FastRouter is a unified AI gateway and control plane for developers and enterprise teams building with LLMs. It routes every request to the right model across 200+ LLMs through one OpenAI-compatible API, optimizing for cost, latency, quality, and reliability. With intelligent routing, failover, observability, and governance, teams can scale AI apps without vendor lock-in or code changes.
Hey Product Hunt! I’m RP, part of the team behind FastRouter.ai.
We built FastRouter because running AI in production meant too much plumbing and too much guesswork: multiple SDKs, scattered dashboards, fragile failover, and no clear answer to “How do we make this cheaper without making it worse?” when all the logs are scattered all over the place.
⚡ One integration. Less provider juggling.
FastRouter gives you a unified API across major models and providers, with support for OpenAI, Anthropic Messages, and Gemini-compatible interfaces.
Claude models, for example, are available through Anthropic, Amazon Bedrock, and Google Vertex AI. FastRouter routes requests to healthy upstreams, so you don’t have to maintain separate SDK integrations and failover logic yourself.
Routing is the starting point. Routing Intelligence is what makes FastRouter different.
Most gateways show you traffic and spending. FastRouter helps you figure out what to change:
Proactive cost insights: Weekly recommendations based on real traffic. Find cheaper models, prompt caching opportunities, and workloads suited to flex pricing. Model-switching recommendations include evals so you can compare quality before switching.
Early warning signs: Spot latency drift, error spikes, and cost anomalies, with alerts delivered to Slack or PagerDuty.
Request-level visibility: See which upstream served each request, allocate costs with tags, and inspect logs, including multimodal outputs.
Evals beyond text: Evaluate production traffic and datasets, including images and video. A successful API response doesn’t always mean a usable output.
Multimodal response caching: Reuse cached image and video responses for matching prompts or cache keys instead of calling the model again.
Better prompt management: Keep prompts in a shared, versioned library, with optimization and compression tools to improve them.
Our production customers are already saving $10K+ per month by acting on FastRouter’s recommendations.
Available as SaaS or fully on-prem, with budget caps, alerts, and access controls built in.
We built this to spend less time maintaining integrations and investigating bills, and more time shipping things that work.
The model zoo is getting ridiculous. Nice to have one gate instead of 200 separate keys and billing tabs. Congrats on the launch! @richie_fredicson@ritprasad@andrej_gamser2
Congrats on the launch, Ritesh, Andrej, and the FastRouter team. Insights is the part that goes past most gateways: weekly cards scoped to project, key, and model, with savings math and an eval before any model switch, and nothing auto-applied. If most traffic goes through a Virtual Model Alias rather than a bare model ID, do those recommendations still attach to the underlying providers, or can Insights suggest a change to the alias strategy itself?
Congrats @ritprasad on the PH launch. We have used Fastrouter; it's helped us to scale things with less hassle ..
How is it any different from OpenRouter? Any key differences you have implemented or plan to implement in the future?
Cost, latency and quality is three knobs where the third one does all the work and is the hardest to measure. We route across 30+ models in our own product and the thing that bit us wasn't a slow call or an expensive one, it was a small model returning something clean, confident and wrong, which passes every format check you have. So the number I'd want out of a control plane is cost per accepted output, not cost per call, because a model that's 4x cheaper and needs two regenerations just moved the bill somewhere nobody is measuring. If the quality signal behind routing is benchmarks rather than what your own users kept, it'll pick the cheap model at exactly the wrong moments.
Really like the failover functionality. If a provider becomes unavailable or throttles during the request process, how quickly is it done and is the streaming capability and tool calls maintained for all the models? Btw, Congratulations @ritprasad , @andrej_gamser2 and team FastRouter 🚀✌️
grouping retries under the original request is useful. if a stream fails halfway through, can failover continue it or does the user get a new response from scratch?
Routing across 200 plus models through one OpenAI compatible endpoint is the kind of thing teams only appreciate once they have written the same retry and fallback logic by hand. Optimizing for cost, latency and quality together is the interesting part, since those usually pull against each other. How transparent is the routing decision when you want to debug why a request went a certain way?
How quickly does it react when a model suddenly gets slower or starts giving weaker results?
am sending this straight to our engineering lead we desperately need something like this right now.
The first users usually seem to come from places where the problem is already being discusses. Curious if anyone has had better results from communities than from posting on their own profiles.
love the idea of a single endpoint for all 200+ models. makes testing new releases so much cleaner.
Can devs prioritise which criteria they want to optimise for: cost, latency, quality, and reliability at the routing layer?
really smooth execution. being able to set rate limits across multiple models in one place saves a lot of hassle.
Congrats on the launch. Can I set my own routing policies in settings on top of the default logic?
About FastRouter.ai on Product Hunt
“Route requests to the right LLM for cost, latency & quality”
FastRouter.ai launched on Product Hunt on October 5th, 2026 and earned 364 upvotes and 57 comments, earning #2 Product of the Day. FastRouter is a unified AI gateway and control plane for developers and enterprise teams building with LLMs. It routes every request to the right model across 200+ LLMs through one OpenAI-compatible API, optimizing for cost, latency, quality, and reliability. With intelligent routing, failover, observability, and governance, teams can scale AI apps without vendor lock-in or code changes.
FastRouter.ai was featured in API (98.8k followers), Developer Tools (521.6k followers) and Artificial Intelligence (481.7k followers) on Product Hunt. Together, these topics include over 232.9k products, making this a competitive space to launch in.
Who hunted FastRouter.ai?
FastRouter.ai was hunted by Rohan Chaubey. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how FastRouter.ai stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rohan Chaubey
Hey Product Hunt! I’m RP, part of the team behind FastRouter.ai.
We built FastRouter because running AI in production meant too much plumbing and too much guesswork: multiple SDKs, scattered dashboards, fragile failover, and no clear answer to “How do we make this cheaper without making it worse?” when all the logs are scattered all over the place.
⚡ One integration. Less provider juggling.
FastRouter gives you a unified API across major models and providers, with support for OpenAI, Anthropic Messages, and Gemini-compatible interfaces.
Claude models, for example, are available through Anthropic, Amazon Bedrock, and Google Vertex AI. FastRouter routes requests to healthy upstreams, so you don’t have to maintain separate SDK integrations and failover logic yourself.
Routing is the starting point. Routing Intelligence is what makes FastRouter different.
Most gateways show you traffic and spending. FastRouter helps you figure out what to change:
Proactive cost insights: Weekly recommendations based on real traffic. Find cheaper models, prompt caching opportunities, and workloads suited to flex pricing. Model-switching recommendations include evals so you can compare quality before switching.
Early warning signs: Spot latency drift, error spikes, and cost anomalies, with alerts delivered to Slack or PagerDuty.
Request-level visibility: See which upstream served each request, allocate costs with tags, and inspect logs, including multimodal outputs.
Evals beyond text: Evaluate production traffic and datasets, including images and video. A successful API response doesn’t always mean a usable output.
Multimodal response caching: Reuse cached image and video responses for matching prompts or cache keys instead of calling the model again.
Better prompt management: Keep prompts in a shared, versioned library, with optimization and compression tools to improve them.
Our production customers are already saving $10K+ per month by acting on FastRouter’s recommendations.
Available as SaaS or fully on-prem, with budget caps, alerts, and access controls built in.
We built this to spend less time maintaining integrations and investigating bills, and more time shipping things that work.
Claim 2 months free: https://fastrouter.ai/product-hunt
What’s your biggest AI production headache right now: reliability, cost, integrations, or quality? Let us know in your comments.