Apple
Meta
NVIDIA
Amazon
TikTok
Reddit
Pinterest
DuckDuckGo
Indeed
DoorDash
Best Buy
Yelp
Elastic
OpenSearch
Qdrant
Depop
Kroger
BMW
AT&T
Zalando
Home DepotDeep coverage across the retrieval stack.
Query Understanding
Intent classification, semantic query parsing, disambiguation & entity resolution.
Vector & Hybrid Retrieval
Embeddings, ANN, quantization, sparse + dense fusion, multivector & multimodal search.
RAG & Agentic Search
Chunking, adaptive queries, agentic search loops, guardrails, retrieval for LLM consumers.
Search Platforms
Solr, OpenSearch, Elasticsearch, Vespa, Qdrant & modern vector search engines.
Knowledge Graphs
Semantic knowledge graphs, ontology mining, graph-powered relevance & reasoning.
Personalization & RecSys
Collaborative filtering, behavioral embeddings, real-time user modeling.
Signals & Reflected Intelligence
Click-stream models, signals boosting, self-learning relevance loops.
Learning to Rank
LambdaMART to cross-encoders, click models, feature engineering, bias correction.
Wormhole Vectors
We help you bridging sparse, dense, and behavioral vector spaces to significantly outperform your current vector or hybrid search systems.
Pseuo-relevance Feedback
Move beyond "ranking-only" search approaches followed by 95% of engineering teams and toward better content-based query understanding.
Local & Fine-tuned Search Models
Break your dependence on expensive and unreliable public APIs. We help you fine-tune, deploy, and run your own Language Models.
LLM as a Judge
Generate reliable relevance judgement training data at scale, leveraging best practices to balance and measure human, implicit, and LLM-based judgments.
Led by the expert who wrote the book on AI-powered search.
Trey Grainger
Trey is lead author of AI‑Powered Search (Manning) and co-author of Solr in Action. He previously served as CTO of Presearch, and as Chief Algorithms Officer & SVP Engineering at Lucidworks, where his teams powered search for hundreds of the world's leading organizations. He is also lead instructor of the industry's most popular live course on modern retrieval (on Maven), Adjunct Professor of Computer Science at Furman University, and a technical advisor at OpenSource Connections.
Founder · Searchkernel
AIPoweredSearch.com
Searchkernel doesn't just practice AI-powered search — we literally wrote the book on it and run the online community around it.
We built and maintain AIPoweredSearch.com, the industry's hub for modern retrieval; we authored AI‑Powered Search (Manning), the definitive guide with over 20,000 copies sold; and we host the AI‑Powered Search community, where over 1,200 search & AI practitioners share the latest techniques, research, and code.
Query intelligence: contextualize your data, domain, and users' intent
Searchkernel QIQ
Searchkernel QIQ (Query IQ) gives your search engine an IQ boost. It's a query intelligence layer that sits in front of any retrieval system — understanding what your users (and agents) actually mean before a single document is fetched.
- Intent classification & query-sense disambiguation
- Semantic query parsing, rewriting & enrichment
- Drops in ahead of Solr, OpenSearch, Elasticsearch, Vespa, or your vector DB
- Built for both human queries and agentic / RAG traffic
- Works with or without an LLM, so supports low-latency search requirements
Take search from "broken" to a strategic advantage.
Search Relevance Audits & Strategy
A rigorous, evidence-based assessment of your current search — and a prioritized roadmap to fix it.
- Relevance evaluation & measurement frameworks
- Query intent & failure-mode analysis
- Architecture & platform recommendations
AI-Powered Search Implementation
Hands-on engineering of modern retrieval, from hybrid search to production ranking models.
- Hybrid lexical + vector retrieval & reranking
- Learning to rank, click models & signals boosting
- Semantic knowledge graphs & personalization
RAG & Agentic Search Systems
Retrieval is the hardest part of RAG. We build the retrieval layer your AI systems deserve.
- RAG architecture, chunking & adaptive queries
- Agentic search loops & tool-using retrieval
- Evaluation: LLM-as-judge & interleaving
Training & Fractional Leadership
Level up your team — or borrow a search leader with two decades of scars and wins.
- Private team cohorts of the AI‑Powered Search course
- Custom workshops on your stack & data
- Advisory & fractional head-of-search engagements
From discovery to production.
Discover
We dig into your users, queries, content, and signals to understand what "relevant" means in your domain.
Diagnose
Measurement first: evaluation frameworks and failure analysis that turn "search feels bad" into a ranked backlog.
Design
An architecture matched to your stack and scale — not a rewrite for its own sake.
Deliver
Hands-on implementation alongside your engineers, so the expertise stays when the engagement ends.
Bring the industry's leading search course in-house.
Recent cohort sold out
AI‑Powered Search: Modern Retrieval for Humans & Agents
Private cohorts and custom workshops based on the popular live course taught by Trey Grainger and Doug Turnbull — tailored to your team's stack, data, and roadmap.