RAG & Enterprise Knowledge That Answers From Your Own Data
Retrieval-Augmented Generation lets an AI system answer from your own documents, products, and internal knowledge rather than only from what the model was trained on, and respect who is allowed to see what.
When you need this
The answer already exists somewhere in your documents, tickets, and wikis, and nobody can find it quickly enough for it to matter.
Build AI systems that securely retrieve and use your company's data, documents, and knowledge.
Let's Get Started- Ingestion pipelines
Connectors, parsing, and chunking for the documents, databases, and systems your knowledge actually lives in.
- Retrieval that holds up
Search and embedding strategy tuned and measured against your content, because defaults rarely survive real data.
- Permission-aware answers
Retrieval scoped to the access a user already has, so an assistant cannot surface what they could not open themselves.
- Citations by default
Every answer points back to its source, so people can verify it instead of having to trust it.
What we work in
The tools this work runs on, and what each one is here for.
LangChainLoading, chunking and retrieval chains over your sources.
QdrantVector search with filters that enforce who can see what.
pgvectorEmbeddings beside the relational data you already keep.
ElasticsearchHybrid keyword and vector search where exact terms matter.
Hugging FaceOpen embedding and reranking models, run where you choose.
OpenAIHosted embedding models when they are the better fit.
The rest of what we build
Most engagements touch more than one of these. Start wherever the problem is.
LLM Integration & AI Copilots
Integrate LLMs into existing applications and workflows to give teams and customers intelligent capabilities.
AI Workflow Automation
Automate repetitive business processes using AI, APIs, agents, and existing business systems.
Custom AI Applications
Design and build AI-powered applications around your specific business requirements, data, workflows, and users.
AI Architecture & Infrastructure
Design the architecture, data pipelines, model integrations, security, monitoring, and infrastructure required to operate AI systems reliably.
AI Modernization
Take existing AI work, including prototypes, notebooks, and early integrations, and turn it into a reliable production system.
Start With a Focused Use Case
ArcusScale can help identify a practical opportunity and build a focused pilot before committing to a larger implementation.