Built-in Hybrid Search for AI-Native Apps
Elastic and semantic search, developer-controlled relevance, permission-aware results, and MCP-enabled discovery — built directly into Kosmera.
Search is no longer just a convenience feature. In modern enterprise applications, search becomes part of how users and AI agents understand, discover, and act on data.
Users expect fast keyword search.
AI agents need semantic discovery.
Both must respect the same permission boundaries.
Kosmera solves this with built-in Hybrid Search: combining lexical and semantic retrieval inside the platform itself, rather than treating search as an external add-on.
Why hybrid search matters
Keyword search is good at exact matches. Semantic search is good at meaning. Real enterprise applications need both. Relying on only one creates a weak retrieval layer: either precise but shallow, or intelligent but inconsistent.
Lexical search
PrecisionIdeal for exact values, known identifiers, codes, names, and explicit filters.
It answers: “Does this text match what I typed?”
Semantic search
MeaningIdeal for natural language, fuzzy intent, related concepts, and AI-driven lookup.
It answers: “Does this result mean what I’m looking for?”
Kosmera combines both approaches so search is not forced to choose between exactness and understanding.
Built in for entities and documents
For each searchable entity or document, Kosmera enables both elastic search and semantic search as part of the platform capability.
What Kosmera handles
- indexing searchable content
- creating summary fields for retrieval
- enabling vector-based semantic lookup
- combining multiple ranking signals
What developers avoid
- building search infrastructure from scratch
- duplicating search logic across modules
- manually wiring AI retrieval paths
- reimplementing access control in search
Developer-controlled relevance
Strong defaults are useful, but enterprise relevance is rarely generic. Search quality depends on how the platform represents business data and how it ranks results.
Summary field control
RepresentationDevelopers can influence how the summary field is built for each entity or document.
That means search can reflect business meaning instead of just raw storage shape.
Ranking control
RelevanceDevelopers can also influence ranking, allowing the application to prioritize what matters most.
That may include domain-specific importance, freshness, semantic similarity, or custom weighting.
This is an important distinction: Kosmera owns the search capability, but the app developer still shapes relevance.
Search stays inside the permission model
Search results are still subject to the system permission model. A user — or an AI agent — will not receive entities they are not allowed to see.
User-safe
Search never becomes a backdoor into restricted data.
AI-safe
AI agents operate under the same visibility rules as users.
Tenant-safe
Retrieval respects tenant and application boundaries by design.
That sounds obvious, but many search systems treat permissions as a secondary filtering step. Kosmera treats them as part of the retrieval contract itself.
Automatically available through MCP
Kosmera automatically enables an MCP server for search. This means search is not only available to your UI — it is also available to AI agents as a native tool.
Search becomes part of the runtime interface for both humans and agents.
The same retrieval capability can power assistant workflows, semantic lookup, grounded responses, and agentic actions — without a separate integration track.
What this gives your application
Better discovery
Users and agents can find entities and documents by both exact matches and conceptual meaning.
Business-aware relevance
Developers shape summaries and ranking so search aligns with domain priorities.
Consistent security
Search respects the same permission boundaries across users, agents, and tenants.
AI-ready retrieval
MCP exposure makes search immediately usable in copilots, assistants, and automated workflows.
The result
With Kosmera, hybrid search is not an external subsystem you bolt on later. It is a built-in platform feature designed for enterprise software and AI-native workflows.
That gives you a better tradeoff:
smarter retrieval, safer access, and less infrastructure to build.
Fast search for users. Semantic discovery for AI. One permission model for both.
That’s the Kosmera approach to search.