AI Model Tuning
Custom-tune AI models for your specific use case — using the latest parameter-efficient techniques to get enterprise results at startup costs.
Make AI Actually Understand Your Business
Off-the-shelf AI models are impressive, but they don't know your terminology, your edge cases, or your standards. Fine-tuning bridges that gap — and thanks to breakthroughs like TinyLoRA and RL-based training, it's now 100–1,000x cheaper than it was even six months ago.
What You Get
Assessment & Strategy (Day 1)
- Evaluate your use case for fine-tuning suitability
- Identify the right base model (open-source vs. proprietary)
- Design reward signals and evaluation criteria
- Estimate cost, timeline, and expected improvement
Model Tuning & Validation (Days 2–5)
- Prepare training data from your existing workflows
- Apply the most efficient tuning approach (RL, LoRA, TinyLoRA, or full fine-tune — based on your use case)
- Benchmark against base model on your real data
- Iterate until quality targets are met
Delivery
- Production-ready model adapter (hosted or self-hosted)
- Evaluation report with before/after metrics
- Documentation for your team to maintain and update
- Runbook for re-tuning as your data evolves
Ideal For
- Customer support teams — tune models to match your tone, policies, and product knowledge
- Legal & compliance — teach models your regulatory framework and document standards
- Data extraction — custom models that understand your specific document formats
- Domain-specific reasoning — healthcare, finance, manufacturing terminology and logic
Why This Approach
Most AI vendors will quote you $50K+ for a "custom model." They're using outdated techniques and oversized teams. Modern parameter-efficient methods mean:
- 26 bytes can teach an 8B model new reasoning capabilities
- Single GPU is enough for most business fine-tuning
- Hours, not weeks from experiment to production
- Per-task adapters that can run concurrently without extra infrastructure
The result: enterprise-grade customization at a fraction of the traditional cost.
Pricing
$4,500 — 1 week deliveryIncludes assessment, tuning, validation, and deployment. Additional adapters for different use cases: $2,000 each.
For ongoing tuning and optimization, consider our Fractional AI Lead retainer.
