Millions of AI requests. Zero rate‑limit failures.
A distributed infrastructure layer that sits in front of OpenAI, Anthropic and Vertex AI, queuing, routing and recovering every chatbot request for a telecom platform serving more than 80 million users.
- 100% of 429 errors eliminated: no more requests lost to provider rate limits.
- Sub-100ms response times: requests handled in the region closest to each user.
- Three providers, one layer: AI models treated as interchangeable resources.
Meet our client
- Client
- Telecommunications provider
- Industry
- Telecommunications
- Market
- Global
In a nutshell
The client's AI chatbot lets more than 80 million users reach its services by voice, chat and image. It was built for experimentation, then adoption exploded: rate-limit errors, failed requests, slow answers outside one region, and no clear view of what was going wrong. We built the layer that manages every request before it reaches a model provider: a global queue, intelligent routing across providers, multi-region deployment, full tracing, and recovery when anything fails.
Built for experiments, hit by 80 million users
Every provider caps how many requests it accepts. With no layer to manage traffic, anything over the cap came back as an HTTP 429 error, and the user got nothing. Push the traffic up and compare.
Illustrative traffic and limits. One provider, one region, no queue.
- Rate-limit failures: traffic above a provider's limit failed outright.
- No routing: requests could not move to another provider when one was full.
- One region: users elsewhere in the world waited longer for every answer.
- Flying blind: engineers had little insight into where requests failed.
- Spikes broke things: sudden surges made the whole system unstable.
- A ceiling on growth: the platform could not scale to enterprise usage.
Spikes are absorbed, not passed on
A distributed queue regulates incoming traffic. When a surge arrives, requests wait for milliseconds instead of failing, important requests go first, and temporary failures are retried. Send a spike and watch.
Every request goes to the best provider right now
The router weighs availability, latency and cost for every request. When a provider nears its limit or goes down, traffic moves automatically. Change what matters most, or break a provider yourself.
Served close to every user
The platform used to run in one region, so everyone else waited. Now requests are processed in the region nearest the user, with failover between regions. Switch the deployment, or take a region offline.
Every request, traced end to end
Monitoring, logging and distributed tracing show how each request moves across providers and regions. When something fails, the trace shows the recovery too. Compare a normal request with one that hit a rate limit.
One layer between users and every model
Requests arrive through API gateways and load balancers, wait in the global queue, and are routed to the right provider and region, with every step monitored. Tap a component, or trace a request.
Three providers, three sets of rules
Tens of millions of users, providers with different limits and behaviour, a global audience and zero tolerance for dropped requests. Flip each card from the challenge to how we solved it.
From unstable chatbot to production platform
Following deployment, the platform reliably processes millions of AI-powered interactions every month across voice, chat and image, with low latency and high availability across regions.
Scale your AI. Not your failures.
Infrastructure that keeps every AI request answered, whatever the model, the region or the traffic spike.
- 01Your business objective
- 02The technical context
- 03The right next step