Teams are stuck on repeat tasks
Hours go to answering, sorting and copying that adds no judgement and drains focus.
Overview
What is ai integration & automation?
Most businesses carry hours of repetitive work every week: answering the same questions, sorting inboxes, copying data between tools, drafting routine documents. AI and automation can take over a large share of it, but only when they are connected to your real data and tools and guarded properly. A chatbot that cannot see your systems, or an agent with no guardrails, creates more risk than value.
We design and build AI that is useful in day-to-day operations: chatbots and voice agents that handle customers, assistants like Claude Cowork that work alongside your team, retrieval systems that answer from your own documents, and MCP integrations that let AI act inside your tools. Around them we put the unglamorous essentials: evaluation, logging, human review points and cost controls.
The problem
What goes wrong without it.
AI pilots never reach production
Demos impress, but without integration, evaluation and ownership they stall.
Answers are not grounded in your data
Generic models guess. Without your documents and tools, they hallucinate or stay shallow.
Safety and cost worry leaders
Without guardrails, logging and budgets, AI use feels risky and unpredictable.
How it works
From first touch to result, step by step.
Scroll to watch the system run. The scene on the left plays as you move through each step.
- Step
Understand the request
A language model interprets a message, call or document and decides what is being asked.
- Step
Ground it in your data
Retrieval pulls the relevant passages from your knowledge base so answers cite real sources.
- Step
Act through tools
Using MCP and APIs, the agent checks calendars, updates the CRM or drafts the reply.
- Step
Check and hand off
Guardrails, confidence checks and human approval catch edge cases before they reach customers.
- Step
Log and improve
Every run is recorded and evaluated, so accuracy and cost improve over time.
What is included
Every service, explained.
AI Agents
AI Agents
Goal-driven agents that plan, use your tools and finish multi-step work, from lead qualification to back-office tasks.
How it works
An agent receives a goal, plans the steps, calls your tools and checks its own work, escalating to a person when confidence is low or the action is sensitive.
Built with
- Claude Agent SDK
- LangGraph
- Tool calling
- Evals
Chatbots
AI Chatbots
Website, WhatsApp and in-app assistants trained on your content that answer, qualify and hand off to a person.
How it works
A chat assistant on your site, WhatsApp or app answers from your approved content, collects details, qualifies leads and hands over to a person with full context.
Built with
- Claude / GPT
- RAG
- WhatsApp API
- Live handoff
Voice Agents
AI Voice Agents
Inbound and outbound phone agents that sound natural, speak your customers' language and book straight into your calendar.
How it works
Speech is transcribed in real time, a model decides the response and calls tools such as your calendar, then a natural voice replies within a fraction of a second.
Built with
- Vapi
- Retell AI
- Deepgram
- ElevenLabs
- Twilio
Claude Cowork
Claude Cowork & AI Teammates
Claude set up as a teammate around your files, tools and routines, drafting, researching and reporting alongside your people.
How it works
We configure Claude around your files, tools and routines so it can draft, research, summarise and report as a teammate, with clear permissions and review steps.
Built with
- Claude
- Connectors / MCP
- Project knowledge
- Permissions
Claude & GPT Apps
Custom Claude, GPT & LLM Apps
Purpose-built products on Claude, GPT, Gemini or open models, with your prompts, guardrails and data.
How it works
We build products on Claude, GPT, Gemini or open models: prompts and system design, structured outputs, tools, guardrails and an evaluation harness.
Built with
- Anthropic API
- OpenAI API
- Structured outputs
- Evals
Knowledge & RAG
Knowledge Base & RAG
Assistants that answer from your documents, wikis and tickets, and show the source.
How it works
Your documents are cleaned, split and embedded, stored in a vector index, and retrieved at question time so answers are grounded and cite their sources.
Built with
- pgvector
- Embeddings
- Reranking
- Citations
MCP & Integrations
MCP & Tool Integrations
Connect AI to your CRM, calendar, email and databases through MCP servers and APIs, so it can act, not just talk.
How it works
We build MCP servers that expose your CRM, calendar, email and databases to AI with scoped permissions, so assistants can act, not just answer.
Built with
- MCP
- OAuth scopes
- REST APIs
- Audit logging
Document AI
Document & Data Processing
Invoices, contracts, forms and emails read, extracted and filed automatically.
How it works
Incoming PDFs, forms and emails are read with OCR and language models, fields are extracted and validated, then filed or pushed to the right system.
Built with
- OCR
- LLM extraction
- Validation rules
- Webhooks
RPA
Process Automation (RPA)
Workflow orchestration and API data integration.
How it works
Workflows connect your apps through APIs and, where none exist, browser automation, with retries, queues and alerts so processes run unattended.
Built with
- n8n
- Make
- Playwright
- Queues
Sales & Support AI
AI Sales & Support Assistants
Lead qualification, follow-up, ticket triage and drafted replies that your team approves in one click.
How it works
Assistants score and qualify leads, triage tickets, and draft replies from your knowledge base. Your team approves in one click.
Built with
- CRM integration
- Ticket triage
- Draft replies
- Approval flow
Content AI
AI Content & Creative
On-brand copy, images, video and product shots generated at scale, with human review built in.
How it works
Models draft copy, images and video in your brand voice from briefs and templates, with style guides, review queues and approval before anything is published.
Built with
- LLMs
- Image & video models
- Brand guides
- Review queue
Analytics AI
Predictive Analytics & Insights
Forecasting, anomaly alerts and plain-language answers over your own business data.
How it works
We combine your data with forecasting models and language interfaces, so you can ask questions in plain English and get alerts when something looks wrong.
Built with
- Forecasting
- Anomaly detection
- Natural-language queries
- BI
Vision & Speech
Vision & Speech AI
Image recognition, transcription, meeting notes and real-time translation.
How it works
Models recognise objects in images and video, transcribe speech, summarise meetings and translate in real time, feeding results into your workflows.
Built with
- Computer vision
- Whisper
- Diarisation
- Translation
AI Strategy
AI Strategy, Training & Governance
Use-case audits, roadmaps, team workshops and guardrails so AI is adopted safely and pays back.
How it works
We audit use cases for value and risk, build a prioritised roadmap, train your team, and set the policies, evaluation and governance that keep AI safe.
Built with
- Use-case audit
- Roadmap
- Workshops
- Governance
Methodology
How we work with you.
Five clear phases, each with something concrete you can see and approve, so there are no surprises.
Discover
We list repeat tasks, measure what they cost, and pick the use cases with the clearest payback and lowest risk.
You receive: Use-case shortlist and ROI estimate
Design
We design the agent: its tools, data, guardrails, tone and where a person approves or takes over.
You receive: Agent design and guardrails
Build
We build with the right model, connect your systems, and test against real examples with an evaluation set.
You receive: Evaluated, integrated prototype
Launch
We roll out in stages, starting with a pilot group, with monitoring and rollback ready.
You receive: Staged rollout with monitoring
Grow
We watch accuracy, time saved and spend, tune prompts and retrieval, and extend to the next use case.
You receive: Quarterly improvement review
Technology
The tools behind it.
We choose proven, well-supported technology and avoid lock-in, so you can grow, change vendors or bring the work in-house.
Models
- Claude (Anthropic)
- OpenAI GPT
- Gemini
- Llama & Mistral
Agents & orchestration
- Claude Agent SDK
- LangGraph
- Tool calling
- MCP servers
Knowledge & retrieval
- pgvector
- Pinecone
- Embeddings
- Reranking
Voice & speech
- Vapi
- Retell AI
- Deepgram
- ElevenLabs
- Whisper
Automation
- n8n
- Make
- Zapier
- Playwright
- UiPath
Safety & ops
- Evals
- Prompt versioning
- Guardrails
- Observability
- Cost budgets
Results
How we measure success.
We agree the numbers that matter up front and report on them, so you can see the effect on your business rather than take our word for it.
Hours of manual work removed
The headline return: time your team gets back each week.
Resolution and containment rate
How many conversations the assistant resolves correctly without escalation.
Answer accuracy on an evaluation set
A fixed test set shows whether changes make the system better or worse.
Cost per task
Model and infrastructure spend per completed task keeps AI economics honest.
We choose per use case. Claude is often our first choice for reasoning, writing and tool use, with GPT, Gemini and open models where they fit better on quality, speed, cost or data-residency needs.
Keep exploring
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Ready to talk about ai integration & automation?
Tell us what you are trying to achieve. We will reply with a clear next step and an honest view of what it needs.