Turn AI capability into useful, controlled business workflows.
We integrate hosted and locally deployable AI models into products and operations, focusing on clear tasks, reliable context, human oversight and measurable usefulness.
AI automation and RAG development services
Choose Applied AI & Automation when a defined task—such as knowledge retrieval, classification, extraction or guided support—needs governed model assistance. Choose Database & API Engineering when the primary need is dependable data flow rather than AI behaviour.
Capabilities
- OpenAI, ChatGPT and Anthropic Claude integrations
- Downloadable Hugging Face and open-source models
- Retrieval-augmented generation and knowledge search
- Ticket triage and document classification
- Information extraction and summarisation
- Support chatbots and guided assistants
- Constrained agents and tool-based workflows
- Prompt, context and evaluation engineering
- Guardrails, review queues and human escalation
Begin with the task, not the model
AI creates value when it addresses a defined job. We identify where classification, extraction, summarisation, retrieval or guided generation can reduce repetitive effort or improve access to information. Boundaries, review points and fallback behaviour are defined before a model is selected.
Hosted and open-source model options
We work with OpenAI and Anthropic services for applications that benefit from managed model APIs. Where privacy, control, cost or task specialisation calls for another approach, we can evaluate downloadable models from Hugging Face and other open-source ecosystems for deployment within an appropriate environment.
Retrieval grounded in your information
Retrieval-augmented generation can make policies, support material, product documentation and internal knowledge easier to use. We design ingestion, chunking, metadata, retrieval and response workflows so answers are grounded in approved sources and can expose references where appropriate.
Ticket triage, chatbots and task-focused agents
Implementations can route support tickets, extract structured details, draft replies, search reference documentation and guide users through defined tasks. Agent-style workflows are designed around constrained tools and permissions instead of unrestricted access to business systems.
Evaluation, human control and integration
We define test cases, expected outputs, unacceptable behaviour and escalation routes. Logging, review queues, confidence thresholds and human approval can connect AI outputs with APIs, CRM platforms, email, databases and operational workflows safely.
How we work
We define the task and risk level, inspect available information, build a narrow prototype, test representative examples, integrate it with the product or workflow, then release it with monitoring and human controls suited to the use case.
- Use case
- Data review
- Prototype
- Evaluation
- Integration
- Controlled release
Frequently asked questions
Can you implement AI without sending all our information to a public service?
Potentially. Depending on the model, infrastructure and task, an open-source model may be deployed in a controlled environment. We review sensitivity, hardware needs, expected quality and operating cost first.
What is RAG?
Retrieval-augmented generation retrieves relevant material from an approved knowledge source and supplies it to the model as context. It still requires sound retrieval design, source management and evaluation.
Can AI automatically answer every customer request?
That is rarely the responsible starting point. We define which requests may be automated, which require approval and which must be escalated directly to a person.
Do you build autonomous agents?
We build task-focused workflows that use defined tools and data sources. Permissions, stopping conditions and review requirements are designed around the risk of the task.
Can AI be added to an existing application?
Yes, provided the application exposes suitable integration points or can be extended safely. We assess data flow, authentication, model access and failure handling first.