AI Applications
Business applications with LLMs at the core — summarization, extraction, classification, and generation built into real product flows.
AI Application Development
Put AI to work on a specific business task. We build applications for finding information, processing documents, preparing drafts, and assisting users, with review steps suited to the task.
Discuss this serviceWhat the project can include
AI Assistants & Chatbots
Assistants for websites or supported messaging platforms, using approved business information and defined handoff paths.
AI Agents
Tool-using agents that plan multi-step work across your APIs and systems, with human oversight built in.
RAG Systems
Retrieval-augmented generation over your documents and knowledge bases, so answers stay grounded and citable.
Document Intelligence
OCR + LLM pipelines that extract, classify, and validate data from invoices, forms, and scanned documents.
AI Search
Semantic search over your content using embeddings and vector search, beyond keyword matching.
Possible applications
Examples of where this service could fit. The final scope depends on your process, information and existing tools.
Customer support assistants that answer from your own knowledge base
Internal assistants for policies, documentation, and operations questions
Document processing for invoices, forms, and scanned records
Lead qualification and routing on websites and WhatsApp
AI features inside an existing SaaS or web application
Semantic search across products, articles, or archives
Automated summaries, reports, and email drafting
Delivery approach, process and technologies
Explore how the work is planned, built and delivered.View detailsHide details
Our approach
Model-agnostic by design
Choose a model and provider around the task, data requirements, and operating costs. Keep provider-specific behaviour separate where practical.
Grounded in your data
Retrieval can supply relevant source passages and citations. Answer quality still depends on the documents, retrieval pipeline and evaluation.
Production-first engineering
Plan evaluation, fallback behaviour, usage limits and deployment requirements as part of the project scope.
Project stages
Discovery
We map the use case, the data involved, and what success looks like.
Prototype
Test a focused proof of concept against representative data and agreed evaluation criteria.
Build & Integrate
The AI is engineered into your product, workflows, and infrastructure.
Launch & Improve
Monitoring, evaluation, and iteration once it's serving real users.
Technology options
Selected around your requirements and existing systems.
- OpenAI
- Anthropic Claude
- LangChain
- Python
- FastAPI
- Node.js
- PostgreSQL
- Supabase
- AWS
- Docker
Common questions
Practical details to consider when planning this service for your business.
The model and provider are selected around the task, data requirements, available APIs and operating costs. Supported capabilities are assessed during scoping.
Often an existing application can be extended. We first review its code, available interfaces and access requirements to determine the changes needed.
Data access, hosting, retention and third-party provider settings should be agreed before development. Tell us about sensitive information and internal requirements during scoping.
Timing depends on the features, data preparation, integrations and evaluation requirements. An estimate follows review of those dependencies.
Explore related services
Find the service that matches the next part of your requirements.
View all servicesHave an AI use case in mind?
Tell us about your requirements, existing tools, and priorities. We can then discuss the scope, timing, and cost.
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