Technology,
engineered to compound.
Platforms, developer tools, SaaS, AI-native products and modern infrastructure, engineered as one integrated engineering practice so the product that finds PMF compounds instead of falling over the week it finds it.
The territory, in four numbers we hold ourselves to.
Technology is judged by product velocity, unit economics and reliability. These are the numbers we design against.
- 1–2
- Weeks
- 6–10
- Weeks
- SLOs
- As a discipline
- $/user
- Engineered
Release cadence on real product teams we run
To first paying customer or measurable outcome
Not as a document that ages
Unit economics visible and negotiable, not surprises
The technology-company formats we build for.
Technology companies span a family of distinct businesses, SaaS, marketplace, platform, developer tools, deep tech. We tailor architecture and delivery to the shape of the company you actually are.
B2B SaaS
Multi-tenant SaaS platforms with enterprise readiness, expansion revenue and predictable unit economics.
Consumer & B2C
Consumer platforms with viral loops, retention engineering and mobile-first experiences.
Marketplaces & platforms
Two-sided marketplaces, platform businesses and network-effect products engineered for both sides.
Developer tools & infrastructure
Developer products, DevOps tools, observability and infrastructure engineered by developers for developers.
AI-native startups
GenAI-first products, agents and AI-driven workflows engineered with evaluation and guardrails from day one.
Deep tech & industry vertical
Vertical SaaS and deep-tech products engineered against the reality of the sector they serve.
Services we deliver into technology companies.
Every technology-company engagement blends product engineering, AI, data, cloud and integration. These are the practices we most commonly deploy for SaaS, platforms, developer tools and AI-native startups, each linked to its dedicated practice page.
The technology-company estate we engineer end to end.
The technology companies that compound are the ones that treat product, platform, data, AI and operations as one integrated system, designed by one team, shipped on one rhythm.
- 01Product engineering
- Zero-to-one and scale product engineering, with the design, front-end, back-end, data and platform disciplines integrated in one team.
- 02SaaS foundations
- Tenancy, identity, entitlements, billing and telemetry engineered as the substrate every SaaS platform sits on.
- 03AI-native features
- AI features where they change customer outcomes, with retrieval, evaluation, guardrails and honest scope from day one.
- 04Platform engineering & DevOps
- Internal developer platforms, paved roads, CI/CD, observability and SRE that make shipping every week the default.
- 05Enterprise readiness
- SSO, SCIM, audit, private connectivity, regional isolation and SOC-2-aligned controls engineered as product surfaces.
- 06Data, analytics & experimentation
- Product analytics, experimentation and semantic layers that answer product questions rather than vanity ones.
Trusted by product leaders, CTOs and founders.
A representative sample of the SaaS, platform, developer-tools and AI-native companies we've engineered with.
Programmes delivered in this sector.
What clients ask us first
01Zero-to-one, or scale, which do you actually do?
Both, but we're honest about the difference. Zero-to-one is about finding the wedge, cutting scope brutally and building an architecture that survives PMF without over-engineering for it. Scale is about performance, reliability, cost, hiring and operating model. The engineers, cadence and tools shift between those phases, we name which one you're in and act accordingly.
02How do you engage, team, staff or full product?
Whatever fits. Embedded integrated team when a company is going zero-to-one and needs the full stack. Staffed specific capabilities when the team needs shape, not volume. Full product delivery when your own delivery capacity is the constraint. In every model the engineers are the same senior ones, not a bench roll.
03How do you handle AI in a startup honestly?
As a product decision, not a technology decision. If AI genuinely changes a customer outcome, draft-and-review, extraction, semantic search, agentic operations, we design it in from day one with evals, guardrails and clear failure modes. If it's a marketing sticker on the roadmap, we say so.
04How do you handle enterprise readiness for SaaS?
As engineered surfaces, not a checklist ticked before an enterprise deal. SSO, SCIM, audit logging, private connectivity, regional isolation and SOC-2-aligned evidence are designed alongside product surfaces. That is usually the difference between a SaaS enterprise motion that lands and one that stalls at security review.
05How do you handle handover so we can run the product ourselves?
Knowledge transfer, hiring plan and internal capability building are designed into the engagement from the first week, not appended after go-live. Engineers pair with yours, decisions are recorded in the code, and by the time the engagement scopes down your team owns the product technically, culturally and operationally.
Let's discuss your technology programme.
Share a brief overview of the product, systems and outcomes you're chasing, we'll arrange an introductory conversation with the relevant practice leadership.