We buildreliableAI systems.
We bring years of experience to projects across many fields, from e-commerce to transport.
- Language models
- Machine learning
- Data infrastructure
- End-to-end delivery
What we do
We put AI into systems that run.
Choosing or training a model is the easy part. The hard part is a system that answers under load, can be measured, and that an organisation can run on its own infrastructure.
- 01
Language models and beyond
Large language models, retrieval, ranking and evaluation. We build whatever a problem actually needs rather than committing to one approach.
- 02
The whole system, not a piece of it
From the data to the model, from the service to the monitoring, we build the whole system. It is hard to be accountable for a system you own only part of.
- 03
Data a model can use
Real data is messy. Preparing, verifying and mapping it is not a precondition for the work — it is the work.
Who we are
The people who build the models build the product.
Bluespring is not an agency and not an integrator. The same team builds the model, the service around it and the data work underneath. That is why, when a system gets an unexpected input wrong, we can tell you what went wrong and why.
We work close to the teams who know the domain, and we judge the result on your own data and your own conditions rather than on an off-the-shelf benchmark.
Our product
The same work, as a product.
Retail search is the domain we have gone deepest into. Smart Search is the product of that work.
Smart Search
An AI search engine for online retailers
It understands the sentence a customer types into your search box, ranks products by how well they answer the request, and asks the one question that narrows the list.
Explore Smart Search- Understands the request as written, typos and all.
- Ranks by how well each product fits, not by how the name matches.
- Explains the differences and asks the question that narrows the list.
Contact
Tell us what you want tobuild.
Write in with the problem you are working on. We will work out what is possible and how the result should be measured.