Activeloop
Product Capabilities
Focused feature set
As of August 1, 2026, Activeloop's features: 14 capabilities and 2 integrations is a tight footprint: buyers get a focused vector database core, but any workflow beyond those 2 integrations requires custom connectors built in-house.
Backed by 16 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
Data VersioningData VisualizationDeep MemoryFine Tuning SupportMulti CloudMulti ModalNatural Language QueryOn PremisesQueryRetrieval AugmentationServerlessStreamingTensor Query LanguageVector Storage
Integrations
GcsS3
Features Change Historydated events · values unlock with a key
Feature removed: VPC Deployment · high significance
Feature removed: Multi Modal · high significance
Feature removed: Fine Tuning · high significance
Feature removed: GCP · high significance
Feature removed: S3 · high significance
Feature removed: Slack · high significance
Feature removed: Model Training · high significance
Feature removed: Petabyte Scale · high significance
Every features fact on this pagekey · value · provenance · dated · sourced
Features across Vector DatabasesActiveloop 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 | Multimodal platform | 31 |
| LanceDB | Hybrid search platform | 25 |
| Pinecone | Reranking platform | 23 |
| Activeloop this record | Focused feature set | 16 |
| Epsilla | RAG platform | 14 |
| KDB.AI | Multi-tenancy platform | 12 |
| TopK | Hybrid search platform | 10 |
| Vespa | RAG platform | 10 |
| Turbopuffer | Multi-tenancy platform | 9 |
No observed features facts yet for Marqo, Milvus and MyScale.
Get features for activeloop.ai via API / MCPevery field dated and sourced
RESTopen tier
GET https://api.bixel.com/v1/companies/activeloop.ai/facts?dimension=features
{
"data": {
"facts": [
{
"key": "features.data-versioning",
"value": true,
"provenance": "company_stated",
"as_of": "2026-08-01",
"source_url": "www.activeloop.ai/resources/the-future-of-ai-data-we-raised-series-a-to-bring-the-database-for-ai-to-fortune-500/"
},
{
"key": "features.data-visualization",
"value": true,
"provenance": "company_stated",
"as_of": "2026-08-01",
"source_url": "www.activeloop.ai/resources/the-future-of-ai-data-we-raised-series-a-to-bring-the-database-for-ai-to-fortune-500/"
},
{
"key": "features.deep-memory",
"value": true,
"provenance": "company_stated",
"as_of": "2026-08-01",
"source_url": "www.activeloop.ai/resources/the-future-of-ai-data-we-raised-series-a-to-bring-the-database-for-ai-to-fortune-500/"
},
{
"key": "features.fine-tuning-support",
"value": true,
"provenance": "company_stated",
"as_of": "2026-08-01",
"source_url": "www.activeloop.ai/resources/the-future-of-ai-data-we-raised-series-a-to-bring-the-database-for-ai-to-fortune-500/"
},
"…"
]
}
}MCPfor agents
# any MCP client (Claude, agents)
const record = await bixel.get_company_facts({ domain: "activeloop.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.