Governed enterprise RAG on your own AWS.
Your data never leaves your VPC.
Turn scattered knowledge into auditable answers with verifiable citations. True multi-tenant isolation. Privacy by design.
The problem
Your knowledge is scattered
PDFs, Notion, Drive, people's heads. New hires take months to absorb it.
You can't upload it to ChatGPT
Customer data, contracts, regulated information. Public SaaS is not an option.
You don't know where an answer came from
Without verifiable citations, every recommendation is a black box. Dangerous in critical contexts.
A complete, governed, enterprise-ready RAG platform
We don't sell a chatbot. We sell the full pipeline that turns your private documents into answers backed by evidence, audited and secure.
Secure ingestion
Upload PDFs, DOCX, Markdown, CSV, JSON. We parse, chunk with overlap, extract metadata, and generate vector embeddings with Amazon Titan. All inside your AWS VPC.
Retrieval with Row-Level Security
Semantic search over pgvector in Aurora PostgreSQL with multi-tenant isolation verified by automated tests. Metadata filters for your vertical (client, goal, date, constraints).
Answers with Claude via Bedrock
Claude Haiku 4.5 / Sonnet 4.6 / Opus 4.6 with automatic cost-aware routing. Guardrails against cross-tenant leaks, prompt injection, and evidence-free responses. Real-time streaming.
Verifiable citations
Every answer links to the exact chunk in the source document. Your team can click through and see where every statement came from — forensic auditability months later.
Governance and audit
Workspace-level RBAC, per-tenant policies, append-only audit log, per-query USD cost tracking, configurable retention, and GDPR export. Enterprise-ready.
Optional BYO-LLM
On Business+ you can plug in your own Anthropic or OpenAI credentials. rags.cc orchestrates the query, the cost runs on your account. Zero vendor lock-in.
✓Who it's for
- Fitness chains with proprietary methodology scattered across PDFs and staff heads
- Boutique law firms needing private internal search
- Consulting teams with per-client knowledge
- Education programs with large course materials
- Any company already on AWS with data that cannot leave its VPC
✕Who it's NOT for
- Individual users chatting with personal notes (use NotebookLM)
- Companies comfortable uploading data to ChatGPT Enterprise
- Teams not on AWS or unwilling to use it
- Cases where LLM creativity matters more than evidence
Why rags.cc
Private by design
Everything runs in your AWS VPC. Bedrock via private endpoint. Zero egress.
Verifiable citations
Every answer links to the exact chunk. Forensic auditability months later.
True multi-tenant
Row-Level Security in PostgreSQL. Isolation verified by automated tests.
LLM replaceability
Decoupled Model Gateway. Switch from Claude to Llama without rewriting the product.
Simple public pricing
All prices in USD. No surprises. Monthly or annual billing with a discount.
Starter
- 1 workspace
- 500 documents
- 1,000 queries / mo
- 10M LLM tokens / mo
- Claude Haiku 4.5
- 30-day audit log
Pro
- 5 workspaces
- 5,000 documents
- 10,000 queries / mo
- 50M LLM tokens / mo
- Haiku 4.5 + Sonnet 4.6
- 90-day audit log
- 99.5% SLA
Business
- 25 workspaces
- 50,000 documents
- 50,000 queries / mo
- 200M LLM tokens / mo
- Haiku + Sonnet + Opus 4.6
- BYO-LLM
- 1-year audit log
- 99.9% SLA
Prices shown in US dollars (USD). Taxes not included. Monthly or annual billing with a discount.