RAG & Knowledge AI
Turn company information into secure AI-powered knowledge systems.
A RAG system is only as good as its retrieval, ingestion, and evaluation. SkyMind builds RAG systems that are accurate, grounded, and safe: document processing pipelines, chunking and embedding strategies, vector and hybrid search, reranking, citation, and evaluation harnesses that measure grounding, recall, and answer quality. We design access controls so users only retrieve what they're allowed to see, and we add guardrails against prompt injection and sensitive disclosure.
Retrieval-augmented generation systems that answer from your authoritative sources — not from model memory.
What this engagement covers
Each capability is a scoped workstream with defined deliverables and acceptance criteria.
Ingestion & processing
Connect to documents, wikis, databases, and APIs with incremental updates and source attribution.
Retrieval architecture
Hybrid vector + keyword search, reranking, and query rewriting tuned for your domain.
Grounding & citations
Every answer is grounded in sources with citations, and refusal behavior when evidence is missing.
Access control & safety
Document-level permissions, redaction, and prompt-injection defenses.
What you walk away with
Tangible artifacts your team owns and operates — not a deck and a handshake.
Knowledge AI system
A grounded question-answering system with citations and source attribution.
Ingestion pipeline
Automated sync from your sources with change detection and reindexing.
Evaluation suite
Grounding, recall, and answer-quality evals with regression tracking.
What changes after this engagement
Answers your team can trust because they're grounded in your sources
Reduced time-to-answer for internal knowledge
Clear provenance for every response
Frequently combined with
Common questions about RAG
Start RAG & Knowledge AI
Tell us about your problem. We'll scope a path that fits your stack, timeline, and risk posture.