It knows your business
Trained on your documents, your products, your policies. Not generic internet answers.
AI that does a job, not a demo
Most AI projects are impressive for a week and then quietly abandoned. We build the boring kind that keeps working — answering the same questions your team answers fifty times a day, finding the document nobody can find, drafting the reply before you wake up.
Most AI projects fail for the same three reasons
It was built to impress, not to be used. A chatbot that can discuss philosophy but cannot tell a customer where their order is.
Nobody costed the running fees. AI charges per message. A chatbot that goes viral can hand you a bill nobody planned for.
The data was a mess. AI can only answer from what you give it. If your information lives in six inboxes and a shared drive, that is the real problem — and no model fixes it for you.
We start with what job you need done, and sometimes we tell you AI is not the tool for it.
What is actually included
It says 'I do not know'
Configured to admit uncertainty and hand over to a human rather than inventing an answer.
Costs you can predict
We estimate the monthly running cost before we build, and set limits so it cannot surprise you.
A human handover path
Every conversation can escalate to a person. AI is the first line, not the only one.
You can see what it said
Logs of every conversation, so you can catch problems and improve it.
Full handover
Code, prompts, API keys, docs. Swap providers whenever you like.
Where AI actually earns its keep
Customer support chatbots
The one that pays for itself fastest. It answers the questions your team answers a hundred times a week — order status, opening hours, returns, how something works — and hands over to a human the moment it is out of its depth. Most businesses see it handle half their support volume within a month.
GPTClaudeLive handoverMulti-language
Document search & knowledge bases
You have hundreds of PDFs, contracts, manuals or policies and nobody can find anything. We build search that understands the question rather than matching keywords — ask it in plain English and it finds the paragraph and tells you which document it came from.
RAGVector searchCitationsPrivate
AI features inside your product
Summarising, drafting, categorising, extracting — the small tasks inside your app that used to need a human. We wire the model into what you already run so it feels like part of the product rather than a bolt-on.
OpenAI APIClaude APIStreamingEmbeddings
Email & workflow automation
Incoming enquiries sorted, tagged, and drafted a reply before anyone opens the inbox. A person still presses send — but they are editing instead of writing from scratch.
Email parsingAuto-draftingZapierWebhooks
Content & catalogue tools
Product descriptions for five thousand items. Alt text for an image library. Translations across a whole site. The jobs that are too big to do by hand and too dull to do well.
Bulk generationTranslationSEO copy
AI strategy calls
Before you spend anything. One call where we look at what you actually do all day and tell you which parts AI can genuinely help with — and which parts it cannot. Sometimes the honest answer is a spreadsheet formula.
Honest adviceNo obligation
The tools behind it
OpenAIClaude APIGPT-4RAGLangChainPineconeOpenAIClaude APIGPT-4RAGLangChainPineconeOpenAIClaude APIGPT-4RAGLangChainPinecone
EmbeddingsVector DBNode.jsPythonNext.jsWebhooksEmbeddingsVector DBNode.jsPythonNext.jsWebhooksEmbeddingsVector DBNode.jsPythonNext.jsWebhooks
How we build it
01
The job
One call. What task are you trying to remove? If AI is the wrong tool, this is where we say so.
02
Your data
We look at what information the AI needs and whether it exists in a usable form. This is usually the real work.
03
Build
We wire it up, test it against real questions, and tune it until it stops getting things wrong.
04
Launch
We start it small — one channel, limited scope — and watch what people actually ask it.
05
Tune
Thirty days of adjustment included. AI needs correcting after it meets real users. Everyone underestimates this.
What it costs
Two numbers matter here — what it costs to build, and what it costs to run. Most agencies only tell you the first one.
Starter
$1,000 – $3,000
One clear job. A support chatbot on your site, or search across your documents. 3–4 weeks.
- Trained on your content
- Human handover
- Conversation logs
- Cost limits
- 30 days tuning
Standard
$3,000 – $7,000
AI built into your product or workflow. Multiple sources, custom logic, admin panel to control it. 6–10 weeks.
- Everything in Starter
- Custom integration
- Multiple data sources
- Admin controls
- Analytics
- Training call
Custom
$7,000+
Complex pipelines, private models, sensitive data, or AI as a core part of what you sell.
- Everything in Standard
- Private deployment
- Custom pipelines
- Compliance work
- Ongoing retainer
The running cost nobody mentions
AI charges per message. A support chatbot handling 1,000 conversations a month typically costs $20–$100 in API fees — small, but it is not zero, and it scales with your traffic. We estimate this before we build and set hard limits so a spike cannot hand you a surprise bill. Anyone who does not mention this to you has not thought about it.
Not sure which one you need? Most people are not. Book a call and we will tell you honestly.
Questions we get asked
Tell us what you keep repeating
A rough idea is enough to start. Send us a paragraph and we will come back within 24 hours with an honest read on scope, cost, and timeline.