Router by Ramp - Tokens are money. Save both.

Hey PH fam!

Excited to hunt Router.com by Ramp for the global builder and engineering community today!

Here’s the pattern we keep seeing across AI development: as teams scale multi-agent systems and complex workflows, LLM inference bills balloon, and developers spend half their sprint juggling separate API integrations, rate limits, and fallback strategies.

We optimized for multi-model flexibility, but ended up with a fragmented nightmare of API keys and unpredictable costs.

Router.com fixes the plumbing.

Built by Ramp, it puts a single, unified endpoint in front of every top closed and open-source model—dynamically routing each request to the lowest-cost model that meets your performance threshold, saving teams an average of 40% on inference spend.

What stood out most to me:

→ One endpoint, total coverage: Access OpenAI, Anthropic, SpaceXAI, and open-source models through a single API key without rewriting your codebase

→ Intelligent auto-routing: Matches request complexity to the optimal model, ensuring you don't overpay for simpler background tasks

→ Built-in spend visibility: Pairs raw inference routing with Ramp’s financial engine, mapping token usage directly back to teams and budgets

→ Instant setup: Zero-cost routing layer through 2026, plus $26 in model credits to test it out right away

Rahul and the Ramp engineering team are here all day.

Question for the community: As multi-model architectures become the default, how are you currently balancing frontier model performance against your monthly inference budget? Curious to hear how teams handle this trade-off 👇