01Build
Launch faster
Delivery of digital products and business applications with structured processes and reusable components.
- Full-Stack
- MVP
- SaaS
Software that evolves with the business.
Engineering for
- Software that evolves with the business. Engineering for digital products — Product engineering from MVP to scale, with clear scope and frequent releases.
- Software that evolves with the business. Engineering for legacy modernisation — Migrating and modernising systems without interrupting operations.
- Software that evolves with the business. Engineering for platform integration — Connecting systems, data and APIs into one coherent platform.
- Software that evolves with the business. Engineering for AI workflows — Generative and agentic AI applied to real business use cases.
We deliver custom software development in Portugal, modernise applications and integrate platforms with engineering designed to reach production and keep evolving.
- Since 2007
- ISO 9001:2015
- Six engineering capabilities
- Build and evolve
Business Outcomes
Where we create value
We help companies launch products faster, modernise critical systems, integrate platforms and adopt AI in practical terms. Each outcome below maps to a concrete capability — not to a generic promise.
02Evolve
Modernise without stopping
Controlled upgrade of legacy systems, without interrupting day-to-day operations.
- Cloud Migration
- Refactoring
- Replatforming
03Evolve
Connect systems
Integration of platforms, APIs and data sources to automate processes and centralise information.
- API Integration
- iPaaS
- Data Pipelines
04Build
AI with a purpose
Generative AI applied to concrete use cases: automation, assistants and data processing.
- LLM Integration
- Copilots
- Automation
05Build
Ready to grow
Solutions designed to support growth, with sound architecture and simplified maintenance.
- Architecture
- Performance
- Security
Business Outcomes
None of these your case?
Describe the business objective and the current state of your systems. We identify the pathway — build, modernise or integrate — and the capability that answers it, before any talk of technology.
Describe your objective
The concrete gain depends on each organisation’s starting point — the state of the systems, the data available and the decisions already made. That is exactly what we assess before proposing anything.
Services
Our engineering capabilities
Proven engineering practices combined with emerging technology, to deliver software that is secure, scalable and aligned with the business. Pick a capability to see what it covers, when it makes sense and what you are left with.
Build
Path · Build
Product Engineering
Build robust digital products from concept to deployment, combining product thinking, modern architecture and end-to-end software engineering.
What it covers
- Product discovery: problem, users, scope of the first version.
- Application architecture, data model and API design.
- Full-stack development, web and mobile, with frequent releases.
- Automated testing, code review and deployment pipeline.
When it makes sense
- There is a product or business application to build from scratch.
- A first version needs validating quickly without mortgaging the future.
- The solution will grow, and the v1 architecture has to survive v3.
What you are left with
- Application in production, with code and documentation handed over.
- Build, test and deployment pipeline.
- Prioritised backlog for the following iterations.
Technologies and practices
- Full-Stack
- MVP
- Plataformas SaaS
Frequently delivered with
Profiles involved
- Development
- Architecture
- QA & Testing
- Management
Path · Build
Generative AI Solutions
Embed generative AI into applications, workflows and internal tools to improve productivity, decision support, knowledge access and user experience.
What it covers
- Integration of language models into existing applications and processes.
- Assistants and copilots over the organisation’s internal knowledge.
- Content generation and transformation inside working flows.
- Assessment of the use case: where AI adds value and where it does not.
When it makes sense
- Repetitive reading, drafting or searching work is consuming team time.
- The knowledge exists, but it is scattered and hard to find.
- You want to test AI on a concrete use case before investing at scale.
What you are left with
- Use case implemented and integrated into the tools the team already uses.
- Criteria for evaluating the quality of responses.
- Human oversight points defined in the flow.
Technologies and practices
- Integração LLM
- Copilots
- Geração de Conteúdo
Frequently delivered with
Profiles involved
- Data & AI
- Development
- Architecture
Where the scope ends
We build the solution; we do not guarantee the accuracy of what a model generates. The design always includes human validation at the points where a decision carries consequence.
Data & AIPath · Build
Agentic AI Solutions
Design and implement agents able to handle multi-step tasks, orchestrate workflows, interact with systems and support higher levels of automation.
What it covers
- Flow design: which steps the agent executes, and where it stops to ask for a decision.
- Multi-agent orchestration and coordination across tasks.
- Connection to systems and APIs, with explicit permissions and limits.
- Action logging, so what was done is auditable.
When it makes sense
- A process has many manual steps chained across several systems.
- The process rules are known and can be made explicit.
- There is appetite to automate progressively, with supervision.
What you are left with
- Automated workflow over a defined scope.
- Human approval points and limits on what the agent may act on.
- Log of the actions executed.
Technologies and practices
- Multi-Agent
- Orquestração
- Workflows Autónomos
Frequently delivered with
Profiles involved
- Data & AI
- Development
- Architecture
Where the scope ends
Progressive automation, with human oversight and a defined scope — not autonomous operation without supervision. The agent’s limits are designed and agreed before any connection to production systems.
Data & AIEvolve
Path · Evolve
Legacy Migration and Modernization
Turn outdated applications and platforms into scalable, secure and maintainable environments, better suited to current and future business needs.
What it covers
- Assessment of the application landscape: what exists, what is critical, what can go.
- Modernisation strategy per application: refactoring, replatforming or replacement.
- Cloud migration and phased rewrite of components.
- Rationalisation: reducing the number of systems before evolving them.
When it makes sense
- Maintaining the current system costs more than evolving it.
- Technology is limiting what the business wants to do next.
- There are dozens of applications doing overlapping work.
What you are left with
- Map of the application landscape and modernisation priorities.
- Phased plan, with the operation still running through the transition.
- Migrated components and the legacy system decommissioned under control.
Technologies and practices
- Cloud Migration
- Refactoring
- Replatforming
Frequently delivered with
Profiles involved
- Development
- Architecture
- Cloud & DevOps
- Enterprise
Where the scope ends
We modernise and migrate the applications. Running the infrastructure underneath them — monitoring, incident management, continuity — is the scope of IT Core Services.
IT Core ServicesPath · Evolve
Connected Platform Services
Connect systems, APIs and data sources to create unified workflows, cross-cutting visibility and greater operational efficiency across the organisation.
What it covers
- API design, development and lifecycle management.
- Integration across enterprise systems, including iPaaS platforms.
- Data pipelines between applications and analytical repositories.
- Automation of processes that today cross systems by hand.
When it makes sense
- The same information is keyed into more than one system.
- There is no single view of a customer, a process or an asset.
- A business process depends on exports and files passed around manually.
What you are left with
- Integrations in production, documented and monitorable.
- API contracts and data mappings between systems.
- Automated process, with defined error handling.
Technologies and practices
- API Integration
- iPaaS
- Data Pipelines
Frequently delivered with
Profiles involved
- Development
- Architecture
- Enterprise
- Data & AI
Where the scope ends
We build the integrations and the pipelines. Designing the analytical platform, governing the data and the models that exploit it are the scope of Data & AI.
Data & AICross-cutting
Path · Cross-cutting
Pre-Built AI Accelerators
Shorten time to first result through reusable frameworks, pre-configured components and implementation patterns already tested on common AI use cases.
What it covers
- Reusable components for recurring AI use cases.
- Tested integration patterns, instead of architecture from scratch.
- A starting environment to experiment before committing investment.
When it makes sense
- You want to see AI working on your own context before deciding the scope.
- The use case is common and does not justify building everything anew.
- A base is needed for a proof of concept with a path to production.
What you are left with
- Use case running on the organisation’s real data and context.
- Assessment of what works, what does not and what is missing.
- A defined path from proof of concept to production.
Technologies and practices
- Frameworks
- Templates
- Deploy Rápido
Frequently delivered with
Profiles involved
- Data & AI
- Development
- Cloud & DevOps
Where the scope ends
Accelerators shorten the start; they do not replace the decision phase. What is reusable is the implementation pattern, not the final solution — that is always adapted to the context.
On the AI capabilities, the scope is always a defined use case, with human oversight over what the system decides and writes. We publish no accuracy guarantees, and we do not promise autonomous operation without supervision.
Quick Start
Structured entry points
For organisations that want to move with a defined scope and less exposure to risk: short, bounded engagements that help validate priorities, define scope and accelerate execution — before a larger commitment.
01Build
AI Opportunity Assessment
Identify practical AI use cases, assess maturity, prioritise opportunities and define a roadmap aligned with business value.
Suited whenThere are several AI ideas in the organisation and it is unclear where to start.
What you are left with
- Use cases identified and prioritised.
- A reading of current maturity.
- A roadmap with a tightly scoped first iteration.
Leads into: Generative AI Solutions
Start here02Evolve
Legacy Modernization Assessment
Assess existing applications, technical debt and modernisation priorities to support a structured transformation plan.
Suited whenThe current system limits the business, but what to touch first is not obvious.
What you are left with
- Application inventory and a reading of technical debt.
- Modernisation priorities.
- A phased plan with dependencies identified.
Leads into: Legacy Migration and Modernization
Start here03Evolve
Integration & Automation Blueprint
Map systems, workflows and dependencies to define a pragmatic integration and automation architecture.
Suited whenInformation is scattered and processes cross systems that do not communicate.
What you are left with
- Map of systems, flows and dependencies.
- Proposed integration architecture.
- Automation sequence per process.
Leads into: Connected Platform Services
Start here04Build
MVP Fast-Track
Rapidly design and deliver a focused first version of a product or business application, with a clear path to scale.
Suited whenThere is a validated idea and it needs to get in front of real users.
What you are left with
- Scope of the first version, tight and agreed.
- A working product in a real environment.
- An evolution path for the next versions.
Leads into: Product Engineering
Start here05Build
Knowledge Assistant / Copilot Starter
Launch an internal AI assistant to improve access to information, reduce repetitive work and support teams.
Suited whenInternal knowledge exists, but it is scattered and slow to find.
What you are left with
- An assistant running over defined knowledge sources.
- Criteria for evaluating responses.
- Human oversight points in the flow.
Leads into: Generative AI Solutions
Start hereQuick Start
Not sure which one to pick?
Describe the context and we will suggest the right entry point — or tell you none is needed and you can go straight to execution.
Discuss your case
The duration and format of each entry point depend on scope and context — we publish no standard durations or prices. What is agreed before starting is what will be analysed and what will be delivered at the end.
Methodology
How we deliver
A clear process, from the initial assessment to delivery in production — and the evolution that follows.
01 · Discover
Understand the problem before writing code
Requirements, technical context and objectives. What exists, what is critical, what really has to be in the first version.
Out of this stage
- Objectives and success criteria
- Scope of the first delivery
- Risks and dependencies
02 · Design
Decide the architecture with an eye on what comes next
Architecture, planning and delivery roadmap. The structural decisions are made here, while they are still cheap to change.
Out of this stage
- Architecture and data model
- Delivery roadmap
- Documented technical decisions
03 · Build
Deliver in iterations, not in a single reveal
Iterative development with frequent releases, automated tests and code review as part of the work — not as a phase at the end.
Out of this stage
- Working increments
- Automated tests
- Build and deployment pipeline
04 · Integrate
Connect to the ecosystem that already exists
Connection to existing systems and platforms. This is where most projects discover what they did not know — which is why we do not leave it to the end.
Out of this stage
- Integrations in production
- Documented API contracts
- Defined error handling
05 · Scale
Delivery is not the end of the work
Optimisation and continuous evolution of the solution, based on what real usage reveals. The software becomes a maintained asset, not a closed project.
Out of this stage
- Performance improvements
- Evolution backlog
- Handover to whoever will operate it
Pace, duration and the number of iterations depend on the agreed scope — we publish no standard durations. What is constant is the sequence: discover before designing, design before building, and integrate before considering delivery done.
After it reaches production
Whoever operates the solution day to day — monitoring, incidents, continuity — can be the client’s internal team or Shore, through IT Core Services. That decision is part of the transition stage; it is not a surprise at the end.
See IT Core ServicesDifferentiation
Why Shore for development
Engineering rigour, modernisation capability, integration knowledge and applied AI — to solve business challenges with practical execution.
What backs this up
- A Portuguese IT Services company since 2007.
- Quality management system certified to ISO 9001:2015.
- Centres of Excellence dedicated to SAP, Microsoft, Oracle, MuleSoft and AI-native engineering.
- Delivery in sectors with high continuity demands — health, logistics, mobility, public sector.
- 01
Engineering with a business focus
We do not build technology in isolation. We design and deliver solutions aligned with real operational and strategic priorities.
- 02
AI applied with purpose
We use AI where it adds value to the actual work of the teams, not as a superficial layer or a marketing exercise. When it does not add value, we say so.
- 03
Modernisation without disruption
We help legacy environments evolve in a controlled, phased way, with the operation still running through the transition.
- 04
Integration-oriented thinking
Software only creates value when it connects effectively to the ecosystem around it. We treat integration as part of the design, not as a problem for the end.
- 05
Pragmatic execution
Delivery discipline, technical depth and focus on what produces value first — to move from concept to implementation without the project losing its way.
Our team
Who delivers, and in which disciplines
A delivery team is composed from the disciplines the project needs — not from an isolated profile. These are the disciplines we work with, and the profiles inside each.
6 profiles found
Development
6 profilesFull-stack, frontend, backend and mobile developers, across the main technology stacks.
Full-Stack Developer
- React
- Angular
- Vue
- .NET
- Java
- Node.js
Frontend Developer
- React
- Angular
- Vue
- TypeScript
- Next.js
- Tailwind
Backend Developer
- .NET
- Java
- Node.js
- Python
- Go
- Microservices
Mobile Developer
- React Native
- Flutter
- Swift
- Kotlin
- Xamarin
Low-Code Developer
- Power Apps
- OutSystems
- Mendix
- Appian
API Developer
- REST
- GraphQL
- gRPC
- API Gateway
- OpenAPI
Profiles are composed according to the project, and onboarding is aligned with the client’s standards. We publish no standard team sizes or allocations — they depend on the agreed scope.
Looking for an individual profile?
If what you need is to reinforce your team with one or more specialists, under your management, the right service is IT Skills & Talent — not this one.
Go to IT Skills & TalentLooking for a team to deliver the project?
If what you need is for Shore to take on delivery of a product, a modernisation or an integration, with responsibility for the result, you are in the right place.
Talk about the projectCentres of Excellence
Specialisation in the platforms where enterprise software lives
When a project sits on an enterprise platform, the difference is made by people who already know it from the inside. These are our dedicated centres.
- SAPS/4HANA & BTP
SAP S/4HANA implementation and migration, development on the Business Technology Platform and enterprise process integration.
- S/4HANA
- BTP
- Process integration
- MicrosoftPower Apps
Low-code development of enterprise applications, process automation with Power Automate and Power BI dashboards.
- Power Apps
- Power Automate
- Power BI
- Oracle ModernizationAPEX
Rapid development of enterprise web applications with Oracle APEX, Oracle database integration and legacy system modernisation.
- Oracle APEX
- Oracle databases
- Legacy modernisation
- MuleSoftIntegration Platform
API architecture, enterprise system integration and connectivity strategies with the Anypoint platform.
- API architecture
- Anypoint
- Enterprise connectivity
- AI-nativeEngineering
Solutions built with generative AI, applied machine learning and AI-powered software engineering.
- Generative AI
- Machine learning
- AI-powered engineering
Centres of Excellence
Not sure which centre fits?
Describe the platform, context and objective. We will identify the most relevant Centre of Excellence or bring together the right expertise when the challenge spans more than one.
Share the context
The Centres of Excellence describe Shore’s own practice on these platforms — skills, projects and dedicated teams. They do not, in themselves, represent formal partner status with the vendors.
Delivery cases
What we have delivered
Representative examples of how we helped organisations solve complex challenges through custom development, modernisation and applied AI.
Health
Modernising field operations
A cloud and mobile platform for greater operational control and better team coordination.
Challenge
A healthcare organisation depended on a third-party managed system that limited operational agility, made team management difficult and prevented critical information from being centralised in real time.
What Shore did
Shore designed and implemented a new platform, with a mobile application and an architecture on Azure, which came to support control of field operations and to centralise critical information in a single place — replacing the dependency on the third-party managed system.
Capabilities involved
- Product Engineering
- Legacy Migration and Modernization
Technologies and practices
- Azure
- Mobile App
- Cloud Platform
- Operations Management
- Product Engineering
Indicators
Quantitative indicators under internal validation — not published.
The description of each case — the challenge, what was built and what changed in the operation — is published. The quantitative indicators associated with these projects (effort gains, go-live timelines, number of applications consolidated) are under internal validation and are not published without a measurement method, a period and client approval. Clients are not identified.
Next step
Have a project in mind?
Describe what you want to build or evolve. If it is still open-ended, start with one of the structured entry points — that is how most projects begin.