Why event search needs to be smarter than keyword matching
Search for "keynote speaker AV requirements" in most event platforms and you'll get one of two results: a list of items that contain those exact words, or nothing at all. If the document you need says "audio visual setup for plenary presenters" instead, you're out of luck. The information exists. The search just can't find it.
This is keyword search. It matches strings of text, not meaning. For a platform managing hundreds of sessions, dozens of exhibitors, and thousands of documents, that's not good enough.
How keyword search fails event teams
Events generate a lot of content across a lot of categories. Session descriptions, exhibitor profiles, speaker bios, floor plan notes, compliance documents, knowledge base articles, internal communications. Different people write these at different times using different terminology.
Your venue team writes "AV requirements." Your production team writes "technical rider." Your speaker coordinator writes "presentation setup needs." They all mean the same thing, but keyword search treats them as completely unrelated.
The result is that people stop trusting search. They learn to navigate manually, clicking through menus and folders, or they ask a colleague who might remember where something is. Search becomes a feature that technically exists but nobody relies on.
What hybrid search does differently
ema uses a combination of semantic search and keyword search across all 13 entity types in the platform. Here's what that means in practice.
Semantic search understands intent. When you search for "audio visual setup," semantic search also surfaces results about "AV requirements," "technical specifications," and "presentation equipment." It understands that these concepts are related, even though the words are different. This is done through vector embeddings — the search engine converts your query and the content into mathematical representations of meaning, then finds the closest matches.
Keyword search handles precision. When you search for a specific exhibitor name, a session code like "CONF-2026-047," or a particular document title, you want exact matches. Keyword search delivers that. Semantic search alone might return conceptually similar but wrong results for precise terms.
The combination covers both cases. You get results that match what you meant (semantic) and results that match what you typed (keyword), ranked by relevance. The system doesn't force you to think about which mode you need — it runs both and gives you the best results from each.
This works across everything
The search isn't limited to one type of content. It spans documents, knowledge base articles, programme sessions, exhibitor records, speaker profiles, communications, tasks, and every other entity in the platform. A single search can surface a relevant document, a related session description, and an exhibitor note — all from the same query.
For events with complex programmes, this matters. A conference with 200 sessions, 80 exhibitors, and a knowledge base full of attendee-facing articles has thousands of searchable items. The difference between finding what you need in three seconds and not finding it at all is the difference between a productive workflow and a frustrating one.
The AI agent uses the same search
When you ask ema's AI agent a question — "What are the AV requirements for the main stage on day two?" — it's using the same hybrid search under the hood. The agent searches across all entity types, finds the relevant records, and gives you an answer with context.
This means the agent is only as good as the search. If the search were keyword-only, the agent would miss relevant information that uses different terminology. Because it's semantic, the agent can find what you're asking about even when the stored data uses different words than your question.
Why this isn't a luxury feature
For small events with a handful of sessions and a few documents, basic search is fine. You can find things manually because there isn't much to search through.
But events scale. A multi-day conference with parallel tracks, an exhibition hall, a full knowledge base, and months of planning documents accumulates a serious amount of information. At that scale, search quality directly affects how quickly your team can work.
Finding what you meant, not just what you typed — that's what event search should do. Keyword matching alone stopped being adequate the moment event platforms started managing more than a calendar and a registration list.