Gateways to language models
A single entry point for every service in the company: routing by task, failover between providers, rate limits and spend accounting.
02 / DEV
AI systems development and rollout
We build systems that survive a provider outage, a load spike and a model change. Monitoring ships with the release, and every change has a rollback plan.
The difference between a demo and a working system is what happens when something breaks. A provider hits its rate limit, a model returns garbage, a service goes down. At that moment the demo shows an error; the working system fails over and continues.
We build the second kind from the start, because we operate what we build, and nobody wants to be woken at night by their own mistakes.
Search over your own documents
A vector database and a model answer questions from your own materials: procedures, knowledge base, correspondence, documentation. On your hardware if the data must stay inside.
Agents and automation
Systems that carry out multi-step tasks: collect data, prepare drafts, watch the state of things and report what matters.
Integrations
We connect AI to what already works: CRM, ad platforms, databases, messengers, internal services.
What this is based on
Our own gateway serves several products at once. When a provider refuses on a rate limit or returns a server error, the request goes to the next one in the list, and the failing provider is excluded for a while so it does not drag the rest down. Local models on our own hardware sit at the end of the chain as a free reserve. The user never sees the failure.
What you get
- A running system with metrics, logs and alerts
- A rollback plan for every change
- Documentation that lets another team take the system over
- A predictable cost of operation
When it is not needed
- If you need one-off text generation, a subscription service is enough
- If nobody will be there to maintain the system, we will suggest something simpler
If the task is not for us, we say so in the first conversation and, where we can, point you to someone who fits.
Questions we get asked
What happens when the model provider is unavailable?
The request goes to the next provider in the list. The failing one is excluded for a while and then checked again. Local models sit at the end of the chain, so a complete failure would mean your own server is down.
Does our data go to external providers?
Only if you want it to. Where confidentiality matters more than the last few percent of quality, we run models on your hardware and the data never leaves your network.
Who maintains the system after rollout?
We can, or you can. In the second case we leave documentation and hand over the knowledge: how it is deployed, what breaks most often, what to do when it fails.
How do we know the system is working correctly?
From the metrics that ship with it. A system whose outage you learn about from a customer counts as broken.
Other services
01 / DESIGN AI Design We work out the economics before the first line of code. Half of the AI requests we see are solved simpler and cheaper, and that is best known at the start. Read more 03 / CONSULTING AI, Software & IT Consulting We work out why a deployed system is not delivering. Most often the model is fine and the problem sits in what gets measured, and where. The same discipline applies to software and IT decisions in general. Read more
Tell us about the task
We will look at where AI pays off and where it would cost more than it returns.