Services/Generative AI
AI-Powered Search
Search that understands intent, not only keywords, across large content libraries and product catalogues.
- 6 to 10 weeks
- Project-based
- Search engineers with a data engineer
- Large content libraries, catalogues, and knowledge bases
What we do
Semantic search, hybrid retrieval, and re-ranking for content libraries, knowledge bases, and product catalogues. We measure relevance on your real queries and tune until the results match what users meant.
What the work includes
Semantic matching
Embeddings that match meaning, so a query finds the right item even when the words differ from the catalogue.
Hybrid architecture
Vector search combined with keyword search for exact matches, product codes, and names.
Re-ranking and personalisation
Cross-encoder re-ranking and behavioural signals applied to the top results where they improve measured relevance.
Measured relevance
Click-through, zero-result queries, and judged relevance tracked over time, so tuning is evidence-led.
How an engagement runs
Scope, build, evaluate, operate.
The same four stages on every engagement, so you always know what happens next and what you will have at the end of it.
Scope
A short discovery with the people who own the problem. Output: a written scope, acceptance criteria, and a fixed estimate.
Build
A named lead and a team sized to the scope. Working software from the first weeks, demonstrated on a fixed cadence.
Evaluate
Every AI component is measured against real cases before rollout. The numbers decide when it goes live.
Operate
Deployment, monitoring, and a support window. Then a handover, or an ongoing team if you want one.
Typical stack
Tools we commonly use for this work. The final choice follows your requirements, region, and existing platform.
- Python
- Elasticsearch
- OpenSearch
- Weaviate
- Qdrant
- Redis
- LangChain
- OpenAI
- Cohere
Related use cases
Related services.
Agentic AI
Systems that take an objective, plan the steps, use tools, and complete multi-step work with minimal supervision.
Conversational AI
Assistants that hold context, answer from your knowledge, and hand off to a person at the right moment.
Enterprise RAG
Retrieval-augmented systems that answer questions from your documents and data, with citations and access control.
Search
Results that match what people meant
We tune search against your own query logs, not a benchmark, so the improvement shows up for your users.