Prompt
I'm building a SaaS app and need a gateway for OpenAI, Anthropic, and Gemini requests; what should I use?
Latest observation
If you want one gateway for OpenAI, Anthropic, and Gemini, the usual choice is:
Best fit: an LLM gateway / abstraction layer
Look at one of these:
- LiteLLM Proxy — most popular open-source option
- Portkey — managed gateway with observability and controls
- OpenRouter — unified API for multiple model providers
- Helicone — great for observability; can be paired with a gateway
- LangSmith / Langfuse — more for tracing/observability than pure gatewaying
My practical recommendation
If you want control and flexibility:
Use LiteLLM Proxy
- Supports OpenAI, Anthropic, Gemini, and many others
- Gives you one OpenAI-compatible API surface
- Good for:
- provider routing
- retries/fallbacks
- rate limits
- spend tracking
- key management
- model aliasing
- Nice if you want to run it yourself
If you want the fastest production setup:
Use Portkey
- Easier managed experience
- Built-in observability, fallbacks, policies, governance
- Good for SaaS teams that don’t want to run infra
If you just want one API endpoint and model access:
Use OpenRouter
- Very simple unified access
- Good for quick integration
- Less of a “full gateway” and more of a model router/marketplace
What I’d choose by stage
- MVP / startup: OpenRouter or Portkey
- Scaling SaaS with infra control: LiteLLM Proxy
- Need logs, audits, prompt tracing: Portkey + Langfuse/Helicone
- Need strict governance / internal platform: LiteLLM self-hosted or custom gateway
Important features to require
Whatever you pick, make sure it supports:
- OpenAI-compatible API so your app only integrates once
- Multi-provider routing and fallback
- Per-tenant API keys
- Usage metering and billing
- Observability / request logs
- Timeouts, retries, circuit breakers
- Model normalization across providers
Quick stack suggestion
For a SaaS app:
- Gateway: LiteLLM Proxy
- Tracing: Langfuse or Helicone
- Billing/usage: your own metering DB + gateway logs
- Fallbacks: route OpenAI → Anthropic → Gemini depending on task/cost
If you want, I can also give you:
- a side-by-side comparison table of LiteLLM vs Portkey vs OpenRouter, or
- a reference architecture for a SaaS multi-tenant LLM gateway.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
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