The Economics of Voice AI: Why We Need Custom Infrastructure

August 16, 2025 · X11.Social Team · Technical, Infrastructure

The Real Cost of Voice AI

We started with ElevenLabs Conversational AI. Great quality, challenging economics.

At $0.10/minute (their current rate), offering 150 minutes for $39/month costs us $15 in voice alone. Add LLM costs, infrastructure, and we’re barely breaking even.

The problem? This doesn’t scale.

The Infrastructure Question

We’re researching custom voice infrastructure that could reduce costs by 10x or more. This is currently in planning phase - we’ll switch once we reach critical mass and it makes economic sense.

Current Reality

  • ElevenLabs Conversational AI: $0.10/minute (plus LLM costs)
  • Total with LLM: ~$0.15/minute all-in
  • Custom Infrastructure: $0.02/minute (achievable target)

A 5-7x reduction would make us profitable at scale.

The Plan (When We Hit Scale)

My Background

I’ve built custom voice infrastructure before. This isn’t theoretical - I’ve deployed ASR systems, optimized models, and reduced costs by orders of magnitude. I know what’s possible.

Technologies Being Evaluated

  • Open-source ASR models: Various streaming transcription options
  • Direct audio streaming: Peer-to-peer connections without middlemen
  • Self-hosted infrastructure: Running models on our own hardware
  • Distributed processing: Regional deployments for low latency

Why Wait?

  1. Focus on product: Get features right first
  2. User validation: Prove people want this
  3. Scale economics: Infrastructure makes sense at 1000+ users
  4. Smart sequencing: Use proven solutions until scale demands custom

The Architecture

Before (ElevenLabs)

graph LR
    A[User] -->|Phone Call| B[ElevenLabs]
    B -->|Transcription| C[AI Processing]
    C -->|Response| B
    B -->|Voice| A
    
    style B fill:#54453a,stroke:#2e2a3d,stroke-width:2px,color:#fff
    style C fill:#2a3a4a,stroke:#2e2a3d,stroke-width:2px,color:#fff

Current: $0.10/min + LLM costs, 500-800ms latency

Future (Custom Infrastructure)

graph LR
    A[User] -->|Direct Stream| B[Our Infrastructure]
    B -->|Local ASR| C[Transcription]
    C -->|Process| D[AI]
    D -->|TTS| B
    B -->|Voice| A
    
    style B fill:#2d4a3a,stroke:#2e2a3d,stroke-width:2px,color:#fff
    style C fill:#2a3a4a,stroke:#2e2a3d,stroke-width:2px,color:#fff
    style D fill:#4a3a5c,stroke:#2e2a3d,stroke-width:2px,color:#fff

Target: ~$0.02/min (5x cheaper), similar or better latency

What We’re Learning

ElevenLabs Is Great, But…

  • Quality is excellent
  • Integration is simple
  • But unit economics don’t work at scale

The Sweet Spot

We don’t need 100x cheaper. Even 5x cheaper transforms the business:

  • Current: Small margins
  • At 5x reduction: Healthy 70% margins
  • That’s sustainable growth

Cost Analysis

For 10,000 minutes/month:

  • ElevenLabs Conversational AI: $1,000 (plus LLM)
  • Custom Infrastructure: ~$200 (all-in)

The math is clear at scale.

The Reality Check

Why Not Yet?

  1. Product first: Features matter more than infrastructure
  2. User validation: Need to prove demand
  3. Engineering resources: Small team, big ambitions
  4. Risk management: Don’t optimize prematurely

When Will We Switch?

  • Trigger point: 500+ active users
  • Economics: When voice costs exceed $5K/month
  • Timeline: When it makes business sense
  • Approach: Gradual rollout with testing

The Smart Approach

Use What Works Now

  • ElevenLabs is expensive but reliable
  • Focus on getting users first
  • Infrastructure can wait

Plan for Scale

  • Research alternatives now
  • Build prototypes on the side
  • Switch when economics demand it
  • Keep it simple

Cost Breakdown

Per User Per Month (150 minutes)

Current (ElevenLabs):

  • Voice API: $15
  • LLM costs: $7.50
  • Total: $22.50
  • Revenue: $39
  • Margin: $16.50 (before other costs)

Future (Custom):

  • Infrastructure: $3
  • LLM costs: $7.50
  • Total: $10.50
  • Revenue: $39
  • Margin: $28.50 (healthy profit)

At Scale (1,000 users)

Monthly Costs:

  • ElevenLabs + LLM: $22,500
  • Custom + LLM: $10,500

Potential Savings: $12,000/month

That’s $144,000/year - enough to justify the engineering investment.

The Honest Truth

We Haven’t Deployed It Yet

  • I’ve built this before - I know it works
  • Have working prototypes
  • Waiting for the right time to switch
  • ElevenLabs is good enough for now

Why I’m Confident

This isn’t my first voice infrastructure project:

  • Built real-time ASR systems before
  • Deployed Whisper at scale
  • Reduced costs 10x+ in previous projects
  • Know exactly what’s needed

Why Tell This Story?

Because every technical founder faces this:

  • You know how to build it better/cheaper
  • But you need users first
  • Infrastructure comes after product-market fit

We’re being transparent about the journey.

Lessons We’re Learning

1. Start With What Works

ElevenLabs is expensive but it works. Ship first, optimize later.

2. Be Honest About Costs

We lose money on every user. That’s okay for now. Growth first.

3. Plan for Scale

Research solutions now. Build when it makes sense.

What’s Actually Next

Get to 100 Users

Prove people want this first.

Then 1,000 Users

That’s when infrastructure matters.

Then Switch

When we’re losing real money, we’ll build it.

For Other Founders

Facing similar economics?

  1. Don’t optimize too early
  2. Use expensive APIs to validate
  3. Switch when you have revenue
  4. Be transparent about the journey

The Business Impact

Current State (ElevenLabs)

  • Lose money on every user
  • Can’t scale pricing
  • Dependent on third party
  • No differentiation

Future State (Custom Infrastructure)

  • Profitable unit economics
  • Flexible pricing tiers
  • Full control
  • Unique offering

The Current Reality

We’re using ElevenLabs. It’s expensive. We’re okay with that.

When we have enough users to justify custom infrastructure, we’ll build it.

Until then, we focus on making the best product possible.

Try it at x11.social

The Bottom Line

We could reduce costs by 10x with custom infrastructure.

But first, we need users who love the product.

That’s the real challenge.

Building voice infrastructure? Let’s chat: @x11_social

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