LLM features
Large Language Model capabilities wired into the screens and workflows your users already know.
Service
AI Integration & AI Chatbot Development
For product teams. We add intelligence to what you’ve already built, working inside your existing stack: LLM features, semantic search, RAG pipelines, copilots and AI support agents.
Who it’s for
Product teams with something already built
You have a product, a platform or an internal tool, and you want it to do more with AI. We integrate Large Language Models and AI capabilities into your existing software, building secure and scalable AI layers into your stack instead of starting over.
- Works inside your existing stack
- Secure, scalable AI layers
- Custom integration build, retainer available
Capabilities
What we integrate
Semantic search
Search that finds content by meaning, not just matching keywords.
RAG pipelines
Answers grounded in your own documents: the system retrieves the relevant content first, then responds from it.
Copilots
Autonomous copilots that help your users and team get tasks done inside your product.
AI support agents
A customer-facing agent trained on your docs and policies. It answers on web and WhatsApp and hands off to a human when it should.
Security
Security and data handling
- Access scoped to your data: the AI layer only reaches the content it needs.
- API keys kept server-side, never exposed in the browser.
- Human hand-off: agents pass a conversation to a person when they should.
- Built inside your stack, with documented code and a clean handover.
Live example
You’re looking at one
The Ask Desmok assistant on this site is a RAG chatbot built by Desmok. It retrieves from our pages and a curated knowledge file, and answers only from that context. Open it from the button at the bottom of the page and ask it about our services.
Process
How an integration project runs
Scope
A scoping conversation about your product, your users and what AI should do for them.
Design
We design the AI layer around your existing stack and the data it may use.
Build
We build and integrate the feature, search, pipeline or agent into your product.
Launch & improve
We ship it, then keep tuning it on a retainer or hand it over to your team.
After launch
Maintenance and scaling on a retainer
On a monthly retainer we look after maintenance and scaling, with continuous optimisation of API calls and scaling as you grow. Prefer to run it yourselves? You get documented code and a clean handover, with no lock-in. Compare engagement models.
Related
Keep exploring
FAQ
Frequently asked questions
Do you rebuild our product to add AI?
No. AI Integration works inside your existing stack: we add the AI layer to the product you have already built.
What can you build into our product?
LLM-powered features, semantic search, RAG pipelines that answer from your own content, autonomous copilots, and AI support agents for web and WhatsApp that hand off to a human when they should.
Can an AI support agent answer from our own documents?
Yes. We train the agent on your docs and policies using a RAG pipeline, so it retrieves the relevant content and answers from it. The Ask Desmok assistant on this site works the same way.
How do you handle our data and API keys?
The AI layer only gets access to the data it needs, API keys stay on the server and never in the browser, and support agents can hand a conversation off to a person.
What happens after the integration goes live?
You can keep us on a monthly retainer for maintenance and scaling, including continuous optimisation of API calls as you grow, or take over with documented code and a clean handover.
How is AI integration priced?
Every project gets a tailored quote after a scoping call. You can choose a custom integration build, a monthly retainer, or both; see our engagement models for details.
Add AI to what you’ve already built
Tell us about your product in a short scoping call, and we’ll come back with a tailored quote.