Vectara
Product Capabilities
Agentic RAG platform
As of October 19, 2026, Vectara's features: 25 stated capabilities incl. agentic RAG, hybrid search, and multimodal +2 more, 4 integrations, 4 models.
Backed by 30 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 RAGAPIBring Your Own ModelBYOCBYOMCitationsCustom InstructionsData RetentionFactual Consistency ScoreFactual Consistency ScoringHallucination CorrectionHallucination DetectionHybrid SearchMulti ModalMultilingualMultimodal IndexingObservabilityOn PremisesRAGRerankingSAASSelf HostedServerlessStructured OutputZero Shot Learning
Integrations
AnthropicGoogle GeminiHugging FaceOpenAI
Details
Model count4
Features Change Historydated events · values unlock with a key
Feature added: Multi Modal
Feature added: Serverless
Feature removed: Air Gapped
Feature removed: MCP Support
Feature added: Data Retention
Feature removed: Multi Modal Ingestion · high significance
Feature removed: Model Agnostic
Feature added: Multi Modal Ingestion
Every features fact on this pagekey · value · provenance · dated · sourced
| Fact | Value | Provenance | As of | Source |
|---|---|---|---|---|
| features.agentic-rag | Agentic RAG | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.api | API | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.bring-your-own-model | Bring Your Own Model | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.byoc | BYOC | company stated | 2026-09-24 | www.vectara.com/pricing |
| features.byom | BYOM | company stated | 2026-09-24 | www.vectara.com/pricing |
| features.citations | Citations | company stated | 2026-10-19 | www.vectara.com/business/platform/vectara-for-evaluation |
| features.custom-instructions | Custom Instructions | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.data-retention | Data Retention | company stated | 2026-10-19 | www.vectara.com/business/platform/vectara-for-evaluation |
| features.factual-consistency-score | Factual Consistency Score | company stated | 2026-10-19 | www.vectara.com/business/platform/vectara-for-evaluation |
| features.factual-consistency-scoring | Factual Consistency Scoring | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.hallucination-correction | Hallucination Correction | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.hallucination-detection | Hallucination Detection | company stated | 2026-10-19 | www.vectara.com/business/platform/vectara-for-evaluation |
| features.hybrid-search | Hybrid Search | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.integration.anthropic | Anthropic | company stated | 2026-09-24 | www.vectara.com/pricing |
| features.integration.google-gemini | Google Gemini | company stated | 2026-09-24 | www.vectara.com/pricing |
| features.integration.hugging-face | Hugging Face | company stated | 2026-09-24 | www.vectara.com/business/platform/models |
| features.integration.openai | OpenAI | company stated | 2026-09-24 | www.vectara.com/pricing |
| features.model_count | 4 | company stated | 2026-09-24 | www.vectara.com/business/platform/models |
| features.multi-modal | Multi Modal | company stated | 2026-10-19 | www.vectara.com/business/platform/vectara-for-evaluation |
| features.multilingual | Multilingual | company stated | 2026-09-24 | www.vectara.com/business/platform/models |
| features.multimodal-indexing | Multimodal Indexing | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.observability | Observability | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.on-premises | On Premises | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.rag | RAG | company stated | 2026-10-19 | www.vectara.com/business/platform/vectara-for-evaluation |
| features.reranking | Reranking | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.saas | SAAS | company stated | 2026-09-24 | www.vectara.com/business/platform |
| features.self-hosted | Self Hosted | company stated | 2026-09-24 | www.vectara.com/pricing |
| features.serverless | Serverless | company stated | 2026-10-19 | www.vectara.com/business/platform/vectara-for-evaluation |
| features.structured-output | Structured Output | company stated | 2026-09-24 | www.vectara.com/business/platform/models |
| features.zero-shot-learning | Zero Shot Learning | company stated | 2026-09-24 | www.vectara.com/business/platform/models |
Features across Vector DatabasesVectara ranked in place · tap through for each read
No observed features facts yet for Marqo, Milvus and MyScale.
IdentityBixel ID · free forever
Operated by
No registered company joined yet. Would resolve with: a registry identifier for the entity; a legal page on the site naming the registered company.
Registry identifiers
None on record.
Published identifiers
- GitHub vectara · inferred
- LinkedIn vectara · inferred
- X vectara · inferred
- YouTube channel/UCoP_hcyjJRLQr0CV050bfMg · inferred
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": "2026-09-24",
"source_url": "www.vectara.com/business/platform"
},
{
"key": "features.api",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-24",
"source_url": "www.vectara.com/business/platform"
},
{
"key": "features.bring-your-own-model",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-24",
"source_url": "www.vectara.com/business/platform"
},
{
"key": "features.byoc",
"value": true,
"provenance": "company_stated",
"as_of": "2026-09-24",
"source_url": "www.vectara.com/pricing"
},
"…"
]
}
}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.