AI-NATIVE OUTSOURCED DEVELOPMENT
AI-native engineers shipping on your roadmap in as little as 2 weeks
NexaQuanta’s outsourced software development pods embed in your team on an Agentic SDLC, led by a named Delivery Manager.
Why do outsourced developers add headcount but not speed?
Most technology partners adopted AI because the market demanded it. They bolted it onto delivery models built before it existed. You pay for more engineers, yet code is still written, tested and documented the old way.
Seniority and cost drift once the contract is signed. Contractor arrangements leave the IR35 questions with you. That’s why clients come to NexaQuanta after earlier partners haven’t delivered.
NexaQuanta was built AI-native from day one, with a dedicated AI practice. Our software engineers, data specialists, AI practitioners and architects work as one delivery organisation. That shapes how we design solutions, how fast we reach value and how long the architecture lasts.
What our engineering pods build
AI-native thinking runs through all three practices. It changes how products are designed, how data platforms are structured and how workflows get built.
Product and software engineering
We build and modernise software that holds up at scale. Every build runs on an Agentic SDLC, on AWS, Azure or Google Cloud.
- SaaS product development and platform build. From concept to production, built to scale and maintained over time.
- Application modernisation and legacy migration. Ageing systems moved to a maintainable architecture while live operations keep running.
- Embeddable plugins and feature extensions. New intelligent capability added to existing software, with no full rebuild.
- API development and third-party integrations. REST, GraphQL, microservices, SnapLogic and Zapier, connecting systems so data flows cleanly.
- Frontend, backend and full-stack development. Senior engineers working in your environment and to your standards.
- QA, test automation and performance engineering. Automated regression and load testing as standard, across multiple frameworks.
- Technical architecture and delivery leadership. Senior architects for design review, governance and programme oversight, on a fractional basis.
Data engineering
Many businesses hold value in their data they can’t yet use. We turn fragmented data estates into decision-ready insight and infrastructure that AI can consume.
- Data migration, aggregation and unification. Disparate sources brought into one consistent, schema-aligned model.
- Warehouses, lakes and lakehouse architecture. Structured for reporting and AI consumption alike.
- Real-time analytics and visualisation. From operational dashboards to board-level reporting.
- Data governance, lineage and compliance. Full auditability from source to analytical layer, built in from the start.
- AI-ready data pipelines. Built to feed machine learning and generative AI applications reliably.
Agentic and generative AI
Our dedicated AI practice takes AI from strategy through to production, scaling and governance. Capabilities include agentic AI, generative AI, machine learning and computer vision. For SaaS vendors, we also embed agentic features directly into your product.
Pick the engagement model that fits
Every model comes with a dedicated Delivery Manager and Engineering Manager. They own continuity, quality and escalation for the life of the relationship.
| Model | How it works | Example from our work |
|---|---|---|
| Team augmentation | Our engineers join your team, under your product owner, on time and materials. | Two full-stack developers migrated a retail CRM platform from Azure to AWS. |
| Blended squad | A NexaQuanta squad with its own QA, product owner and architect, on time and materials. | Two Laravel developers, QA and a part-time PO and architect built a logistics platform. |
| Fully outsourced delivery | We own the outcome against an agreed scope, at fixed price or on time and materials. | A recruitment SaaS product, delivered at fixed cost and scope. |
Scale up in weeks, down in a month
Capacity grows with your pipeline and is built for a multi-year relationship.
A minimum viable team from day one
Full-stack developers, QA and a BA or product owner can start in as little as 2 weeks from signing.
Structured scale-up
Each new role is onboarded and productive within 2–6 weeks.
Defined role profiles
Matched to your job descriptions, so seniority and cost hold no surprises.
Flexible ramp-down
Release any engineer with one month’s notice.
Contract-to-permanent
Keep control of key people by moving them onto your payroll.
Governance you can audit
Your engineering standards, enforced
We work to your SDLC: coding standards, security requirements, peer review and CI/CD quality gates. That protects the quality and security of your source code.
Documentation and process that scale
AI tools speed up documentation. We also help define Agile development, testing, deployment and release processes. Start-up habits become a scaled operating model.
Delivery management in the open
We run Scrum or Kanban and keep RAID registers for risks and dependencies. Meeting minutes and decision logs are shared with you. You receive regular reports on performance, quality and utilisation.
Regular review and audit
We audit our own compliance with your processes, standards, documentation and reporting requirements. Gaps are found before they reach your release.
Specialists beyond the core pod
Senior expertise joins full-time or fractionally, onshore or offshore.
Architecture and technical leadership
Enterprise, data, AI and solution architects for design reviews, solution governance and technical debt strategy.
Product and delivery
Business analysts, product owners, product managers and delivery leads who know enterprise SaaS and CRM in regulated industries.
Data integration
Data architects, engineers and migration experts for complex pipelines, event-driven architecture and integration-heavy builds.
Agentic AI advisory
Our AI practice helps you define, build and scale AI, from strategy to production deployment.
Our technology stack
| Backend and application | Frontend | API and integration | QA and DevOps |
|---|---|---|---|
| Python, Django, FastAPI | React, Next.js | REST and GraphQL | Automated unit and integration testing |
| PHP, Laravel | Vue.js | Event-driven architecture | End-to-end and load testing |
| Node.js, .NET, C# | Angular | Third-party integrations | CI/CD pipelines |
| Java, Spring Boot | TypeScript, UI/UX design | Data pipelines, microservices | AWS, Azure, GCP, infrastructure-as-code |
Where we've delivered
Our experience spans financial services, professional services, automotive and the public sector. Four contexts come up most often.
Enterprise SaaS and platforms
Complex, multi-tenant environments where uptime, performance and code quality can't slip.
Regulated financial services and fintech
Compliance and auditability designed in as standard.
API-led, integration-heavy systems
Third-party partner networks, high-volume transactional systems and complex integration architecture.
CRM solutions
Development on CRM platforms and integration with them.
How a partnership starts
Scoping call
We learn your platform, engineering culture and priorities.
Core pod live
Your minimum viable team can start contributing in as little as 2 weeks from signing.
Scale by role
Specialists and extra engineers join as your roadmap demands.
Report & review
Metrics reach you on an agreed cadence, backed by regular audits.
Case studies
Enterprise SaaS platform and data warehouse
A PE-backed dealership management software company serves 19,500 retailers in 82 countries. It needed its products on one platform, connected to a single data warehouse. Our blended squad built the core platform, an SSO service and the warehouse, integrating product databases and third-party sources.
Product team: 1 lead and 3 senior full-stack developers, 2 QA engineers, 1 DevOps engineer, 1 programme lead, fractional architect.
Data team: 4 data engineers, 1 data BA, 1 product owner. Both ongoing.
Stack: React, Node.js, Keycloak, AWS, Debezium, Kafka (Redpanda), Dagster, OpenMetadata, OpenLineage, Python.
Core banking platform
A fintech core banking platform serves 175,000 active users. Our embedded team developed and modernised its backend and APIs, KYC and payment integrations, and iOS and Android apps.
Team: 2 senior developers, 1 QA engineer.
Time and materials. Completed.
Logistics and e-commerce SaaS
A Laravel platform connects e-commerce companies with multiple delivery providers. We built the core platform and REST APIs, plus an admin portal, a driver app and e-commerce plugins.
Team: 2 Laravel developers, 1 QA engineer, 0.5 FTE product owner, 0.5 FTE solutions architect. Time and materials.
Recruitment performance management SaaS
A MERN-stack product tracks the performance of recruitment professionals. It integrates with applicant tracking systems and CRMs through REST APIs.
Team: 2 full-stack developers, 1 QA engineer, 0.5 FTE product owner, fractional architect. Fixed cost and scope. Ongoing.
Frequently asked questions
Every engineer is a NexaQuanta employee or a managed contractor engaged through NexaQuanta. You have no direct contractor relationship with any individual.
A minimum viable team can start in as little as 2 weeks from signing. Each additional role is productive within 2–6 weeks.
Yes. Any engineer can be released with one month’s notice.
Yes. Contract-to-permanent arrangements are available, so you keep control of key people over a long partnership.
Yes. We work to your SDLC, coding standards, security requirements and CI/CD quality gates. Where processes don’t exist yet, we help define them.
NexaQuanta is headquartered in London. Engineers and specialists work onshore or offshore, full-time or fractionally, to suit your engagement.
Book a scoping call
Start with one small, well-defined project before you commit to a full squad.