Ten layers, one team
Finance: Numbers before nouns
Every build starts from the numbers: what it costs, what it returns and what it puts at risk.
- Start with the case. Before we write a line of code we put numbers on it: what it costs, what it returns, and how soon.
- Price the risk. Technical, security and delivery risk, named and weighed up front, so decisions are made with open eyes.
- Build, buy, or don't. Total cost of ownership, honestly counted. Often the best system is a purchase, a smaller scope, or nothing at all.
Technologies: QuickBooks, Xero, NetSuite, SAP S/4HANA, Sage Intacct, Dynamics 365, Workday, Stripe, Microsoft Excel, Anaplan.
Most common techniques: ROI analysis; TCO modelling; NPV and cash-flow modelling; Scenario planning; Unit economics.
Consulting & Strategy: Right problem, shortest path
Many failed projects solved the wrong problem well. We make sure we are solving the right one.
- Question the brief. Most failed projects solved the wrong problem well. We interrogate the goal before we choose the solution.
- Read the room and the code. Independent review of architectures, vendors and plans: what is sound, what is fragile, and what to fix first.
- Diligence you can act on. A plain-spoken read on the true state of a codebase, a team and a stack, for leaders, investors and acquirers.
Technologies: TOGAF, ArchiMate, C4 model, SAFe, Domain-driven design, Wardley mapping, Miro, Confluence, Jira, Lucidchart.
Most common techniques: Discovery workshops; Architecture decision records; Technical due diligence; Risk registers and SWOT; Build-versus-buy analysis.
Product design: Taste you can use
Products and interfaces designed together with the engineering, so what gets drawn is what gets built.
- Start with the person. Flows are shaped around what people are trying to do, then tested as prototypes before engineering commits.
- Systems, not screens. Components and tokens that keep a product coherent as it grows and as the team changes.
- Designed with engineering. Designers and engineers work from the same constraints, so what is drawn is what ships: fast, accessible, and consistent.
Technologies: Figma, FigJam, Sketch, Storybook, Tailwind CSS, Radix UI, Framer, Lottie, Maze, zeroheight.
Most common techniques: User interviews; Usability testing; Personas and journeys; Heuristic evaluation; Design tokens.
Generative AI: Judgment over novelty
Agents, retrieval and knowledge systems where they earn their place, measured so you know they work.
- Does it need AI at all?. We decide whether a problem needs AI, and which approach is the simplest that works: prompting, retrieval, fine-tuning or agents.
- Agents that earn trust. Tool-using agents and retrieval over your own documents and data, wired into the software you already run, including AI for governance, risk and compliance.
- Measured, not hoped. Evaluation sets, LLM judges, regression tests and monitoring, so quality, cost and failure behaviour are known and stay known.
Technologies: Claude, GPT, Gemini, Llama, LangChain, LlamaIndex, Hugging Face, PyTorch, pgvector, Model Context Protocol, LLM-as-a-Judge.
Most common techniques: Prompt engineering; RAG; Fine-tuning (LoRA); Agents and tool use; Evaluation and guardrails.
Applications & websites: Fast, clear, built to change
Web, mobile and backend software on clear architecture, fast, accessible and built to be changed.
- Clear architecture. Web, mobile and backend software with boundaries that make sense, so the next engineer understands it on day one.
- Fast and accessible. Performance budgets and accessibility from the first commit. Slow or unusable software is broken software.
- Built to change. Tests, typed interfaces and small steps, so changing the product next year is cheap rather than frightening.
Technologies: JavaScript, TypeScript, Python, React, Node.js, Next.js, FastAPI, Java, C#, React Native, C++.
Most common techniques: API design (REST, GraphQL); Test-driven development; Clean architecture; Modular services; Core Web Vitals tuning.
Automation: Work that runs itself
Workflows, integrations and internal tools that remove repetitive work, and fail loudly instead of silently.
- Find the leverage. We look for the repetitive work where automation pays back fastest, and leave the rest alone.
- Connect everything. Workflows, integrations and internal tools that remove the hand-offs between the systems you already use.
- Fails loudly. Retries, alerts and monitoring on everything, so a failure is noticed in minutes, not months.
Technologies: Zapier, Make, n8n, Workato, Apache Airflow, Temporal, Prefect, Camunda, GitHub Actions, UiPath.
Most common techniques: Event-driven workflows; RPA; ETL and ELT pipelines; API orchestration; Idempotent retries.
Database administration: The data you cannot afford to lose
Data designed, tuned and protected so it stays correct, fast and recoverable as you grow.
- Designed for your questions. Schemas and indexes shaped around real access patterns, with integrity enforced by the database itself.
- Fast, and kept fast. Query analysis, tuning and capacity planning before slowness becomes an outage.
- Safe to lose a server. Backups you have actually restored, replication and careful migrations, so the data survives the bad day.
Technologies: PostgreSQL, MySQL, SQLite, SQL Server, Redis, MongoDB, MariaDB, Oracle, Elasticsearch, Snowflake.
Most common techniques: Index design and query tuning; Point-in-time recovery; Replication and HA; Zero-downtime migrations; Partitioning.
Operations: Stays up
Deployment, observability and the day-two reality of running software, so your team can keep it healthy.
- Ship safely. Automated build, test and release turn deployment into a routine, not an event.
- See everything. Logs, metrics, traces and alerts that tell you something is wrong before your customers do.
- Runnable by your team. Runbooks, on-call practice and documentation, so the system never depends on us.
Technologies: Kubernetes, Docker, Terraform, GitHub Actions, Argo CD, Jenkins, GitLab CI, Helm, Prometheus, Grafana.
Most common techniques: CI/CD pipelines; Infrastructure as code; GitOps; Observability; Incident response and SLOs.
Cybersecurity: Secure by design
Security treated as part of the architecture from the first day, not a review bolted on at the end.
- Threat model first. We map what could go wrong and who might cause it, then spend effort where the risk really is.
- Hardened by default. Least privilege, strong authentication and managed secrets from the first day, not retrofitted.
- Compliance without theatre. Controls and evidence that satisfy auditors because they are real, not paperwork laid on top. Our experts have brought industry-leading GRC intelligence to multiple Fortune 500 financial organisations.
Technologies: OWASP Top 10, MITRE ATT&CK, NIST CSF 2.0, ISO 27001, SOC 2, CIS Controls, OAuth 2.0 / OIDC, Okta, HashiCorp Vault, Burp Suite.
Most common techniques: Threat modelling (STRIDE); Zero Trust architecture; Defence in depth; Penetration testing; Least privilege.
Network engineering: The quiet foundation
The connectivity everything else depends on, designed simply and sized to what you actually need.
- Foundations. Topology, addressing and segmentation designed simply, so the network is understandable and secure.
- Connected and fast. Cloud, on-premise and hybrid connectivity, with latency, throughput and resilience planned in.
- Sized to need. Infrastructure that fits today's demand with a clear path to growth, not an expensive guess.
Technologies: BGP, OSPF, VXLAN, IPsec, WireGuard, SD-WAN, Cisco IOS, Juniper Junos, Wireshark, Ansible.
Most common techniques: Network segmentation; Redundant routing; VPN and zero-trust access; Network automation; Traffic monitoring.