What we build, tune and hand over.

Sovereign Search (SEIR)

One search across the records of several organizations, while each one keeps its own data, decides who may see what and keeps its own audit log. Owner agents push only what the owner chooses, grants and clearance are applied before the search runs, and matching tolerates misspellings, other scripts and names that sound alike.

deliverable: a focused pilot over your own sources, with access policy and audit built in.

Enterprise search engine builds

Design and delivery of a high performance search platform over your own content: crawlers and source connectors, document indexing, analysis and language handling, permissions-aware retrieval, faceting, and the operational surface around it.

deliverable: a running search service, infrastructure as code, and runbooks.

Real-time indexing pipelines

Event-driven ingestion with change data capture, schema contracts, idempotent writes, replay and backpressure — so freshness becomes a number you can promise.

deliverable: a pipeline with replay, monitoring and documented failure modes.

Vector, semantic and RAG search

Chunking strategy, embedding choice, hybrid lexical-and-dense scoring, filtering, reranking, and honest measurement against a keyword baseline before anything ships.

deliverable: a retrieval layer plus the evaluation that justifies it.

Relevance tuning & evaluation

Judgement sets, offline evaluation harnesses, query-log analysis, ranking features and interleaving experiments. Ranking stops being a matter of taste.

deliverable: an evaluation pipeline and a prioritised relevance backlog.

Search analytics & observability

Instrumentation of query latency, zero-result and abandonment rates, click models and quality drift, surfaced in dashboards product people can read.

deliverable: dashboards, alerts and a weekly quality report.

LLM & AI product engineering

Retrieval-grounded assistants and internal copilots built on your corpus, with citation, caching, cost control and evaluation from the first commit.

deliverable: a production service with eval suite and cost model.

Architecture review & consulting

A short, direct read of an existing system: shard and capacity model, query patterns, index lifecycle, cost per query, and the two or three changes worth making first.

deliverable: a written review and a sequenced roadmap.

Training & team enablement

Hands-on workshops on Elasticsearch and Lucene internals, analysis, scoring, and operating clusters — taught against your own index rather than a toy dataset.

deliverable: workshop materials your team keeps, plus pairing weeks.

Migration off legacy search

Moving from an end-of-life or licence-bound engine — commonly between Elasticsearch and OpenSearch, or off Solr — with parity testing, dual-running and a cutover plan that does not gamble on a single weekend.

deliverable: parity report, dual-run period and cutover plan.