipping.

One of them? ElevenLabs. Let me show you what execution looks like.

2 - TL;DR

ElevenLabs killed the localization agency model by building a lean internal AI pipeline: ASR → LLM → TTS → Human QA.

Result: 90% cost reduction, hours instead of weeks to launch, and the ability to ship campaigns in 30+ languages simultaneously.

3 - What Changed?

ElevenLabs was doing what everyone does:

  • $50k localization platform
  • Agencies for every market ($100k+/year)
  • Delays, back-and-forth, endless approvals

Then someone did the obvious: Proofread the copy with GPT. It crushed the agency’s work.

That broke the loop.

Before AI:

  • Localization = days to weeks
  • Cost = $150k+ per campaign
  • Brand voice = fragile across markets

After AI:

  • Localization = done in hours
  • Cost = -90%
  • Quality = 90% AI, 10% human mod (on the edges)
💡 Critical unlock:
  • It wasn’t just cost savings.
  • They could launch globally, simultaneously—a growth advantage worth way more.

That’s what I call Applied AI. No decks required.

4 Patterns You Should Shamelessly Copy

4.1. Pattern #1 — Hunt for “High Cost, Low Novelty”

Jobs where:

  • You pay six figures.
  • The work is boring and repetitive.
  • Failure is reversible (“just send it back to the old vendor”).

🔍 Check your P&L.

You’ll find something equally dumb you’re overpaying for.

4.2. Pattern #2 — Internal First, External Never

They shipped for one team: marketing.

That meant:

  • No multi-tenant security headaches
  • One brand voice to tune
  • Instant Slack feedback loop

Don’t launch platforms. Solve your problem first.

4.3. Pattern #3 — 90% Agent, 10% Human

Forget the “autonomous AI” hype.

Here’s what works:

  1. AI translates 90% of it
  2. Human reviews edge cases
  3. Feedback gets fed back into the RAG store

Net:

  • ⏱ 10% of the old workload
  • ✅ Higher quality

5 The 6-Point Applied-AI Checklist

  1. One-Sentence Problem “We burn $X translating Y.”
  2. Quantifiable Win Track cost-per-word or time-to-publish.
  3. Weekend MVP If it takes > 2 weeks to test, cut the scope again.
  4. Tight Feedback Loop Build a team that shares a Slack with users.
  5. Cheap Reversal Plan Keep fallback vendor on standby—no risk.
  6. Metrics First Hook logs into cost dashboards before UX polish.

No pitch decks. No working groups. Just applied AI that frees up growth.