VectorAmp Docs

Your knowledge. Cited answers.

Build with filter-native vector search and intelligence. Connect your sources, retrieve the right context, and deliver answers your users can trace back to the evidence.

Build your first search →Explore the API

01 Connect sources→02 Search with filters→03 Get cited answers

Start fast

Create your first dataset, add content, and run a cited search.

• Introduction
• Quickstart
• Production readiness checklist

Build with Intelligence

Use implementation guides for governed knowledge search, grounded answers, analysis, compliance assistants, RFP workflows, support escalation, and agent access.

• Guides overview
• Company knowledge with citations
• REST API cited search backend

Operate the platform

Manage datasets, ingestion, embeddings, organizations, and API keys from the dashboard.

• Application overview
• Datasets
• Pipelines
• API Keys

Integrate from code

Call VectorAmp from your backend, SDK, CLI automation, LangChain app, or MCP-compatible agent.

• Client libraries
• CLI
• Python SDK
• JavaScript SDK
• API Reference

What VectorAmp is optimized for

Capability	Where to go
Filter-aware vector retrieval for tenant, role, source, and document boundaries	Vector indexes, tenant-scoped search
Cited answers grounded in approved sources	Company knowledge with citations, Intelligence API
Ingestion workflows for files and source systems	Pipelines, CLI ingestion guide
Hybrid search when exact terms and semantic meaning both matter	Hybrid search guide, search comparison
Agent knowledge access without handing agents unrestricted data	MCP guide, enterprise agents guide