Product Engineering Services for Software Companies in the US & EU

Builds are fixed-scope and tiered by type, all-in and quoted in USD. A landing or small build runs from $1,100; a corporate site or internal system from $2,900; an online store or marketplace from $5,800; a portal or web service from $10,400. The exact number depends on the number of sections and roles, the integration count (payments, delivery, CRM, third-party APIs), complexity of business logic and compliance scope. You see the line-item budget after a free scope assessment and sign off before any code is written — no recruitment markup, no tool surcharges, and cloud and third-party fees run on your own accounts.

Product engineering is an outcome-owned engagement: a cross-functional pod (PM, designer, full-stack engineers, QA, DevOps, SRE) takes accountability for a product surface or a whole product and is measured on product KPIs — activation, retention, NPS, lead time, deploy frequency. Staff augmentation is the opposite: you rent named seats and your team owns priorities, design, QA and ops. Product engineering reduces handoffs and management load on your side; staff aug gives you more direct control over each engineer's day.

During discovery we agree on two layers of metrics. Product KPIs are tied to the product's north-star — activation, retention, conversion, NPS, revenue per user, time-to-value. Engineering KPIs cover delivery hygiene — lead time for changes, deploy frequency, change-failure rate, MTTR. We report both monthly and tie pod composition and roadmap decisions to those numbers. The KPI set is co-owned with your product leadership and revisited every quarter.

Default model: our PM leads the pod and works in lockstep with your product leadership; our designer owns UX and design system; our tech lead owns architecture. You keep final say on roadmap, scope and release. If you already have a strong PM in-house, we can drop our PM role and run the pod under your PM — in that case we replace the PM seat with an additional engineer or designer at the same fully-loaded rate.

Every engagement opens with a one-to-two-week discovery: product narrative, north-star metric, target users, scope of the first release, success criteria, architecture sketch and risk log. The output is a written engagement charter that we both sign. Design runs ahead of engineering by one sprint in a shared Figma library with design tokens. Discovery is fixed-price; if you decide not to proceed after discovery, you keep all artefacts and there is no obligation to continue.

Most product engineering engagements run 9–24 months. The shortest are 6-month new-product builds — discovery, MVP, public launch, first 90 days of operate. The longest are multi-year platform partnerships where the pod owns a product surface across several major releases. We do not take engagements shorter than six months, because product KPIs cannot be moved meaningfully in less time, and a shorter engagement is better served by our dedicated team or custom development offering.

All pods are GDPR-aligned by default: EU data residency, EU-based contracts, DPAs on request, sub-processor register. SOC 2 Type II is in progress. HIPAA-capable scoping is available for health workloads — BAAs, encrypted PHI handling, audit trail. CCPA notice obligations are acknowledged for US consumer data and we align with your privacy notice. ISO 27001 controls are applied to repos, endpoints and access. For payments we run inside PCI DSS scope and align with your QSA.

Scope changes are normal in product engineering; the process for handling them is what matters. Between sprints, you can reprioritise the backlog freely — the pod plans the next sprint against whatever is at the top. Inside a sprint, we do not accept scope changes as a rule: mid-sprint pivots destroy flow, inflate defect rates and make velocity measurement meaningless. For genuinely urgent changes that cannot wait one to two weeks, we use a controlled sprint-interrupt process: the PM evaluates impact-to-effort, drops equivalent-weight items from the sprint, and the change is tracked as a sprint interrupt in the retrospective so patterns can be addressed in planning.

The minimum viable pod for a product engineering engagement is four people: a PM, a designer, two engineers. Below that headcount, a pod cannot maintain the discovery-one-sprint-ahead rhythm, run meaningful code review, or handle on-call rotation. If you need one or two engineers to work against your existing PM and design, that is better served by our dedicated development team offering. The most common starting pod is five to six people, scaling to eight to twelve at peak build phases.

We do not impose a stack. If you have an existing codebase or a strong technology preference, we build on it. Our default recommendation for new products starts with the technology that the largest pool of senior engineers can maintain, and that has the lowest operational overhead for the product's scale. In practice: React or Next.js for web frontends, React Native for cross-platform mobile, Node.js or Python for APIs where speed of iteration matters, Go for services where throughput matters, and PostgreSQL as the default relational store. We avoid framework churn; the stack the pod ships in year one should be the stack a new engineer can hire into in year three.

Handoff is a structured process, not a file dump. We allocate the final 6 to 8 weeks of an engagement to knowledge transfer: architecture decision records documented in the repository, runbooks tested by your team against live systems, on-call shadowing where your engineers carry pagers alongside ours, and a final architecture review where your team leads ask the hard questions. All IP transfers to you on creation under the master services agreement — we hold no retention rights on code, data or documentation. The goal is that on day one after handoff, your team can ship, respond to incidents and make architectural decisions without calling us.

Both, but the engagement shape differs. With early-stage startups, discovery is longer and the charter is lighter — we help define what the first release should be, not just how to build what is already specified. The pod starts at the minimum four-person configuration and scales as funding and product-market fit signal determine. With established companies, we typically step into an existing product with a defined backlog, existing infrastructure and a team to complement. The most common reason an established company brings in a product engineering pod is to accelerate a specific product surface while keeping the internal team focused on core-platform work.