How Narev fits your stack?
Narev complements your observability, gateway, and FinOps tools—it's the experimentation layer that connects them.
Your observability tools show you the problem. Narev tells you the solution. Helicone shows you spent $50K on GPT-4 this month. Your gateway makes it easy to switch models. Your FinOps dashboard tracks the unit economics. But none of them answer: Should I switch to Claude? Will GPT-4o-mini hurt quality? What's the actual ROI? That's what Narev does.
The missing experimentation layer
Your LLM stack has three layers:
| Layer | Tools | Purpose | |
|---|---|---|---|
| Provider | OpenAI, Claude, Groq | Generates responses | Narev Finds your optimal configuration |
| Gateway | OpenRouter, LiteLLM, Portkey | Routes production traffic | |
| Observability | LLM: Helicone, Langfuse, W&B | Shows what happened | |
FinOps: Vantage, CloudZero, Finout | Tracks costs and spend |
Most teams have providers, gateways, and observability. Narev works with them, running experiments to optimize your entire stack.
How Narev works with your existing tools?
| Category | How Narev works together | What Narev adds |
|---|---|---|
| Provider (OpenAI, Anthropic, Groq) | Tests providers side-by-side on your prompts | Identifies which provider delivers the best cost/quality/latency |
| Gateway (OpenRouter, LiteLLM, Portkey) | Tests routing strategies and fallback configurations | Determines optimal routing logic and failover paths |
| Observability: LLM (Helicone, Langfuse, W&B) | Imports production traces and runs what-if experiments | Tests configurations before and during production |
| Observability: FinOps (Vantage, CloudZero, Finout) | Connects cost data to quality-aware optimization tests | Turns spend tracking into actionable cost reduction |
Who needs Narev?
You need Narev if:
- You're spending >$1K/month on LLMs and want to optimize systematically
- You can't afford to sacrifice quality when testing cheaper models
- Developers, PMs, and FinOps need shared visibility into optimization decisions
- You need data-backed answers to "should we switch models?"
You might not need Narev if:
- You're spending <$1K/month on LLMs
- You have unlimited budget with no optimization pressure
The bottom line
Narev connects your existing tools through systematic experimentation:
Import production traces → Test configurations → Deploy winners → Monitor results → Repeat
- Use it with your observability platform to find what works
- Use it with your gateway to route smarter
- Use it with your FinOps tools to optimize spend with confidence.