Custom AI chatbots and RAG (retrieval-augmented generation) knowledge bases trained on your docs, products, policies and brand voice. Deployed on your site, in Slack, in Intercom or as a standalone app — answering customer questions 24/7 with human-grade accuracy.
AI chatbots built on Retrieval-Augmented Generation (RAG) are conversational assistants that answer questions by retrieving relevant passages from a defined knowledge base — such as company PDFs, Notion pages, Confluence wikis, product catalogues, or support ticket histories — rather than relying solely on a general-purpose language model's training data. Sumit Brands designs and deploys RAG chatbots trained on client-supplied content, using foundation models including Claude, GPT-4, or open-source alternatives such as Llama and Mistral. Chatbots can be deployed to websites, Slack, Intercom, WhatsApp, and Microsoft Teams. All vector and document data is hosted in Australia using Supabase, Pinecone, or AWS Sydney infrastructure to satisfy data residency requirements. Each deployment includes an evaluation harness designed to detect and reduce hallucinations, and a 30-day post-launch tuning window during which response accuracy is monitored and the retrieval pipeline is refined.
A generic chatbot will confidently make up your refund policy. A RAG-grounded bot quotes the actual document — with citations — and politely declines when it doesn't know. That's the difference between a liability and a real support agent.
We build, deploy and tune chatbots that retrieve from your real knowledge: PDFs, Notion, Confluence, product catalogues, ticket history. Your bot learns your business, not the open internet.
Document ingestion, chunking, embeddings and vector search — production-grade.
System prompts and few-shot examples that match your tone, not generic ChatGPT-speak.
Every answer can show its source. Builds trust, kills hallucinations.
Escalate to live agents, log to CRM, create tickets — never a dead end.
Web widget, Slack, Intercom, WhatsApp, Microsoft Teams — same brain.
Automated regression testing so updates don't break answers.
Whichever fits — Claude for nuance, GPT-4 for breadth, open-source (Llama, Mistral) when data sovereignty matters. We test and recommend based on your use case.
Your choice. Australian-region Supabase, Pinecone, AWS Sydney — we'll match your compliance requirements.
RAG dramatically reduces them. We also build in evaluation tests, citation requirements and "I don't know" fallbacks.
Yes — agentic flows with tool use, calendar APIs, payment links. We scope these in the discovery phase.
Free scoping call. We'll come back with a build plan, model recommendation and budget.