Build & Ship
Embed the AI agents that fix the bottlenecks.
We embed AI agents into your delivery workflow — code reviews, test generation, requirement validation, deployment checks. And we build the products and tools that run on the infrastructure we help you create. Engineers review, refine, and own what ships; agents handle the first pass.
- Individual productivity is up, but specs, handoffs, and review cycles still eat most of your cycle time
- AI tools adopted but not embedded in the workflow — no agents fixing the bottlenecks between roles
- No clear picture of where to embed agents: code review, tests, requirements, deployment
- Proof of concepts that never reached production or never got measured
- Engineering teams using Copilot and Cursor but the handoff chain is unchanged
- You want to ship value faster — and know which agents to embed first
The issue isn't more AI tools. It's embedding agents where they fix the bottlenecks — and building the operating model so people orchestrate them. We start with an assessment of where your delivery is held back, then we embed agents into the workflow and measure the difference.
We build the products and tools that run on the infrastructure we help you create. Assessment, pilot, results you can measure.
AI Readiness Assessment
A structured evaluation of your current workflows, data landscape, team capabilities and tech stack — designed to identify where AI will create the highest return, and where it won't.
No generic maturity matrices. We map your actual processes, find the friction, and quantify the opportunity.
- Workflow mapping and bottleneck analysis
- Data readiness and quality audit
- Team capability and skills gap review
- Prioritised opportunity backlog with ROI estimates
- Governance and compliance risk assessment
Workflow Automation & AI Integration
Designing and building AI-powered workflows that connect to your existing tools and processes. We work with what you have — not rip-and-replace.
From document intake and triage to automated reporting, approval chains, and intelligent routing.
- Process automation with n8n, Make, Zapier or custom pipelines
- API integrations with your practice management and CRM systems
- Document processing and intelligent extraction
- Automated quality checks and compliance monitoring
- Human-in-the-loop design for high-stakes decisions
Generative AI Enablement
Helping teams use large language models effectively — not just ChatGPT in a browser, but structured GenAI workflows embedded into daily work with proper guardrails.
We build the prompts, the pipelines, and the training so your people can use AI confidently and consistently.
- Custom GPT and LLM agent development
- Prompt engineering frameworks for your domain
- RAG (Retrieval Augmented Generation) over your documents
- Content generation, summarisation and analysis pipelines
- Team training and adoption programmes
Machine Learning & Predictive Analytics
When pattern recognition, prediction or classification can drive better decisions — we build the models, connect them to your data, and make the outputs actionable.
Practical ML applied to real business problems, not research projects.
- Predictive modelling for demand, risk or churn
- Classification and anomaly detection
- Natural Language Processing for unstructured data
- Computer vision for document and image analysis
- Model monitoring, retraining and governance
Large Language Models
OpenAI GPT-4o, Anthropic Claude, Google Gemini, open-source models via Ollama and Hugging Face. We match the model to the task.
Automation Platforms
n8n, Make, Zapier, custom Python pipelines. From simple triggers to complex multi-step agentic workflows with error handling and logging.
Integration & APIs
REST, GraphQL, webhooks and middleware. We connect AI to the systems you already use — CRMs, ERPs, practice management, document stores.
Data & ML Platforms
Python, scikit-learn, TensorFlow, PyTorch. Supabase, PostgreSQL, vector databases for embeddings and semantic search.
Cloud & Infrastructure
Azure, AWS, Vercel, serverless architectures. UK data residency options for regulated industries. SOC 2 and GDPR compliant patterns.
Governance & Security
Data loss prevention, prompt injection protection, audit trails, role-based access. Enterprise-grade security from day one — not bolted on later.
What are multi-agent systems?
Instead of one general-purpose AI doing everything, multi-agent systems decompose complex work into specialised roles. Each agent is purpose-built for a specific task — planning, coding, reviewing, testing, deploying — and they communicate through structured handoffs, just like a high-performing team.
The orchestrator agent coordinates the flow: it decides which agent to invoke next, handles exceptions, manages feedback loops, and ensures quality gates are met before work moves forward.
The result: faster delivery, higher quality, continuous feedback loops, and human oversight exactly where it matters most.
How this plays out
A feature request enters the system. The Orchestrator parses the requirement and activates the Planning Agent, which breaks "JWT auth with refresh tokens" into discrete tasks: token generation, refresh rotation, middleware, database schema, and API endpoints.
The Architecture Agent evaluates the task list, selects an asymmetric key strategy (RS256), designs the token lifecycle, and defines the API contract. It produces a technical spec the Coding Agent can execute against.
The Coding Agent implements across multiple files — auth middleware, token service, refresh endpoint, database migration. It follows the architecture spec and project conventions automatically.
The Review Agent scans for security vulnerabilities, checks token expiry handling, validates error cases, and verifies the refresh rotation prevents replay attacks. Issues get fed back to the Coding Agent.
The Testing Agent generates unit and integration tests, including edge cases like expired tokens, concurrent refresh attempts, and revoked sessions. The DevOps Agent deploys to staging, and the Monitoring Agent watches for anomalies.
Concept to prototype
We help you shape the idea — what problem are you solving, who for, and what does "done" look like? Then we build fast: a working prototype that you can test with real users, not a slide deck.
Production-ready MVP
From validated prototype to a product you can ship and sell. We handle architecture, build, and iterative delivery — using AI tools to move at a pace that was previously impossible for a small team.
AI-powered products
We've built AI-powered platforms, product lifecycle toolkits, and SaaS products from scratch. We know where AI creates genuine leverage in a product — and where it's a distraction.
Build alongside your team
We work as an extension of your team, not a separate contractor. Knowledge transfers as we go. By the time we're done, your team can own, maintain, and extend what we've built together.
We've built AI-powered platforms, product lifecycle toolkits, and SaaS products from scratch — by people who blend product thinking, design, and engineering themselves. See what we've built →
See where the leverage is
We start with an operating model assessment: how your roles work today, where AI is speeding up tasks, and where the structure and tooling are holding back delivery. Then we restructure one team, embed AI agents into the workflow, and measure the difference. No six-month engagement. An assessment, a pilot, and results you can measure.
Book an Assessment