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How Fusion Reduces AI Costs by 70%

Product Team
November 3, 2025
How Fusion Reduces AI Costs by 70%

How Fusion Reduces AI Costs by 70%

AI costs can spiral quickly. Between GPT-4, Claude, and other premium models, organizations often spend thousands per month on AI infrastructure. Fusion changes that.

The Cost Problem

Most organizations overspend on AI because:

  1. Over-provisioning: Using GPT-4 for simple tasks
  2. Lack of visibility: No clear understanding of usage patterns
  3. Manual routing: Human decisions on model selection
  4. No optimization: Missing opportunities for cost savings

Fusion's Approach

1. Smart Model Selection

Fusion automatically routes requests to the most cost-effective model that meets your quality requirements.

// Example: Fusion automatically chooses the right model
await fusion.complete({
  prompt: "Summarize this article",
  targetQuality: 0.85,
  optimize: "cost"
});
// Routes to GPT-3.5 instead of GPT-4, saving 90% on cost

2. Request Batching

Group similar requests together for bulk processing at lower rates.

3. Caching

Fusion caches common responses to avoid redundant API calls:

  • Semantic similarity matching
  • TTL-based invalidation
  • Configurable cache policies

4. Fallback Strategies

Start with cheaper models, escalate only when needed:

const strategy = {
  primary: "gpt-3.5-turbo",
  fallback: ["claude-2", "gpt-4"],
  escalationTrigger: "quality < 0.8"
};

Real Results

Before Fusion

  • Monthly spend: $15,000
  • Average cost per request: $0.08
  • Wasted spend: ~40%

After Fusion

  • Monthly spend: $4,500 (70% reduction)
  • Average cost per request: $0.024
  • Quality improvement: +15%

Cost Optimization Features

Budget Controls

Set spending limits and alerts:

  • Daily/monthly caps
  • Per-team budgets
  • Real-time alerts

Analytics Dashboard

Track costs in real-time:

  • Cost per model
  • Cost per user/team
  • Trend analysis
  • Optimization recommendations

Model Comparison

A/B test different models to find the best cost/quality balance.

Getting Started

  1. Connect your models: Add API keys for your AI providers
  2. Set policies: Define quality requirements and budget constraints
  3. Deploy: Route all requests through Fusion
  4. Monitor: Watch costs decrease while quality improves

Best Practices

1. Start Conservative

Begin with strict quality requirements, then optimize:

{
  minQuality: 0.95,
  optimize: "quality"
}

2. Use Quality Scoring

Enable automatic quality assessment:

{
  enableQualityScoring: true,
  feedbackLoop: true
}

3. Monitor and Adjust

Review analytics weekly and adjust policies based on actual usage.

ROI Calculator

Estimate your savings:

  • Current monthly AI spend: $_____
  • Expected reduction: 60-70%
  • Estimated savings: $_____/month
  • Annual savings: $_____/year

Conclusion

With Fusion, you don't have to choose between cost and quality. Get both with intelligent orchestration.

Ready to reduce your AI costs? Get started with Fusion →

Need help with cost optimization? Our team is here to help: [email protected]

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