KDB.AI
Product Capabilities
Hybrid search platform
As of September 3, 2026, KDB.AI's features: 11 stated capabilities covering hybrid search and multi-tenancy give enterprise buyers a reasonable checklist, but one listed integration means most connection work lands on the buyer's engineering team.
Backed by 12 dated facts
Every value derives from a dated, sourced capture — open any fact for its source.
Every value derives from a dated, sourced capture — open any fact for its source.
Capabilities
ExplainabilityHybrid SearchMulti ModalMulti Source RetrievalMulti TenancyNatural Language InterfaceOn Disk IndexingReal Time SearchTemporal Similarity SearchTime SeriesVector Search
Integrations
Langchain
Features Change Historydated events · values unlock with a key
Feature removed: Metadata Filtering · high significance
Feature removed: RAG · high significance
Feature removed: Shape Based Matching · high significance
Feature removed: Sub Second Latency · high significance
Feature removed: Vector Indexing · high significance
Feature added: Explainability
Feature added: Hybrid Search
Feature added: Natural Language Interface
Every features fact on this pagekey · value · provenance · dated · sourced
| Fact | Value | Provenance | As of | Source |
|---|---|---|---|---|
| features.explainability | Explainability | company stated | 2026-09-03 | kdb.ai/solutions |
| features.hybrid-search | Hybrid Search | company stated | 2026-09-03 | kdb.ai/learning-hub |
| features.integration.langchain | Langchain | company stated | 2026-09-03 | kdb.ai/learning-hub |
| features.multi-modal | Multi Modal | company stated | 2026-09-03 | kdb.ai/learning-hub |
| features.multi-source-retrieval | Multi Source Retrieval | company stated | 2026-09-03 | kdb.ai/solutions |
| features.multi-tenancy | Multi Tenancy | company stated | 2026-09-03 | kdb.ai/legal/ |
| features.natural-language-interface | Natural Language Interface | company stated | 2026-09-03 | kdb.ai/solutions |
| features.on-disk-indexing | On Disk Indexing | company stated | 2026-09-03 | kdb.ai/learning-hub |
| features.real-time-search | Real Time Search | company stated | 2026-09-03 | kdb.ai/solutions |
| features.temporal-similarity-search | Temporal Similarity Search | company stated | 2026-09-03 | kdb.ai/learning-hub |
| features.time-series | Time Series | company stated | 2026-09-03 | kdb.ai/solutions |
| features.vector-search | Vector Search | company stated | 2026-09-03 | kdb.ai/solutions |
Features across Vector DatabasesKDB.AI ranked in place · tap through for each read
| Company | Features read | Facts |
|---|---|---|
| Zilliz | Hybrid search platform | 75 |
| Weaviate | Hybrid search platform | 35 |
| Chroma | Hybrid search platform | 34 |
| Qdrant | Focused feature set | 32 |
| Vectara | Agentic RAG platform | 31 |
| LanceDB | Hybrid search platform | 25 |
| Pinecone | Reranking platform | 23 |
| Activeloop | Focused feature set | 16 |
| Epsilla | Multi-tenancy platform | 14 |
| KDB.AI this record | Hybrid search platform | 12 |
| TopK | Hybrid search platform | 10 |
| Vespa | Hybrid search platform | 10 |
| Turbopuffer | Multi-tenancy platform | 9 |
No observed features facts yet for Marqo, Milvus and MyScale.
Get features for kdb.ai via API / MCPevery field dated and sourced
RESTopen tier
GET https://api.bixel.com/v1/companies/kdb.ai/facts?dimension=features
{
"data": {
"facts": [
{
"key": "features.explainability",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-03",
"source_url": "kdb.ai/solutions"
},
{
"key": "features.hybrid-search",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-03",
"source_url": "kdb.ai/learning-hub"
},
{
"key": "features.integration.langchain",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-03",
"source_url": "kdb.ai/learning-hub"
},
{
"key": "features.multi-modal",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-03",
"source_url": "kdb.ai/learning-hub"
},
"…"
]
}
}MCPfor agents
# any MCP client (Claude, agents)
const record = await bixel.get_company_facts({ domain: "kdb.ai", dimension: "features" })
# returns the features record above,
# each value with its source_url + as_of,
# ready to reason overBuild on the company record. One key, REST + MCP, every signal dated and sourced back to the page it came from.
Public record, read from companies' own pages and boards. Every fact dated and sourced; provenance (observed vs company stated) shown inline.