# Answers from your data, with receipts.

> Retrieval-augmented generation over your documents, tickets and databases, with citations, permissions and measured answer quality. Chat with your company data, safely.

URL: https://ai.arcvs.tech/en/services/rag-knowledge-systems · Português: https://ai.arcvs.tech/pt/servicos/rag-base-de-conhecimento.md · ARCVS AI: https://ai.arcvs.tech/en.md

Assistants that search your docs, wikis, tickets and databases, answer with citations, respect who can see what, and say "I don't know" instead of inventing. Quality is measured, not assumed.

- **Week 1**: Prototype on your data
- **Day 30**: Production pilot
- **100%**: Yours: code & weights

## Most RAG demos die on real documents.

Scanned PDFs, stale wikis, tables, permissions and contradictory versions break naive retrieval. We engineer ingestion, chunking, hybrid search, reranking and access control, and we prove answer quality with an eval set built from your real questions.

## What we build

- **Internal knowledge assistant**: Policies, processes and product docs answered in seconds, with the source paragraph linked.
- **Support deflection**: Customers get correct answers from your help center and past tickets; agents get suggested replies.
- **Contracts & compliance search**: Find clauses, obligations and deadlines across thousands of documents.
- **Analytics in plain language**: Text-to-SQL over your warehouse with guardrails, so the answer comes from the database, not a guess.

## What you get

- Ingestion pipeline: PDFs, Office, Notion, Drive, Confluence, databases
- Hybrid search (vector + keyword) with reranking
- Document-level permissions mirrored from your sources
- Answer-quality evals: faithfulness, citation accuracy, refusal rate
- Chat UI, Slack/Teams bot or API, your call

## Stack

pgvector, Postgres, Elasticsearch, Qdrant, Embeddings, Rerankers, Claude, GPT, Gemini, Next.js

## FAQ

### Will it hallucinate?

We design it to cite or refuse. Every answer links its sources, and the eval suite tracks faithfulness and refusal rate so regressions are caught before release.

### Can it respect document permissions?

Yes. Retrieval filters by the asking user's access, mirrored from your source systems, so nobody gets an answer built from a document they can't open.

### Do we need a vector database?

Often Postgres with pgvector is enough and keeps your stack simple. We only add infrastructure when scale demands it.

### Where does our data go?

It stays in your cloud. Embeddings and indexes live in your accounts, and we can use models with zero-retention terms or self-hosted ones.

## Other capabilities

- [AI agents](https://ai.arcvs.tech/en/services/ai-agents): Agents that use your tools, follow your rules and finish real tasks end to end.
- [Agentic orchestration](https://ai.arcvs.tech/en/services/multi-agent-orchestration): Planner, workers and reviewers that run in parallel, with one owner of state and a full audit trail.
- [Model training & fine-tuning](https://ai.arcvs.tech/en/services/llm-fine-tuning): Fine-tuned and distilled models that win on your task, run cheaper, and belong to you.
- [AI automation](https://ai.arcvs.tech/en/services/ai-automation): Workflows where AI reads, classifies and decides, and code does the rest. Measured in hours reclaimed.
- [Private & on-prem AI](https://ai.arcvs.tech/en/services/private-ai): Open-weight models on your cloud or hardware. Your prompts and documents never leave your perimeter.
- [AI security](https://ai.arcvs.tech/en/services/ai-security): Red teaming for LLM apps and agents: prompt injection, data leakage, excessive agency, insecure tools.
- [OSINT & security audits](https://ai.arcvs.tech/en/services/osint-security-audits): Your exposure, seen from outside: breaches, leaks, forgotten assets, CVEs. Then authorized testing and fixes.

## Contact

- WhatsApp: +5532999143361 (https://wa.me/5532999143361)
- Telegram: @w1ldcrow (https://t.me/w1ldcrow)
- Email: contact@arcvs.tech
- Contact section: https://ai.arcvs.tech/en#contact
- Parent studio: https://www.arcvs.tech