AI that knows your business, not just the internet
Large language models like GPT-4o are extraordinarily capable — but left to their own devices, they answer from their training data, which is general, outdated, and does not know anything about your company, your products, or your policies.
We build chatbots with a Retrieval-Augmented Generation (RAG) pipeline at the core. Your documentation, knowledge base, or support content is indexed into a vector database. Every user query retrieves the most relevant chunks of your actual content, which are then passed to the LLM to generate a grounded, accurate answer — with sources. The result is a bot that behaves like a well-informed expert on your organisation, available 24/7.
How RAG Works
Four steps from your content to an accurate, grounded answer.
Ingest your content
We load your documentation, PDFs, web pages, Notion, Confluence, or any other content source into a processing pipeline that chunks, cleans, and structures the data.
Generate embeddings
Each chunk of content is converted into a high-dimensional vector embedding using OpenAI or another embedding model and stored in a vector database (Pinecone or pgvector).
Retrieve relevant context
When a user asks a question, we run a semantic similarity search to retrieve the most relevant chunks from your knowledge base — far more accurate than keyword search.
Generate a grounded answer
The retrieved context is passed to the LLM (GPT-4o, Claude 3.5, or Gemini 1.5) alongside the user question. The model answers using only your data — no hallucinations.
Why RAG beats fine-tuning for most use cases: Fine-tuning bakes knowledge into model weights and becomes stale the moment your docs change. RAG retrieves live from your knowledge base — so updates take minutes, not retraining runs.
What We Build
Four distinct chatbot types, each engineered for a different purpose.
Knowledge-Base Bots
Connect your help centre, documentation site, internal wiki, or product manuals. The bot answers questions 24/7, cites its sources, and learns from new content as you update it.
Key capabilities
- Ingests PDFs, URLs, Notion, Confluence, Google Docs
- Semantic search across thousands of documents
- Source citations in every response
- Automatic re-indexing when content changes
- Confidence scoring — low-confidence answers escalate
- Multi-language support
Customer Support Bots
Automate tier-1 support — the repetitive, high-volume queries that consume your support team. The bot handles them instantly, around the clock, and hands off to a human when it should.
Key capabilities
- Ticket deflection with measurable resolution rates
- Intelligent escalation to human agents
- Integration with Zendesk, Intercom, Freshdesk
- Conversation history and context across sessions
- CSAT rating capture after each conversation
- Manager dashboard with volume and resolution metrics
Website Chat Widgets
A fully branded, embeddable chat widget for your website — deployed with a single script tag, no iframe. Customise colours, avatar, welcome message, and conversation starters to match your brand.
Key capabilities
- Single <script> tag deployment
- Full CSS and branding customisation
- Mobile-responsive, accessibility-compliant
- Proactive trigger rules (scroll depth, time-on-page)
- Lead capture form inside the chat
- GDPR consent banner built in
Internal AI Assistants
Private bots for your team — trained on your internal policies, SOPs, HR docs, and technical documentation. No data leaves your infrastructure unless you want it to.
Key capabilities
- Trained on internal policies and SOPs
- Role-based access — different bots for different teams
- SSO/LDAP authentication
- On-premise or private cloud deployment option
- Audit trail of all queries and responses
- Feedback loop for continuous improvement
Integrations
We connect your chatbot to the tools your team already uses — from support desks to CRMs to content platforms.
Not on the list? If it has an API or a webhook, we can integrate it. Get in touch and we will confirm.
Why HostingOcean Solutions
AI chatbot agencies are everywhere. Here is what makes the difference.
RAG-first approach
Every bot we build uses your data, not the model's training data. Accurate, source-backed answers — not confident hallucinations.
Production-grade from day one
Rate limiting, error handling, fallback models, streaming responses, and conversation persistence — all built in, not added later.
Continuous improvement loop
Every conversation generates data. We build feedback mechanisms and dashboards so you can identify gaps and improve accuracy over time.
GDPR & data security
EU data residency, conversation retention controls, DPA agreements, and optional on-premise deployment for sensitive use cases.
Model agnostic
We are not tied to any one AI provider. We choose the right model for each task and switch or blend models as the landscape evolves.
You own the code
We deliver full source code, infrastructure configs, and documentation. You are never locked into a third-party chatbot SaaS.
How an AI Chatbot Project Works
From content audit to a live, monitored production bot — a structured six-step delivery.
Discovery & Use-Case Scoping
We start by understanding the problem you want to solve — the content sources, the user types, the expected query volume, and what success looks like. We document the use case, data sources, integration requirements, and acceptance criteria before writing any code.
Architecture & Model Selection
We design the full RAG pipeline — chunking strategy, embedding model, vector store choice, retrieval method (semantic, hybrid, or keyword), and LLM selection. You get a technical specification document and a fixed-price quote before development begins.
Knowledge Base Build & Indexing
We ingest your content — PDFs, web pages, Notion, Confluence, Google Docs, or custom APIs — process it through our pipeline, and build the vector index. You can review the indexed content and test retrieval quality before we connect the LLM.
Bot Development & Evaluation
We build the bot interface, connect all integrations, and run a structured evaluation suite — a set of real questions the bot should answer correctly. We measure precision, recall, and answer quality before you see a single conversation.
Deployment & Embedding
We deploy to production — whether that is a hosted API, an embeddable widget, a Slack integration, or a WhatsApp bot. We manage infrastructure, SSL, rate limiting, and monitoring. You receive a deploy guide and embed instructions.
Monitoring, Feedback & Iteration
Post-launch, we monitor response quality, track unanswered questions, and close gaps in the knowledge base. Every engagement includes a support window and optional retainer for continuous improvement as your content evolves.
AI Chatbot Pricing Guide
Every project is scoped individually — but here is a realistic guide to what AI chatbot builds cost.
Knowledge-Base Bot
£5,000 – £12,000
A RAG chatbot trained on your documentation, FAQs, or knowledge base — embedded on your website or internal tool. Ideal for support deflection and self-service.
- RAG pipeline with up to 500 documents
- GPT-4o or Claude-powered responses
- Embeddable website chat widget
- Source citations in responses
- Admin dashboard with conversation logs
- Post-launch support (30 days)
Customer Support Bot
£10,000 – £28,000
A full support automation system integrated with your ticketing platform. Handles tier-1 queries, escalates intelligently, and tracks resolution rates.
- RAG pipeline with unlimited documents
- Zendesk / Intercom / Freshdesk integration
- Intelligent human handoff logic
- Conversation analytics dashboard
- Multi-language support
- GDPR-compliant data handling
Internal AI Assistant
£8,000 – £22,000
A private, role-aware assistant for your team — trained on internal SOPs, HR docs, and technical knowledge. SSO-authenticated, audit-logged, and deployable on-premise.
- Private deployment (your infrastructure)
- SSO / LDAP / Active Directory auth
- Role-based access control
- Full audit trail of all queries
- Feedback loop & retraining workflow
- Priority support SLA
All prices are estimates — final costs depend on content volume, integrations, and complexity. View full pricing guide →
Frequently Asked Questions
Straight answers to the questions every AI chatbot buyer asks.
Will the chatbot make up answers (hallucinate)?
How much content does the bot need to get started?
How long does it take to build and deploy?
What happens when my documentation changes?
Can the bot work in multiple languages?
Who owns the bot code and data after the project?
Ready to deploy your AI chatbot?
Tell us what problem you want to solve and what content your bot should know about. We will design the right architecture, choose the right model, and deliver a production-ready system — complete with admin dashboard and embed widget.
Free scoping call · No commitment · UK-based team