Create and Tune Search & AI Solutions
We know search, with decades of experience of a wide variety of platforms, architectures and search engines. Our engineers are leading experts and can design and build solutions fast and accurately, reducing business risk and taking advantage of the latest innovations in search and AI. We can review and tune your existing systems and empower your teams to constantly improve search quality, becoming proactive rather than just reactive.
The right technology for you
If your search engine is underperforming it’s tempting to consider migrating to a new platform. This may be the right choice if your engine is old or unsupported, but there are also risks when migrating to a new technology.
We know the landscape of search & AI technology, from open source solutions such as Apache Solr, Elasticsearch & OpenSearch, to vector databases like Weaviate, Qdrant or Vespa, to commercial engines like Vectara. We’re neutral and will help you choose a technology that fits your use case and business – and if we think you should stay with what you have, we’ll tell you!
If you do decide to migrate our measurement-focused approach helps you identify & mitigate the risks. We’ve even got a Playbook for this kind of project and have helped organisations large and small achieve success.
From architecture to implementation, prototype to production
We can support your team at all stages, from roadmapping, system design & architecture review to prototype and finally production implementation and tuning. With a deep understanding of how search should be built for performance, scalability and accuracy, we can make sure your search platform is future proof.
If you just need to add a feature like spelling correction, faceted search or auto-suggest, or are interested in adding AI capabilities like semantic search or Retrieval Augmented Generation, we can help you build it right first time.
Our team, recognised experts in search & AI engineering, includes committers to the Apache Solr project, authors of leading books about search, maintainers of the Elasticsearch Learning to Rank plugin (used by Wikipedia) and creators of leading search engine tools such as Querqy and Quepid. We contribute to many other open source projects, but we also work with closed source and commercial technologies. We’re trusted by many companies that sell search products to evaluate market fit and performance, create specialised training courses and guide their product roadmap.
Using the latest AI techniques to revolutionize information access
The world of search has been turned upside down by AI – and we’re ready to help you take advantage of these cutting-edge techniques. We’ve demonstrated how vector search can revolutionize e-commerce and talked about how to build pragmatic AI-powered search at the British Computer Society, winning Best Paper.
We’ve worked with leading AI startups to measure the effectiveness of their solutions and are developing AI applications using Retrieval Augmented Generation to reduce the risk of LLM hallucination.
Tuning search quality with continuous improvement
Our data-driven approach gives you a way to tune and improve how your search and AI systems deliver answers to your customers, based on real user interactions.
Starting with analyzing and improving your base algorithms, we can introduce a programme of continuous improvement using techniques such as Bayesian optimisation of field weights. An offline search lab lets you experiment with new search settings without affecting production – but once we find solutions that work, they can be A/B tested with real users.
We can also implement powerful Search Management features, training your customer-facing teams to use tools such as Querqy/SMUI to fix search issues in minutes by adding syonyms and boosts.
Get expert search & AI engineering help
Our team help you deliver solutions that work.