Everything your business
needs online, engineered.
Websites, e-commerce stores, AI agents, and digital marketing — all built with the same engineering discipline. No templates, no guesswork, no deliverables that don't ship.
We build websites for real estate agencies, service businesses, hospitality, and B2B companies that need a site that actually does something — not just looks good in a Figma preview.
Every site is built with performance, SEO, and conversion in mind from the first line of code. Not bolted on after launch.
What we build
- Marketing and landing page sites for service businesses
- Real estate agency websites with listing search and lead capture
- B2B lead-gen sites with CRM and calendar integrations
- Web applications with custom logic, auth, and APIs
- Speed and conversion audits for existing sites
What you get
- Core Web Vitals scores that actually pass (not "close enough")
- On-page SEO structure — metadata, schema, internal linking — from day one
- CMS setup so your team can update content without us
- Analytics and goal-tracking configured and verified
- Documentation and 30-day post-launch support
We've built e-commerce platforms that have scaled to multi-million dollar, multi-country operations. The architecture decisions at the start matter — we've learned which ones cause problems at scale.
Whether you're launching a new store or fixing one that's slow, leaky, and hard to manage — we build it right.
What we build
- New Shopify, WooCommerce, or custom storefronts
- Performance rebuilds of existing stores (often 2–5× speed improvement)
- Multi-currency and multi-country setups
- Custom checkout flows, loyalty programs, and subscription products
- Third-party integrations: ERP, 3PL, CRM, PIM
What you get
- A store that loads fast — under 2s on mobile, which directly lifts conversion
- Checkout optimised to reduce abandonment
- Scalable architecture that doesn't break under traffic spikes
- Analytics configured: revenue attribution, funnel visibility, AOV tracking
- Handoff docs and team training so your team can run it
Digital marketing run like a software sprint — with hypotheses, tests, metrics, and retrospectives. Not "we boosted your brand presence" reports that explain why nothing moved.
We work best with clients whose websites or stores we've built — we know the stack, we can make changes fast, and we own the full funnel from click to conversion.
What we run
- Technical SEO: site structure, crawlability, Core Web Vitals, schema markup
- Content strategy and on-page optimisation for target keywords
- Google Ads: search, shopping, and performance max campaigns
- Meta Ads for e-commerce and lead generation
- Conversion rate optimisation — landing page testing, checkout tuning
How it works
- Starts with an audit: technical, keyword, and competitive
- Prioritised action list: what to fix, what to build, what to test
- Monthly sprints with clear objectives and reported outcomes
- No lock-in — monthly engagements, cancel any time
How AI agent
engagements work.
AI agents are a distinct discipline with their own engagement model. Every build starts with an Audit, moves into a Pod or Custom Platform, and is supported by an optional ongoing retainer.
The Audit exists for the most common situation we see: leadership knows AI should be doing more in the business, but isn't sure where it pays off, what to build, or whether to build vs. buy.
In two weeks we map your workflows, identify the 3–5 highest-ROI agent candidates, and give you a ranked recommendation with rough scope, integration paths, and build-or-buy guidance for each.
What you get
- A workflow audit of 2–4 functions you nominate (sales, support, ops, etc.)
- A ranked map of 3–5 agent opportunities with estimated ROI for each
- Architecture sketches for the top 2 opportunities
- Build-or-buy guidance — including when an off-the-shelf tool is the right answer
- A kickoff scope ready to green-light if you want to move forward
- A 60-minute readout with your leadership team
How it runs
- Week 1: discovery interviews with the teams doing the work today
- Week 2: synthesis, ROI modeling, and the deliverable
- Roughly 4–6 hours of your team's time across the two weeks
What it isn't
- A McKinsey deck. The deliverable is short, specific, and operational.
- A sales pitch. About 40% of audits end with us recommending an off-the-shelf product, an internal hire, or doing nothing.
Agent Pods are our productized builds — specific agents for specific job functions. Sales triage, support copilot, document review, knowledge base, listing moderation, and more.
Each pod is built from a proven blueprint we've shipped before, customized to your stack and data. That's how we get to 4–8 week timelines without cutting corners on the engineering.
What you get
- A production-deployed agent running in your stack
- Integrations with your tools (CRM, helpdesk, data warehouse, etc.)
- An evaluation set tuned to your real data and edge cases
- Monitoring dashboards (latency, cost, accuracy, escalation rate)
- Team training and full documentation
- 30 days of post-launch tuning and bug fixes included
How it runs
- Week 1: discovery, data access, eval set definition
- Weeks 2–4: build & iterate against the eval set
- Weeks 4–6: shadow run with your team, refine
- Weeks 6–8: production launch, monitoring, handoff
The 18 pods we offer today
Browse the full library on the agents page — each one has its own timeline and example outcomes.
Custom Platforms are for when a Pod isn't enough — multi-agent systems, bespoke RAG architectures, custom UIs, complex integrations, or proprietary workflows that don't fit a template.
Every Custom Platform engagement starts with an Audit. We need a clear scope before either of us signs up for a multi-month build — and you need to know we're the right team before betting six figures on it.
What you get
- A bespoke multi-agent system or AI platform built around your business
- Custom UIs, internal tools, or end-customer-facing features
- Architecture documented for your engineering team
- Full eval and observability stack
- Knowledge transfer so your team can extend it
- 60 days of post-launch support
How it runs
- Always starts with a 2-week Audit (scoped separately, credited toward the build)
- Months 1–2: foundations, core agents, integrations
- Months 2–4: workflows, UIs, evals
- Months 4–6: shadow run, refinement, production launch
- Bi-weekly steering check-ins with your leadership
When this makes sense
- You have a workflow that's truly novel — no off-the-shelf agent maps to it
- You need multiple agents that coordinate
- You want a customer-facing AI surface that needs to be designed, not just engineered
- You're committed to AI as core infrastructure, not just an experiment
AI agents aren't ship-and-forget. Models change. Data drifts. Your business changes. A retainer keeps the system tuned and improving.
Most clients who ship a Pod or Platform with us move into a retainer after the 30/60-day included support window ends. About a third don't — and that's fine.
What's included
- Ongoing eval monitoring — we catch quality regressions before your team does
- Cost and performance optimization (often pays for itself)
- Model upgrades when better ones ship
- Small feature additions and tuning based on user feedback
- Monthly report on what changed, what's working, what to improve
What buyers always ask.
It depends on the architecture. For most builds we use API calls to enterprise model providers (Anthropic, OpenAI, Azure) with zero data retention enabled and SOC 2 / HIPAA-compliant deployments. For more sensitive cases we can deploy fully on your infrastructure using open-weight models. We make the call together during the Audit or scoping conversation.
You do. All code, prompts, eval sets, and documentation produced during the engagement transfer to you on delivery. We retain the right to reuse generic patterns and our internal tooling — not your business logic, prompts, or data.
The Audit is the safety mechanism. If after the Audit we don't think a build will hit the ROI you need, we'll tell you and you walk away with a clear picture of why. For builds, we agree on success metrics in the kickoff scope — measured against the eval set — and we don't call it done until we hit them.
Yes — and most of our clients do, eventually. We build with handoff in mind: documented code, runbooks, eval frameworks, and team training. The retainer is optional. We'd rather have you happy and self-sufficient than locked in and resentful.
We're engineers first — that's the whole point. We work with whatever you have: REST APIs, GraphQL, SOAP, databases, on-prem systems, custom auth, weird legacy stuff. The Audit confirms feasibility before either of us commits to a timeline.
Third-party costs (model API tokens, vector DB hosting, infrastructure) are passed through at cost. Major scope changes mid-engagement are handled via a change order. We don't do generic strategy consulting, AI training programs, or build things we don't think you should build.
We build and ship. Most AI consultancies stop at the deck. We stop when there's a working agent in your production stack that's tested, monitored, and accepted by the team that has to live with it. The 12+ years of production software engineering is what makes this possible — it's not the LLM that's hard, it's everything around it.
Yes. Mutual NDA is standard before the Audit. We also have a one-pager on our security practices, ZDR setups, and data handling we can share alongside it.
Not sure
where to start?
Tell us what you're trying to build or fix — website, store, AI system, or marketing. We'll recommend the right starting point and scope it honestly.
Let's talk →