Claritas One

Enterprise Product Engineering

We provide embedded product engineering capabilities that accelerate the roadmaps of enterprise product organisations — from concept validation through scaled delivery — operating as an extension of your engineering leadership rather than a conventional outsourcing vendor. Velocity, quality, and institutional knowledge transfer in every engagement.

Roadmap velocity vs. equivalent in-house hiring timeline
85%+
Automated test coverage target on all delivered codebases
< 2 weeks
Time to productive squad contribution from engagement start
92%
Client re-engagement rate for follow-on product programmes

Enterprise product organisations face a structural tension: the engineering capacity required to execute a competitive roadmap typically exceeds what can be sustainably hired, onboarded, and retained within budget constraints — particularly in specialist domains like AI, data infrastructure, and mobile. Offshore outsourcing models solve the capacity problem but create a quality, knowledge-transfer, and communication overhead that often consumes 30-40% of the efficiency gain. Our product engineering practice is designed for organisations that need senior engineering capability at scale without the overhead of traditional outsourcing: embedded squads that operate inside your development process, align to your engineering standards, and transfer architectural knowledge to your permanent team throughout the engagement.

Our approach

01

Product Discovery & Technical Feasibility

We conduct structured product discovery sessions with your product, design, and engineering leadership to validate assumptions, define the MVP scope with precision, and produce a technical feasibility assessment that surfaces architectural risks before a single line of production code is written.

02

Architecture Design & Engineering Standards Alignment

Our engineering leads work alongside your technical leadership to design a system architecture that meets your performance, scalability, and security requirements — and that your permanent engineering team can maintain and extend confidently after the engagement concludes. We align to your existing engineering standards, not our own defaults.

03

Agile Delivery & Embedded Squad Operation

We operate embedded squads inside your delivery process — participating in sprint planning, daily standups, code review, and retrospectives as first-class team members. Velocity benchmarks are established in week two and reported transparently through your existing project governance framework.

04

Quality Engineering & Test Automation

Automated test coverage — unit, integration, and end-to-end — is built alongside features, not retrospectively. We implement contract testing for service boundaries, performance benchmarking in CI, and accessibility testing automation so that quality is a continuous property of the codebase, not a gate at the end of a sprint.

05

Knowledge Transfer & Engineering Handoff

Every engagement concludes with a structured knowledge transfer programme: architecture documentation, runbook creation, system administrator training, and a 90-day post-handoff support retainer. Your permanent team inherits a codebase, a test suite, and the architectural context required to own it.

Core capabilities

Embedded engineering squads operating inside your delivery process and standards
Technical architecture design with long-term maintainability as a primary constraint
Full-stack engineering: React, Next.js, Node.js, Go, Python, and cloud-native services
Automated test suite engineering: unit, integration, contract, and end-to-end coverage
Performance benchmarking and load testing with production SLA validation
Accessibility engineering to WCAG 2.1 AA compliance
DevSecOps pipeline implementation with SAST, DAST, and dependency scanning
Structured knowledge transfer with architecture documentation and team coaching

Accelerate Your Product Roadmap With Senior Engineering Capacity

Our engineering leadership will review your roadmap priorities and team structure to design an embedded squad model that delivers maximum velocity with minimum management overhead.

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