Vectara
Product Capabilities
Agentic RAG platform
As of September 3, 2026, Vectara's features: 26 stated capabilities anchor on agentic RAG, hybrid search, and MCP, with 4 integrations and 4 supported models. That breadth covers the core enterprise RAG stack, but buyers should verify which capabilities are available per deployment type before the sales call.
Backed by 31 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
Agentic RAGAir GappedAPIBring Your Own ModelBYOCBYOMCitationsCustom InstructionsFactual Consistency ScoreFactual Consistency ScoringHallucination CorrectionHallucination DetectionHybrid SearchMCP SupportModel AgnosticMulti Modal IngestMultilingualMultimodal IndexingObservabilityOn PremisesRAGRerankingSAASSelf HostedStructured OutputZero Shot Learning
Integrations
AnthropicGoogle GeminiHugging FaceOpenAI
Details
Model count4
Features Change Historydated events · values unlock with a key
Feature added: API
Feature added: Anthropic
Feature added: Google Gemini
Feature added: Model Agnostic
Feature added: Multi Modal Ingest
Feature added: Multilingual
Feature removed: Agent Tool Validation · high significance
Feature removed: AI Agents · high significance
Every features fact on this pagekey · value · provenance · dated · sourced
| Fact | Value | Provenance | As of | Source |
|---|---|---|---|---|
| features.agentic-rag | Agentic RAG | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.air-gapped | Air Gapped | company stated | 2026-09-03 | www.vectara.com/business/platform/why-vectara |
| features.api | API | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.bring-your-own-model | Bring Your Own Model | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.byoc | BYOC | company stated | 2026-08-31 | www.vectara.com/pricing |
| features.byom | BYOM | company stated | 2026-08-31 | www.vectara.com/pricing |
| features.citations | Citations | company stated | 2026-09-03 | www.vectara.com/business/platform/why-vectara |
| features.custom-instructions | Custom Instructions | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.factual-consistency-score | Factual Consistency Score | company stated | 2026-09-03 | www.vectara.com/business/platform/models |
| features.factual-consistency-scoring | Factual Consistency Scoring | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.hallucination-correction | Hallucination Correction | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.hallucination-detection | Hallucination Detection | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.hybrid-search | Hybrid Search | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.integration.anthropic | Anthropic | company stated | 2026-08-31 | www.vectara.com/pricing |
| features.integration.google-gemini | Google Gemini | company stated | 2026-08-31 | www.vectara.com/pricing |
| features.integration.hugging-face | Hugging Face | company stated | 2026-09-03 | www.vectara.com/business/platform/models |
| features.integration.openai | OpenAI | company stated | 2026-08-31 | www.vectara.com/pricing |
| features.mcp-support | MCP Support | company stated | 2026-09-03 | www.vectara.com/business/platform/why-vectara |
| features.model_count | 4 | company stated | 2026-09-03 | www.vectara.com/business/platform/models |
| features.model-agnostic | Model Agnostic | company stated | 2026-09-03 | www.vectara.com/business/platform/why-vectara |
| features.multi-modal-ingest | Multi Modal Ingest | company stated | 2026-09-03 | www.vectara.com/business/platform/why-vectara |
| features.multilingual | Multilingual | company stated | 2026-09-03 | www.vectara.com/business/platform/models |
| features.multimodal-indexing | Multimodal Indexing | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.observability | Observability | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.on-premises | On Premises | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.rag | RAG | company stated | 2026-09-03 | www.vectara.com/business/platform/models |
| features.reranking | Reranking | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.saas | SAAS | company stated | 2026-09-03 | www.vectara.com/business/platform |
| features.self-hosted | Self Hosted | company stated | 2026-08-31 | www.vectara.com/pricing |
| features.structured-output | Structured Output | company stated | 2026-09-03 | www.vectara.com/business/platform/models |
| features.zero-shot-learning | Zero Shot Learning | company stated | 2026-09-03 | www.vectara.com/business/platform/models |
Features across Vector DatabasesVectara 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 this record | 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 | 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 vectara.com via API / MCPevery field dated and sourced
RESTopen tier
GET https://api.bixel.com/v1/companies/vectara.com/facts?dimension=features
{
"data": {
"facts": [
{
"key": "features.agentic-rag",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-03",
"source_url": "www.vectara.com/business/platform"
},
{
"key": "features.air-gapped",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-03",
"source_url": "www.vectara.com/business/platform/why-vectara"
},
{
"key": "features.api",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-03",
"source_url": "www.vectara.com/business/platform"
},
{
"key": "features.bring-your-own-model",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-03",
"source_url": "www.vectara.com/business/platform"
},
"…"
]
}
}MCPfor agents
# any MCP client (Claude, agents)
const record = await bixel.get_company_facts({ domain: "vectara.com", 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.