Turn Your Website Into a 24/7 Pre-Sales Engineer
We build controlled AI assistants that answer only from your approved content — with citations, security controls, and measurable commercial impact. Not a chatbot. A governed knowledge system.
What Changes for Your Business
This isn't a novelty feature. Every component is designed to move a specific commercial metric.
Faster Qualification, Higher Intent
Complex pre-sales questions answered instantly from your approved documentation. Prospects don't bounce when they can't find answers. Technical buyers get depth immediately. When someone reaches "Book a demo," they've already qualified themselves.
Fewer Tickets, Better Documentation
Repetitive pre-sales questions deflected before they become support tickets. Every query is logged — recurring questions reveal documentation gaps. You don't just reduce support load, you improve the knowledge base that causes the load.
Governed Answers, Auditable Trail
Every response sourced from approved material. No hallucinated pricing, no outdated feature claims, no off-brand messaging. Full query logging creates an audit trail of what your AI said and when. If accuracy is business-critical, governance isn't optional.
AI Is Already Talking About You
Your customers are asking ChatGPT, Claude, Perplexity and Google AI Overviews about your industry right now. The question isn't whether AI will affect your pipeline — it's whether you'll control what it says.
Invisibility
AI systems don't mention your brand at all. Competitors get recommended instead. You lose pipeline you never even see.
Misinformation
LLMs describe your products incorrectly — wrong pricing, outdated features, confused with competitors. Your brand is being misrepresented at scale.
Loss of Control
Generic chatbots and AI search engines scrape your site and present answers without context, nuance, or commercial framing. You've lost control of the narrative.
A Governed Knowledge System, Not a Chatbot
A Controlled AI Knowledge Agent is a domain-restricted assistant deployed on your website that answers questions using only your approved content. It doesn't search the internet. It cites every source. And when it can't answer from approved material, it says so — rather than guessing.
Think of it as giving your website an expert employee who knows your products, services and methodology inside out — available 24/7, never off-brand, and always pointing visitors toward the right next step.
Why Not Just Install a Chatbot Plugin?
Fair question. There are WordPress chatbot plugins available for under £100/month. Here's the difference between installing a feature and engineering a knowledge system.
AI Chatbot Plugin
- Generic RAG setup with default settings
- API keys often exposed client-side
- Weak or no citation validation
- Minimal refusal logic — guesses when unsure
- No governance model or audit trail
- No measurable improvement loop
- Installed in a day, abandoned in a month
Governed Knowledge System
- Curated, structured knowledge base
- Server-side proxy — keys never exposed
- Enforced source grounding on every response
- Boundary enforcement — refuses rather than guesses
- Documented governance controls + full logging
- Query analytics driving continuous optimisation
- Designed for long-term commercial performance
If your AI assistant gives incorrect legal, financial, or technical information, the reputational cost dwarfs the installation fee. We're not installing a feature. We're building a knowledge system.
Trust & Governance
If you're in a regulated industry, selling complex products, or simply taking brand accuracy seriously — governance isn't a feature. It's the foundation.
See It in Action
Our own LLM Optimisation page runs on exactly this architecture. It's not a mock-up — it's a production system handling real queries, with the same citation enforcement and governance controls we deploy for clients.
Most agencies selling AI products haven't built one themselves. We have. Ask it anything.
Try the Live DemoHow We Build It
Every engagement follows a three-phase model. Each phase delivers standalone value — you can stop at any point with something useful.
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1
AI Infrastructure Audit
We audit your current AI visibility across ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews. We assess your existing content, benchmark against competitors, and scope the architecture. You get a clear report of what LLMs currently say about you, whether a Knowledge Agent is viable, and the ROI levers. If it's not viable, we tell you not to build.
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2
Build & Deploy
We structure your knowledge base, build the retrieval system, configure citation enforcement and security controls, design the conversational UX, and deploy to your WordPress site. Typical builds take 4–6 weeks from audit to live.
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3
Optimise & Evolve
We monitor query analytics to identify content gaps, refine retrieval scoring, expand the knowledge base, and evolve the system as your products and market change. Monthly performance reviews show exactly what's working and what needs attention.
Why We Build It This Way
There is a growing assumption in AI product circles that open is always better. Connect everything. Expose your data through a universal standard. Let any AI system query your business in real time.
We build the opposite. Deliberately. Here is why.
The Curated Gallery
Someone has decided what is on those walls. Someone chose the sequence, the lighting, what sits next to what and why. You are not browsing — you are being guided through an argument. Every decision is deliberate. You leave having seen exactly what the curator intended.
- AI draws only from approved, verified content
- Every response sourced and cited
- Defined perimeter — the AI cannot roam outside it
- Your brand, your experience, your lead capture
- Governed, auditable, maintainable
The Open Library
Walk in, take whatever you want, follow whatever thread interests you. Open access. Self-directed. The AI decides what is relevant. The brand is whoever made the interface, not you.
- AI queries whatever it can reach
- No source validation on responses
- No perimeter — gaps filled with inference
- Experience belongs to the AI platform, not you
- Difficult to audit, govern, or explain
Think about what a good solicitor does before they advise a client. They don't say the first thing that comes to mind. They draw on what they know, what they have verified, what they would stake their professional reputation on. That is what a governed AI assistant does. It only tells your visitors what you have decided is accurate enough to put your name to.
An open system that queries whatever it can find is the equivalent of asking a stranger in the street for legal advice. They might be right. You have no way of knowing. And crucially — neither do they.
Control creates trust
The AI cannot hallucinate pricing it has never been told. It cannot quote a policy that does not exist in your knowledge base. When it reaches the edge of what it knows, it says so and offers to help another way. That behaviour is engineered, not hoped for.
Trust creates value
Visitors on your website are not "using AI." They are using your assistant. Your brand, your language, your lead gate. An integration living inside someone else's AI tool has no brand presence at all — the experience belongs to their platform, not to you.
Value justifies the investment
A curated, expertly maintained intelligence system is worth something. A database connection is a utility. Utilities do not command premium positioning. Curated expertise does. The gallery charges for the experience. The library is free.
People trust what others say about you more than what you say about yourself. Think about why you check TripAdvisor before booking a hotel — the hotel's own website will tell you it's wonderful, of course. But TripAdvisor is editorial. Nobody paid those reviewers. That's precisely why you believe them.
A governed AI assistant is the opposite of self-promotion. It answers from structured, verified knowledge with sources attached. When a technical buyer asks a hard question and your AI responds with a sourced, accurate answer — citing the specific documentation section it drew from — that is a trust signal no marketing copy can replicate.
Strong brands rank and dominate. In the AI era: strong brands rank, get cited, and dominate. The principle has not changed. The surface it plays out on has.
What about MCP and open protocols?
Model Context Protocol — the emerging standard for connecting AI systems to live business data — is real, important, and worth planning for. We wrote about it in detail: MCP Will Change Which Businesses AI Recommends.
The honest position: MCP becomes commercially decisive when AI moves from answering questions to completing tasks. That shift is coming. But it sits at Stage 5 of the recommendation eligibility pipeline — only relevant after the foundations are solid. A live data layer on top of an unverified, inconsistently positioned business does not solve the underlying problem. Gallery first. Live data layer when the use case demands it.
Typical Investment
Every build is scoped individually based on content scale, compliance requirements, and integration needs. These ranges give you a realistic picture.
AI Infrastructure Audit
Comprehensive AI visibility assessment, competitor benchmarking, content readiness review, audience resonance analysis, and Knowledge Agent blueprint with exact scope and pricing. Delivered within 5 business days.
Build & Deploy
Knowledge base structuring, retrieval system build, citation enforcement, security controls, governance documentation, conversational UX, WordPress deployment, and testing. Typical delivery: 4–6 weeks.
Optimise & Evolve
Monthly performance review, query analytics, knowledge base expansion, retrieval refinement, content gap reports, and conversion optimisation. Cancel anytime.
What's Included in the Audit
The audit is a standalone deliverable with immediate value — even if you never build the Knowledge Agent, you'll know exactly what AI platforms are saying about your brand and whether your target buyer would care.
We query ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews with 15–20 prompt variations about your brand, products and industry. Every response documented and scored for accuracy, completeness and sentiment.
Same prompts for 2–3 competitors. Where do they get mentioned and you don't? Where are they described more accurately? This shows you the gap — and the opportunity.
We map AI responses against your target buyer's actual priorities and decision criteria. It's not enough that AI mentions you — does what it says match what your buyer cares about?
A scoped proposal: knowledge base structure, topic clusters, integration approach, access model, governance requirements, and a specific investment figure — not a range, an exact number.
A 15–25 page PDF report with AI Visibility Scorecard, annotated LLM response evidence, competitor comparison, audience resonance scoring, and the Knowledge Agent blueprint with exact scope and pricing. Delivered within 5 business days.
Not sure where you'd sit? The AI visibility audit is the starting point — it gives you a clear scope and exact investment before you commit to anything.
Learn about the audit →Is This Right for You?
You need a governed system if
- You have complex products that generate pre-sales questions
- You're in a regulated industry (healthcare, legal, finance)
- You have 50+ pages of product, service or documentation content
- Brand accuracy is business-critical, not nice-to-have
- You want AI to generate qualified leads, not just answer questions
- You need an audit trail of what your AI says
A plugin may be enough if
- You have under 20 pages of content
- Brand risk is low and accuracy is non-critical
- You want experimentation, not production deployment
- You don't need logging, governance, or analytics
We'll tell you honestly if a plugin would serve you better. The audit exists to answer exactly this question.
Questions We Get from Buyers
"What does this actually change for our pipeline?"
Prospects get depth immediately instead of bouncing when they can't find answers. Technical buyers self-qualify through the assistant before booking a call. Your sales team spends less time on basic qualification and more time on high-intent conversations. We track CTA engagement from assistant sessions so you can measure the impact directly.
"What does this change for our support load?"
Repetitive pre-sales questions get answered instantly from your knowledge base. But the bigger value is what the query analytics reveal — the questions your audience keeps asking that your documentation doesn't answer. You reduce support tickets and improve the content that causes them.
"What about risk — what if it says something wrong?"
The system is designed to answer only from approved sources. When it can't ground a response in your content, it refuses rather than guessing. Every response is logged with its source reference. For regulated industries, this governance model is the difference between a useful tool and a liability.
"What if we need to move on — are we locked in?"
No proprietary lock-in. WordPress-native deployment, documented architecture, transferable knowledge base. The retainer is cancel-anytime. If you ever want to bring it in-house or switch providers, everything stays yours.
"You're a one-person operation — what about continuity?"
Valid concern. Every build includes full architectural documentation and runbooks. The system is designed to be maintainable by any competent WordPress developer. You're getting direct access to the person who architected and built it — not a junior account manager. The trade-off is capacity, not capability.
Ready to own the AI conversation?
Start with an AI Infrastructure Audit. You'll know exactly what LLMs are saying about your brand, whether a Knowledge Agent is viable, and the commercial case for building one. If it's not right for you, we'll say so.