Wavelength White-Label Platform
Turning our battle-tested voice agent infrastructure into a multi-tenant platform that other businesses can resell.
$0.013 cost vs $0.07 sell
Calls/month capacity on 3 GPUs
Infrastructure cost at scale
Calls per 3-GPU cluster
The Problem
After building Wavelength for our own use and proving it works across 10+ bot personas and thousands of calls, we realized the same infrastructure could serve other businesses. Coaching companies, course creators, and agencies all need AI calling capabilities but don't have the engineering team to build it. The existing market (Vapi at $0.08-0.15/min, Retell at similar pricing) is expensive and doesn't offer the customization our clients need.
What We Built
A white-label platform architecture on top of Wavelength:
Multi-tenant system:
- Each client gets isolated bot configurations, call logs, and analytics
- Clients can customize personas, scripts, and conversation flows without touching code
- Bot config format supports: system prompts, persona engine, product intelligence, social proof injection, situation-based response injection, and GHL workflow triggers
Client dashboard:
- Call history with transcripts, recordings, summaries
- Analytics (calls today/week/month, happiness scores, conversion rates, trend charts)
- Usage and billing visibility
- Manual call trigger capability
Admin dashboard:
- All clients overview with per-client call volumes and revenue
- System health monitoring (active calls, queue depth, error rates)
- Client management (add/edit/suspend)
- Revenue dashboard with margin analysis
Billing system:
- Per-minute usage tracking (rounded to nearest 6 seconds)
- Monthly invoice generation with full breakdown
- Cost vs revenue margin tracking per client
The Numbers
| Metric | Value | Context |
|---|---|---|
| Our cost per minute | ~$0.013 | Plivo + Gemini + STT + infra combined |
| Client price per minute | $0.07 | Cheaper than Vapi/Retell for them |
| Gross margin | ~5.4x | $0.057 profit per minute |
| Monthly infra cost (3x A40) | $378 | Handles 10 concurrent calls |
| Calls/month capacity | 25,000-75,000 | Depends on operating hours (8-24hr) |
| Revenue at 100K min/month | $7,000 | Against ~$1,300 in costs = $5,700 gross profit |
| Scaling cost per pod | $0.35/hr | Just add a GPU, no re-architecture needed |
| Concurrent calls per pod | 3-5 | Validated through load testing |
Key Engineering Challenges
1. Multi-Tenant Isolation: Each client's bot config, call recordings, transcripts, and analytics must be completely isolated. A bug in one client's prompt or a spike in their call volume cannot affect another client's service quality. Built tenant-level resource isolation with independent connection pools.
2. Scaling Without Re-Architecture: Designed the session router so that adding capacity is literally “spin up another GPU pod via RunPod API.” No code changes, no deployment, no migration. The router auto-discovers new pods and distributes calls.
3. Cost Model Validation: Ran detailed cost analysis across Plivo (telephony ~Rs 0.50-1.00/min), Gemini (LLM ~Rs 0.30-0.50/min), STT (~Rs 0.10/min), and infrastructure (~Rs 0.10/min) to validate that the 5x margin holds at different volume tiers. The margin actually improves at scale because GPU costs are fixed while per-minute telephony costs are variable.
Want to build something like this? Let's talk.