Features

A complete RAG platform,
end to end.

Veldora handles every layer of grounded AI — from crawling your site to streaming answers — so your team can focus on customers, not infrastructure.

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Features

Everything you need to ship AI
grounded in your own data.

A complete RAG platform — scraping, embeddings, vector search, analytics, and embeds — wired together so you can focus on customers, not infrastructure.

Trained on your website

We crawl every page, doc, and FAQ — your chatbot only answers from your own content. No hallucinations from generic AI.

Smart RAG chatbot

Retrieval-augmented generation pipeline that grounds every reply in real chunks from your knowledge base.

Lightning-fast scraping

Distributed workers handle thousands of pages, sitemaps, and SPAs — JS-rendered or not. Always up to date.

Semantic vector search

Embeddings + vector DB find meaning, not just keywords. “Refund policy?” matches “money-back terms.”

Multi-step pipelines

Scrape → clean → chunk → embed → index. Every step versioned, observable, and reproducible.

Realtime analytics

See conversations, top questions, deflection rate, lead intent, and where your AI needs more training.

Multi-tenant isolation

Every customer’s data, embeddings, and chat history are fully isolated. Enterprise-grade by default.

One-line embed

Drop a single script tag on your site and the AI assistant appears — instantly themed, instantly trained.

Always-learning AI

Re-train on demand or on schedule. Push new docs, blog posts, or pricing — your chatbot updates itself.

The Veldora RAG pipeline

Each step is observable, versioned, and tenant-isolated. Re-run any stage independently — no full re-trains.

Step 01

Crawl

Headless browser workers extract every page, even JS-rendered SPAs.

Step 02

Clean

Strip nav, ads, scripts. Normalize to readable text + metadata.

Step 03

Chunk

Recursive splitting tuned for retrieval, with overlap & headings preserved.

Step 04

Embed

Premium embedding models, batched for cost & latency.

Step 05

Index

Tenant-isolated vector store with hybrid (semantic + keyword) search.

Step 06

Serve

Low-latency chat API, embeddable widget, and SSR-friendly streaming.

Multi-tenant by design

Enterprise-grade isolation, on day one.

Every customer’s pages, embeddings, conversations, and API keys live under tenant-scoped keys. Vector queries can never cross-contaminate. Encryption in transit and at rest. Audit-ready from the first deploy.

Per-tenant vector namespaces & API keys
Row-level isolation in Postgres + object storage
SOC 2-ready controls; DPA available on Enterprise
Bring-your-own LLM and vector backend

tenant-isolation.ts

// every query is automatically scoped to the tenant
const results = await veldora.search({
  tenantId: ctx.tenant.id,         // <- enforced server-side
  query: "what is your refund policy?",
  topK: 5,
  hybrid: true,
});

// chat completion is grounded ONLY in this tenant's chunks
const reply = await veldora.chat.complete({
  tenantId: ctx.tenant.id,
  messages,
  retrieval: results,
});

Ship AI in minutes, not months

Turn your website into your smartest team member.

Start free. Train an AI assistant on your real content. Deploy a grounded, on-brand chatbot to your customers today.