AI-powered system
RAG Systems
AI that actually knows your business.
Vector databases, semantic search, document ingestion. Your agents actually know your business — not just generic ChatGPT answers.
What you get
- Accurate answers
- Faster onboarding
- Less tribal knowledge
Generic chatbots guess. Retrieval-augmented generation (RAG) grounds every answer in your own documents, SOPs, contracts, product data and tickets — with citations. We build the ingestion pipelines, vector search and evaluation harness that make AI accurate enough to trust with customers and staff.
Capabilities
Everything included in our rag systems.
Document ingestion
PDFs, Google Drive, Notion, SharePoint, websites, help desks — chunked and indexed automatically.
Semantic + hybrid search
Vector and keyword search combined, with re-ranking for precise answers.
Cited answers
Every response links back to the source so users can verify it.
Access control
Users only retrieve documents they’re allowed to see.
Auto-sync
New and updated documents re-index on a schedule or on change.
Evaluation suite
We measure accuracy on your real questions before and after launch.
Use cases
Where it pays off fastest.
An internal assistant trained on SOPs and policies.
A customer-facing support bot grounded in your docs.
Searching contracts, reports and case files in plain English.
Process
How we work
Fixed scope, weekly demos, no black boxes. Most AI projects go live in 2–5 weeks.
Audit
We map your workflows, calls and data, then rank opportunities by ROI. Free, 30 minutes.
Design
Conversation flows, architecture and integrations — signed off before we write code.
Build
Weekly demos, a shared Slack channel and production-grade code you own.
Launch & optimise
Go live, monitor every conversation and workflow, and improve every week.
Case studies
RAG & Knowledge AI in production.
Tech & SaaS · RAG & Knowledge AI
RAG support agent for a B2B SaaS
A cited, grounded support agent trained on docs, changelogs and resolved tickets.
Law Firms · RAG & Knowledge AI
Contract & precedent search for a corporate law firm
Attorneys ask questions across thousands of agreements and get cited, permission-aware answers.
Manufacturing · RAG & Knowledge AI
Shop-floor SOP assistant for a manufacturer
Operators ask questions on a tablet and get step-by-step answers from SOPs and machine manuals.
FAQ
RAG Systems — FAQ
What is a RAG system?
Retrieval-augmented generation: before the AI answers, it searches your own knowledge base and uses the most relevant passages as context. The result is accurate, up-to-date, citable answers.
Is my data used to train public models?
No. We use API providers with zero-retention or no-training terms, and can deploy on your own cloud.
Which vector database do you use?
Pinecone, Supabase pgvector, Qdrant or Weaviate — picked for your scale, budget and hosting needs.
How accurate is it?
We build an evaluation set from your real questions and report accuracy before launch. Typical production systems we ship answer the large majority of in-scope questions correctly and say “I don’t know” for the rest.
RAG & Knowledge AI across the US
Remote-first, across all 50 states.
We work with businesses nationwide, with daily overlap across Eastern, Central, Mountain and Pacific time. Tell us where you’re based →
Pairs well with
Related services
AI Calling Platforms
Voice agents that handle inbound and outbound calls autonomously — appointment booking, lead qualification, support. Powered by our flagship platform Voxiqo.
AI Chat Agents
WhatsApp, Instagram DMs, website chat. Multi-channel agents that sell products, qualify leads, resolve tickets, and hand off to humans only when needed.
Workflow Automation
n8n, APIs, business process automation. We’re Pakistan’s only n8n Certified Training Institute — and we wire your entire stack together.