The Cost Problem with AI Applications
Running AI applications at scale quickly becomes expensive. A single OpenAI GPT-5 API call can cost $0.03 per 1K tokens for input and $0.06 per 1K tokens for output. For a SaaS chatbot handling 100,000 requests per day, this translates to $6,000+ per month in API costs alone.
Enter Multi-Provider Routing
B2ALABS® AI Gateway solves this by intelligently routing requests across multiple LLM providers based on cost, performance, and availability. Here's how it works:
1. Real-Time Cost Calculation
Before sending a request, B2ALABS® estimates the token count and calculates the cost across all available providers:
OpenAI GPT-5: $0.005 per request
Anthropic Claude: $0.004 per request
Google Gemini 2.5 Pro: $0.0015 per request
Google Gemini 2.5 Flash: $0.0003 per request (94% cheaper!)2. Intelligent Routing Strategy
The gateway selects the cheapest healthy provider automatically. For the example above, routing to Gemini 2.5 Flash saves $0.0047 per request. At 100K requests/day, that's $470/day or $14,100/month in savings.
3. Automatic Failover
If the cheapest provider is down or rate-limited, the gateway automatically fails over to the next best option. No manual intervention required.
Real-World Case Study
One of our customers, a SaaS company with a customer support chatbot, implemented B2ALABS® and achieved the following results:
- Before: 100% traffic to GPT-3.5-turbo = $6,000/month
- After: 60% to Gemini 2.5 Flash, 40% to GPT-3.5-turbo = $1,800/month
- Savings: $4,200/month (70%)
- Annual savings: $50,400
Semantic Caching: The Ultimate Optimization
Beyond smart routing, B2ALABS® offers semantic caching. When a similar question is asked, the gateway returns the cached response instantly—no API call needed.
How Semantic Caching Works
- Generate an embedding (384-dimensional vector) for each prompt
- Calculate cosine similarity with cached prompts
- If similarity exceeds 95%, return cached response
- Cache hit = 100% cost savings + 95% latency reduction
Our customers see an average cache hit rate of 34%, which means one-third of all requests are essentially free.
Getting Started
Implementing cost optimization with B2ALABS® takes less than 10 minutes:
- Add API keys for multiple providers (OpenAI, Gemini, Claude, Mistral)
- Enable semantic caching with Redis
- Configure routing strategy (default: lowest_cost)
- Monitor savings in Grafana dashboard
docker-compose up -d
curl http://localhost:8080/health
# Ready to save money!Monitoring Your Savings
B2ALABS® includes a Grafana dashboard showing:
- Cost per request by provider
- Total savings vs. single-provider
- Cache hit rate
- Request distribution
- Cost trends over time
Conclusion
With B2ALABS® AI Gateway, you can reduce your AI infrastructure costs by 40-75% without changing a single line of application code. Multi-provider routing and semantic caching work together to minimize expenses while maintaining or even improving performance.
Ready to start saving? Check out our Getting Started guide or Cost Optimization course.