The Problem
Cloud API costs and latency make large-scale agent automation uneconomic for operators — and you pay for every token they "think." That adds up fast: $145/day = ~$4,350/month just in inference fees.
The Solution — Local Inference
Run task-specific, quantized models (3B/7B) on your own inference server. Once the server is paid for, marginal inference cost is essentially zero.
How It Works
- Task-specific models: small, fast models for call summaries, email triage, and content drafting.
- Speed-as-conversion: sub-second reply windows for lead follow-up.
- Privacy-first: customer data stays on-prem or on your private host.
Cost Comparison
| Item | "The Other Guy" (API) | Project Studios (Local) |
|---|---|---|
| Inference cost | $145/day → ~$4,350/mo | ~$500/mo hosting — marginal inference ≈ $0 |
| Management | $2,000/mo | $1,000/mo |
| Total monthly | ~$6,350/mo | ~$1,500/mo |
| Monthly saving | ~$4,850/mo | |
The Profit Stack
- Private AI Employee — flat yearly fee, no per-token surprises.
- LeadStream attribution — agentic follow-up integrated with your pipeline.
- Reduced API spend — margin stays in your pocket.
Example
A custom LeadStream agent summarises missed calls instantly and emails the sales rep. Marginal cost per lead ≈ $0, response time <1s — much higher conversion.
Agentic SEO
Automatic monitoring, drafting, and publishing of location-intent pages when competitive signals change. The agent drafts the page, pings for a photo, and publishes — all with human oversight.