CORE SERVICE

Custom AI Model Fine-Tuning

Generic ChatGPT and Claude are trained on everything—we train models on your specific data to master your domain. 30-50% accuracy improvements. 40-60% cost reduction. Competitive moats no-code cannot replicate.

Why Generic Models Fail at Domain-Specific Tasks

ChatGPT and Claude are trained on everything, which means they're experts at nothing specific.

Legal Firms

  • Miss jurisdiction-specific citations
  • Generate non-compliant documents
  • Hallucinate case law references

Healthcare / RCM

  • 75-85% accuracy on ICD-10 coding
  • Miss payer-specific rules
  • Cause claim denials & revenue loss

Recruitment

  • Miss nuanced qualifications
  • Can't apply client-specific criteria
  • Can't prioritize 15-30 weighted criteria

Fine-Tuning Delivers Measurable ROI

Custom models trained on your data outperform generic AI

30-50%

Accuracy Boost

40-60%

Cost Reduction

3-5x

First Year ROI

8-12

Week Delivery

$750K

Annual value for 50-attorney firm

2,500 hours saved × $300/hr

$180K+

Additional billing revenue

30-provider RCM company

$625K

Additional placement fees

200-placement recruitment agency

When You Need Fine-Tuning

Fine-tuning is a strategic investment. Here's when it makes financial sense.

Fine-Tuning Is Right For You If...

  • You have high-volume repetitive tasks requiring domain expertise
  • Accuracy requirements exceed 90% (compliance, revenue-critical)
  • You need competitive differentiation through proprietary AI
  • You have 5,000+ training examples available
  • Generic models consistently fail at your specific use case

Start with Standard AI Instead If...

  • Generic model accuracy (75-85%) is sufficient
  • You have fewer than 1,000 training examples
  • Use case is general-purpose (not domain-specific)
  • Budget is under $40K for AI project
  • RAG or prompt engineering can solve the problem

Our Fine-Tuning Process

8-12 weeks from kickoff to production deployment

1

Data Assessment

2-3 WEEKS
2

Model Training

3-4 WEEKS
3

Integration

2-3 WEEKS
4

Optimization

ONGOING

Fine-Tuning Use Cases

LEGAL FIRMS

Legal Document Intelligence

Train models on 10,000+ firm documents to master jurisdiction requirements, citation formats, and firm style.

  • 45-60% attorney review time reduction
  • 99%+ citation accuracy
  • Consistent firm voice
$100K-$200K
HEALTHCARE RCM

ICD-10 Coding Intelligence

Train on 50,000+ coded procedures with payer-specific rules to achieve 95-99% accuracy.

  • 95-99% coding accuracy
  • 40% reduction in denials
  • 15-25% revenue increase
$75K-$125K
RECRUITMENT

Candidate Matching Intelligence

Train on 5,000+ placements to understand client preferences and predict placement success.

  • 45% better match quality
  • 35% faster time-to-fill
  • 25% more placements
$60K-$120K

Investment & Pricing

Transparent pricing based on scope and complexity

Single Use Case

One specific task optimized

$40K-$75K
  • 5,000-10,000 training examples
  • 8-10 weeks delivery
  • Deployment + 30-day support
MOST POPULAR

Multi-Use Case

2-3 related tasks optimized

$75K-$150K
  • 15,000-30,000 training examples
  • 10-14 weeks delivery
  • Integration + 60-day support

Enterprise Custom

Complete domain specialization

$150K-$250K
  • 30,000-100,000 training examples
  • 14-20 weeks delivery
  • Multi-model + 90-day support

Ongoing Optimization Retainer

Keep your fine-tuned models performing at peak accuracy with ongoing monitoring, retraining, and capability expansion.

  • Monthly performance tracking
  • Quarterly retraining with new data
  • Priority support & consulting
  • Capability expansion for new use cases
$5K-$15K

per month

Why Work With Us

Fine-tuning requires deep ML expertise, domain knowledge, and production engineering skills that most AI consultants lack.

What We Bring

  • 15+ years software engineering experience
  • Deep domain expertise in healthcare, legal, recruitment
  • Production-grade infrastructure (Golang, TypeScript, Kubernetes)
  • HIPAA-compliant data handling with BAAs
  • 8-12 week delivery vs 6-12 months at enterprise consultancies

vs. Alternatives

VS NO-CODE PLATFORMS

Cannot fine-tune at all. Limited to generic pre-trained models with zero competitive differentiation.

VS LOW-COST AI IMPLEMENTERS

Lack ML expertise for fine-tuning. Can only do prompt engineering on pre-trained models.

VS ENTERPRISE CONSULTANCIES

Same outcomes at 40-50% lower cost. 8-12 weeks vs 6-12 months. Senior engineer delivery.

Ready to Build Your Competitive Moat?

Custom fine-tuned models create proprietary AI advantages that no-code platforms can never replicate.