Integrate Narev with Helicone Gateway for LLM Cost Optimization
Use Narev to test and validate model configurations before deploying to Helicone Gateway. Reduce LLM costs by 99% while maintaining quality through systematic A/B testing.
Helicone Gateway monitors your LLMs. Narev tells you what to optimize. Helicone Gateway gives you observability, logging, and analytics for your LLM applications. But which models should you use? What's the actual cost difference? Will quality suffer if you switch? Narev answers these questions before you change production.
The Problem with Helicone Gateway Alone
Helicone Gateway is an excellent observability platform—it provides detailed logging, analytics, caching, and cost tracking for your LLM infrastructure. But observability alone doesn't optimize: you need to know what changes to make.
With visibility into costs and usage patterns, teams often:
- See high costs but fear switching models without validation
- Test models manually by deploying to production and hoping for the best
- Guess at which model offers the best cost-quality-latency tradeoff
- Miss optimization opportunities because testing is time-consuming
The result? Most teams overspend on LLMs by 10-100x because they lack systematic testing.
How Narev + Helicone Gateway Work Together
Narev and Helicone Gateway complement each other perfectly:
Tool | Purpose | When You Use It |
---|---|---|
Narev | Test models systematically to find optimal configuration | Before changing production |
Helicone Gateway | Monitor production LLM usage with observability and analytics | In production, after testing |
The workflow:
- Export production traces from Helicone Gateway's dashboard
- Test alternative configurations in Narev with A/B experiments
- Deploy winners with confidence
- Monitor results using Helicone Gateway's analytics and repeat continuously
Integration Guide
Step 1: Export Your Helicone Gateway Usage Data
Narev works with your existing Helicone Gateway logs to create realistic test scenarios. Export your recent prompts, model selections, and response patterns from Helicone Gateway's dashboard to build experiments that reflect your actual production workload.
Step 2: Create Your First Experiment
Let's say you're currently using gpt-4o-mini
through Helicone Gateway and want to explore if Claude 3.5 Haiku offers better performance.
Create an experiment in Narev testing:
Variant A (Baseline)
claude-3-5-haiku-20241022
Variant B
gpt-4o-mini
Narev will test both variants on the same prompts and measure:
- Cost per request and per million tokens
- Latency (time to first token, total response time)
- Quality (accuracy, completeness, tone)
Step 3: Analyze Results with Confidence
Narev provides clear data on which model performs best:
Step 4: Update Your Helicone Gateway Configuration
With data-backed confidence, update your Helicone Gateway integration:
// Before: Using GPT-4o-Mini
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
baseURL: "https://oai.helicone.ai/v1",
defaultHeaders: {
"Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`,
},
});
const response = await client.chat.completions.create({
model: "gpt-4o-mini", // ← Old default
messages: [...],
});
// After: Switch to Claude 3.5 Haiku based on Narev results
import Anthropic from '@anthropic-ai/sdk';
const client = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY,
baseURL: "https://anthropic.helicone.ai",
defaultHeaders: {
"Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`,
},
});
const response = await client.messages.create({
model: "claude-3-5-haiku-20241022", // ← Tested winner
messages: [...],
});
Step 5: Monitor and Iterate
Helicone Gateway's analytics dashboard will show you the real-world performance. Use Narev to:
- Test new models before switching in production
- Experiment with prompt variations
- Validate caching strategies with different model configurations
- A/B test temperature and parameter changes
Why Test Before Deploying with Helicone Gateway?
Without Narev: Risky Approach
- "Should we try Claude instead of GPT-4?"
- Deploy directly to production
- Hope quality doesn't drop
- Wait days/weeks for enough data in Helicone Gateway
- Quality issues surface → rollback
- Lost time + degraded user experience 💸
With Narev: Data-Driven Approach
- "Should we try Claude instead of GPT-4?"
- Test in Narev with production-like prompts
- Get results in minutes with statistical confidence
- Deploy winner with confidence ✅
- Monitor with Helicone Gateway
- Realize savings immediately 💰
Helicone Gateway Features Narev Helps You Optimize
1. Model Selection
Helicone Gateway gives you: Visibility into which models you're using and their costs
Narev tells you: Which cheaper models actually work for your use case
2. Cost Tracking
Helicone Gateway gives you: Real-time cost tracking per model and per user
Narev tells you: How to reduce those costs by 50-99% without sacrificing quality
3. Caching Strategy
Helicone Gateway gives you: Request caching to reduce costs
Narev tells you: Which model + caching combinations provide maximum savings
4. Rate Limiting
Helicone Gateway gives you: Rate limiting controls
Narev tells you: Which faster models let you handle more requests within limits
5. Custom Properties
Helicone Gateway gives you: Custom properties for request tagging
Narev tells you: Which configurations work best for different request types
Common Helicone Gateway + Narev Use Cases
🎯 Model Migration
Test whether switching from GPT-4 to Claude-3.5 or GPT-4o-mini maintains quality for your specific prompts before updating your code
📊 Cost Analysis
Use Helicone Gateway data to identify expensive patterns, then test cheaper alternatives in Narev before switching
💰 Cost Reduction
Systematically test cheaper alternatives to expensive defaults and validate they meet your quality bar
🔧 Parameter Tuning
A/B test temperature, max_tokens, and other parameters to optimize responses for cost and quality
Pricing: Narev + Helicone Gateway
Helicone Gateway pricing: Free tier available, paid plans based on usage
Narev pricing: Free for experimentation, no fees on top of your model costs
Combined value: Test $1 worth of prompts in Narev to validate a configuration that saves $10,000/month in production costs tracked by Helicone Gateway.
Getting Started
Step 1: Sign Up for Narev
Sign up - no credit card required.
Step 2: Export Data from Helicone Gateway
Export your prompts and traces from Helicone Gateway's dashboard to create your first experiment.
Step 3: Run Your First Test
Compare your current model against 2-3 alternatives. Results in minutes.
Step 4: Deploy Winners
Update your code with confidence based on real data, and monitor results in Helicone Gateway.
Frequently Asked Questions
Start Optimizing Your LLM Costs Today
Stop guessing which models to use. Start testing systematically.
Next Steps: - Read the 3-Step FinOps Framework for AI - See how to reduce costs by 99% by switching models - See how to reduce costs by 24% by prompt engineering