Work Smarter.
Automate the Rest.
Intelligent automation and AI integration — from workflow bots and LLM pipelines to custom agent architectures. We help teams move faster by automating the repetitive, connecting the disconnected, and embedding intelligence where it adds the most value.
AI & Automation Capabilities
From simple API glue to full agentic architectures — we build automation and AI solutions that fit your actual workflows, not generic demos.
LLM & Agent Pipelines
Designing and implementing language model pipelines using OpenAI, Anthropic Claude, Mistral, or open-source models — from simple prompt-response flows to multi-step agentic architectures with tool use, memory, and structured output parsing.
- Multi-step agentic workflows with tool use
- Structured output & JSON schema enforcement
- Model selection & cost optimisation
Workflow Automation
End-to-end automation of repetitive business processes using n8n, Zapier, Make, or custom-coded pipelines — connecting your CRMs, CMSs, spreadsheets, and APIs into seamless automated flows that run without human intervention.
- Trigger-based automation across any API
- CRM, CMS & spreadsheet integrations
- Error handling & retry logic built in
AI-Powered Content Generation
LLM-driven content pipelines that generate, transform, classify, or summarise content at scale — structured for CMS ingestion and configured to match your brand voice. Ideal for product descriptions, SEO content, and translation workflows.
- Bulk generation with brand voice guardrails
- CMS-ready structured output (JSON, CSV)
- Translation & multilingual content pipelines
Chatbots & Conversational Agents
Custom chat interfaces and conversational AI agents — FAQ bots, customer support assistants, and internal knowledge base assistants backed by your own data via retrieval-augmented generation (RAG). Embeddable in any website or product.
- RAG with your own documents & knowledge base
- Embeddable widget or API endpoint
- Conversation history & context management
API & Data Integration
Connecting AI tools, third-party APIs, and data sources into coherent pipelines — feeding data into a model, reading AI outputs back into a database, triggering downstream workflows based on AI decisions, or syncing between platforms in real time.
- REST & GraphQL API orchestration
- Webhook event processing
- Data transformation & normalisation
AI Audits & Strategy
A structured review of where AI can deliver genuine value in your business — not hype-driven. We identify use cases with real ROI, realistic implementation timelines, and the right level of tooling, then help you prioritise what to build first.
- Use-case identification & ROI estimation
- Build vs buy vs API analysis
- Phased automation roadmap
What Sets Us Apart
A lot of AI work is demos that never ship. We build production systems that run reliably, integrate cleanly, and are maintained by real engineers.
We Build, We Don't Just Prompt
Our team writes code, not just prompt templates. Every pipeline we deliver is a real software system — versioned, tested, documented, and deployable to your own infrastructure. You own the output, with no dependency on our tooling to keep it running.
Practical, Not Experimental
We're not here to sell you the shiniest new model. Every recommendation we make is grounded in what actually works in production — appropriate model selection, predictable costs, graceful failure handling, and data privacy considerations thought through from the start.
Integrated Into Your Stack
We don't deliver standalone scripts that need a data scientist to maintain. Our pipelines integrate with your existing CMS, CRM, databases, and APIs — built to the same engineering standards as the rest of your platform, with proper error handling and monitoring.
Transparent About Limitations
We'll tell you when LLMs are the wrong tool — and recommend a simpler, cheaper, more reliable solution. Our goal is to solve your problem efficiently, not to bill hours implementing AI for its own sake. That honesty builds better long-term relationships.
Recent Projects
A selection of AI and automation projects — from quick workflow wins to fully custom agentic pipelines built for production.
Real-Time IoT Data Platform
How we helped an industrial technology company turn isolated hardware data into a connected digital ecosystem — in weeks, not months.
Read Case StudyMeeting Intelligence Platform
How we helped a consulting firm automate meeting documentation — from hours of manual work to minutes — in 4 weeks.
Read Case StudyContainerized AI Tooling Infrastructure
A digital agency needed AI-powered tools in their workflow — without the dependency chaos. We containerized everything with Docker and MCP, cutting developer onboarding from 2–3 days to 30 minutes and eliminating dependency conflicts entirely.
Read Case StudyFrom Brief to Running Pipeline
Five stages, every engagement — so you know what you're getting, what it costs, and when it ships, before we write a single function.
Discovery & Scoping
A focused session to understand the problem, the data sources involved, and what success looks like. We scope the engagement, confirm the right approach, and produce a fixed-price brief before any work starts.
Data & Integration Mapping
Audit of your data sources, APIs, authentication flows, and output destinations. We identify data quality issues, access constraints, and privacy considerations before the pipeline design is finalised.
Pipeline Build & Testing
Iterative build with regular checkpoints — prototype outputs reviewed with your team, prompts and logic tuned against real data, edge cases handled explicitly. All code committed to a repository you own throughout.
Integration & Deployment
Pipeline deployed to your infrastructure — cloud function, VPS, or your existing platform — with environment variables, API keys, and scheduling configured. End-to-end smoke test run against production data before handover.
Monitoring & Iteration
Error alerting, run logs, and cost monitoring configured from day one. Post-launch support window included. Ongoing iteration — prompt tuning, new data sources, expanded workflows — available on a retainer or fixed-scope basis.
Our AI Stack
The models, frameworks, and platforms we use to build automation and AI systems — selected for reliability, cost-effectiveness, and ease of ongoing maintenance.
LLM Providers
Orchestration & Agents
Workflow Automation
Vector & Memory
Backend & Runtime
CMS & Output Targets
Related Articles
These articles come directly from problems we encountered on real client projects. When we solve something worth sharing — a rate-limiting pattern, a deployment edge case, an integration approach that saved significant time — we write it up. No contrived examples; everything here was discovered in production.
Orchestrating AI Pipelines with Celery: Rate Limits, Retries, and Failure Handling
How I built a resilient job processing system for chained AI service calls
How to Dockerize MCP Servers for Claude Desktop: A Complete Guide
Stop polluting your host system with AI tool dependencies. Here's how to run every MCP server in isolated Docker containers.