Launched this week
One API key to 300+ models, hosted in the EU. Drop-in compatible with the OpenAI, Anthropic, and Google SDKs: switching is a base URL change. What's different: ~half our 30+ providers run inference in Europe, one EU sub-processor covers every model, no prompts stored by default. Add the control plane for routing, PII masking, per-team spend caps, and audit trails. Agent-native: paste one line into Claude Code or Cursor and it sets up Opper for you. No markup on tokens, 3% fee on credit top-ups.
Opper AI
Hey Product Hunt! Felix here, one of the founding members of Opper.
We're launching Opper, Europe's answer to OpenRouter: one API key to 300+ models across 30+ inference providers.
One integration to find the right model for any task, run it, and switch the moment something better ships. OpenAI, Anthropic, Google, Meta, xAI, Mistral, DeepSeek, plus the leading open-weight labs.
The reason we built it: there is no single best model. The lead changes every week, and wiring up a new provider every time it changes means new contracts, new SDKs, new billing. With Opper that's one integration, no new contract per model or provider.
Being European isn't just where we're incorporated, it's the product. Around half of our 30+ providers run inference in Europe, including sovereign hosts like Evroc, Berget, Geodd, and many more.
EU data residency, audit trails, and PII controls are built in, not bolted on. If you've ever needed the best models AND a straight answer on where your data runs, that's us.
On the control side: per-team spend caps and full cost visibility. Think Stripe for AI spend.
Where we are today: 50,000+ developers, powering AI for 10M+ end users, €3M raised from the investors behind Lovable.
You might already know us without knowing the name: we're the team behind the viral Car Wash Test, where we asked 53 models whether to walk or drive 50 meters to a car wash and only 5 said drive: opper.ai/blog/car-wash-test
That's now a thing you can do yourself with AI Roundtable: put any question to 200+ models and watch them answer and debate at askroundtable.ai.
I'll be in the comments all day. Would love to hear what would make you switch gateways, or what's kept you from using one at all.
RiteKit Company Logo API
@felix94123 One API key to hundreds of models, hosted in the EU and drop-in compatible with the SDKs teams already use — that's the combination that makes switching painless, and the European hosting is a real, specific reason to choose you over the default.
A gateway shows its value better in motion than in a description, and you launched without a demo video — so I made you one, free and whitelabel, no strings:
Yours to keep — download it from https://foxplug.com/v/ss-opper-launch-the-european-ai-d289407f and put it on your own channel or launch page. Launches with a video do better, and yours is still editable.
Made at https://foxplug.com/?utm_source=producthunt&utm_medium=comment — make more there, or record your own product tour in ~2 minutes. Anyone else launching soon: paste your site, video in about 30 seconds. Nice work.
Opper AI
@saulfleischman cool 😎
how do the spend caps behave mid-chain when an agent calls several models back to back - does it fail gracefully or need pre-checking before each call?
Opper AI
@ulykbek11 Spend caps are enforced once per request, at the gateway on the way in, not per model call. So when an agent chains several models back-to-back (or falls back primary→fallback₁→fallback₂), the cap is checked once up front and never re-checked between calls. You don't need to pre-check before each call, and nothing gets killed mid-chain: if you're over a cap, the next request gets a clean 402 before any model runs. Two things worth knowing:
Metering is eventually-consistent (spend is debited after each call and batched before it hits the ledger), so a long chain or a parallel burst can overshoot the cap slightly before the block kicks in on the following request. For "stop runaway spend" that's exactly what you want; if you need a hard per-call ceiling, gate on balance yourself between calls.
Failed fallback hops are free — you only pay for the model that actually delivers tokens, not the ones that erred and fell over. And if you're already over the cap before the call, you never reach the fallback at all; you get the 402 up front.
@ulykbek11 @felix94123 that eventually-consistent metering answer is a lot more honest than most gateways would give, "gate on balance yourself if you need a hard ceiling" is a real caveat, not marketing. separate question given the EU-residency pitch: does the metering/billing pipeline itself (the batched spend ledger, not the prompts) ever transit outside the EU, or is that boundary held for billing metadata too
Congrats on the launch! The EU-hosted angle is smart, that's usually an afterthought for most teams. Does it route to EU inference automatically, or do you choose that per request?
Opper AI
Thanks @irahimiam! You can either set it as a fixed rule in your route settings or choose EU as a region when setting the model in the platform. You can also filter in our public model list and copy the API ID directly: https://opper.ai/models?region=EU
Congratulations on the launch! I'm new to gateways and have questions about the setup. First, how does my data stay in the EU if a request goes to a US-hosted model like Claude or GPT? Or the EU residency is only for the models you host in Europe? And second, if I mostly use one EU model, what does routing give me over just calling that model directly? Thank you!
Opper AI
Thanks@alieksia ! For your data to stay fully within the EU, you have to choose a model with EU hosting availability. We offer this out of the box for almost all models, even for leading ones like Claude Opus 4.8 with several providers, so you can even have a fallback. Fallbacks is also why you would want a router, imagine you use Claude Opus 4.8 on AWS Bedrock and they have an outage, then your app / access is also down. By choosing another provider, e.g. Azure as a fallback, you ensure that you have continued access to Opus 4.8. And outages / ratelimits have been very common in the past. There are many more reasons, like having the ability to switch to other models for specific tasks so you don't pay $$ premium opus tokens for a basic task that 10x cheaper open-source models can easily handle.
@felix94123 Thank you for the answer, now it's clear to me.
Opper AI
@alieksia glad to hear!
Very cool. So basically Opper can guarantee that my data never leaves the EU if I use models hosted in the EU?
Opper AI
Thanks @tom_dickson1 and yes that's exactly right. You can even set this as a fixed routing rule so you or anyone in your team can't switch the region by accident. Happens more than one would think :)
@felix94123 nice! I have been using Evroc and Nebius for EU sovereign tokens but they are flaky. All of a sudden Nebius API for some model returns error codes. So it makes sense to aggregate these token providers which has far worse API uptime then what we are used to with AWS/GCP etc. They are also slow with getting the latest Kimi models. Evroc is always 3 months behind on the latest Kimi releases it feels like.
Opper AI
@tom_dickson1 yea having fallbacks even for sovereign hosted models is still crucial, we have 15+ EU hosting providers so you can have multiple fall back options on the same model, still in the EU not risking any downtime if one provider has an outage. And out of all these, one will be the first to add the latest model, which you then have immediate access to, instead of waiting.
No mention of latency added by routing through Opper vs calling direct.
Opper AI
@cody_spencer good question, we wrote an article about that, and routers do not inherently add latency: https://opper.ai/blog/llm-router-latency-benchmark-2026
the single EU sub-processor covering everything is the detail that actually matters for GDPR compliance. most AI gateway solutions technically run in Europe but still have US-based sub-processors in the chain, which creates the same data transfer headache you were trying to avoid. the drop-in compatibility with existing SDKs is smart too, switching costs are the main reason teams stay on non-compliant infrastructure longer than they should. curious how latency compares to going direct to anthropic or openai for european users?