Embedded hardware and software service planning

Services

Engineering support across the full development lifecycle.

We step in where embedded teams need leverage: new platform definition, complex firmware delivery, or stronger release quality.

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Requirements Engineering

Clear Requirements. Better Products. Lower Risk.

Requirements are the starting point of every successful engineering project. Poorly defined requirements lead to misunderstandings, design inefficiencies, verification issues, and costly rework. Our Requirements Engineering services help organizations establish clarity from the beginning.

We combine proven engineering practices with AI-assisted analysis and quality assessment to improve consistency, identify gaps early, and accelerate the requirements lifecycle while maintaining full engineering oversight.

Requirements Elicitation

We work closely with stakeholders to understand business needs and transform them into clear, structured and actionable engineering requirements. Through collaborative workshops, interviews and AI-assisted analysis, we establish a solid foundation for successful system development.

Stakeholder Workshops Requirements Discovery Business Needs Analysis Use Case Definition User Story Development AI-Assisted Analysis

Business Benefits

  • Clear Project Scope Capture stakeholder expectations accurately from the beginning of the project.
  • Better Stakeholder Alignment Build a shared understanding across business, engineering and project teams.
  • Reduced Development Risk Identify missing, conflicting and incomplete requirements before implementation begins.

Requirements Analysis

We analyze requirements to identify ambiguities, inconsistencies, conflicts and missing information, ensuring they are technically accurate, complete and ready for documentation, validation and downstream engineering activities.

Requirements Identification Concept Validation Simulation Gap Analysis Consistency Checks Conflict Detection AI-Assisted Reviews

Business Benefits

  • Higher Requirement Quality Increase confidence in engineering decisions from the very beginning of the project.
  • Reduced Engineering Risk Detect ambiguities, conflicts and missing information early to prevent costly downstream issues.
  • Faster Reviews Accelerate requirements analysis with AI-assisted quality checks while maintaining full engineering oversight.

Requirements Documentation

We create structured, consistent and verifiable requirements specifications that improve communication, support traceability and provide a reliable foundation for system design, implementation and verification.

Textual Representation Model-based Representation Formal Representation UML & SYSML Traceability Requirements Patterns AI-Assisted Authoring

Business Benefits

  • Clear Engineering Communication Create structured and unambiguous specifications that align stakeholders across the development lifecycle.
  • Consistent Documentation Maintain uniform terminology, formatting and quality throughout engineering documentation.
  • Faster Documentation Accelerate the creation, review and maintenance of engineering specifications with AI-assisted support.

Requirements Validation and Verification

We validate and verify requirements to ensure they are correct, complete, consistent and testable before they drive downstream engineering activities. By combining structured engineering reviews with AI-assisted quality analysis, we help identify issues early and improve the overall quality of the specification.

Requirements Quality Reviews Validation Workshops Verification Rules Testability Analysis Standards Compliance AI-Assisted Quality Checks

Business Benefits

  • Increase Customer Satisfaction Validate requirements with stakeholders to ensure the solution meets customer expectations.
  • Reduced Development Effort Identify requirement issues early to minimize redesign, implementation rework and project delays.
  • Better Product Quality Provide verified and testable requirements that enable reliable design, implementation and product verification.

Requirements Management

We manage requirements throughout the development lifecycle by controlling changes, maintaining traceability and ensuring consistency across all engineering artifacts. AI-assisted impact analysis and quality monitoring help teams adapt efficiently while keeping requirements under control.

ASPICE Change Management Impact Analysis Version Control Baseline Management ISO 29148 AI-Assisted Change Analysis

Business Benefits

  • Controlled Project Scope Manage requirement changes in a controlled manner to prevent scope creep and maintain project objectives.
  • Reduced Project Risk Identify and assess change impacts early to minimize engineering errors, rework and delivery risks.
  • Predictable Project Execution Maintain trusted requirement versions and baselines to keep engineering teams aligned throughout the project.

AI-Assisted Requirements Engineering

Our engineers leverage AI to strengthen requirements quality assessment and accelerate engineering activities while maintaining full engineering oversight. AI supports faster reviews, earlier detection of inconsistencies and gaps, improved traceability, and more efficient handling of repetitive analysis tasks. This allows teams to improve quality and delivery speed without giving up technical rigor, accountability, or control.

Faster Quality Reviews

AI helps review requirement sets more quickly and surfaces patterns, inconsistencies, and missing details earlier in the process.

Earlier Gap Detection

AI-assisted analysis highlights ambiguities, contradictions, and incomplete statements before they turn into downstream engineering issues.

Improved Traceability

AI supports the mapping of requirements to related artifacts, making trace links easier to establish and maintain across the lifecycle.

Higher Engineering Efficiency

Repetitive analysis tasks are handled faster, so engineers can spend more time on the decisions that require domain expertise and accountability.

Why Better Requirements Matter

Clear and verifiable requirements reduce project risk, improve collaboration, accelerate development, and enable efficient verification throughout the engineering lifecycle.

Key Benefits

  • Reduce ambiguity and costly rework
  • Improve quality from the start
  • Enable efficient architecture and design activities
  • Strengthen traceability and compliance
  • Accelerate verification and validation
  • Increase confidence in project outcomes

System and Software Design

Architectures and design decisions that support reliable embedded products.

Effective system and software design transforms requirements into clear structures, responsibilities, interfaces, and implementation concepts. Our services help teams build technically coherent solutions that remain scalable, maintainable, and aligned with product goals.

We combine proven architecture and design practices with AI-assisted analysis to evaluate dependencies, identify inconsistencies, assess risks, and accelerate design activities while maintaining full engineering oversight.

Requirements Allocation

We analyze system and software requirements, allocate functionality to the appropriate elements, and define clear boundaries and responsibilities across the solution.

Functional Decomposition Requirements Allocation System Boundaries Responsibility Mapping Traceability AI-Assisted Allocation

Business Benefits

  • Clear Engineering Responsibilities Establish clear ownership of functions and requirements across system and software elements.
  • Reduced Integration Risk Identify missing allocations, overlaps and boundary issues before architecture development progresses.
  • Stronger Design Traceability Maintain clear links between requirements and the architecture elements that implement them.

System Architecture

We define the system structure, decompose functions, establish interfaces and interactions, and evaluate architectural alternatives against technical and project constraints.

Functional Architecture System Decomposition Interface Definition Architecture Trade-Offs SysML Modelling AI-Assisted Reviews

Business Benefits

  • Coherent System Structure Create a clear architecture that aligns functions, interfaces and system responsibilities.
  • Better Technical Decisions Evaluate architectural alternatives early using requirements, constraints and engineering trade-offs.
  • Lower Integration Complexity Define interfaces and interactions clearly to reduce downstream integration effort and uncertainty.

Software Architecture

We structure software into clear layers, components and services, define communication mechanisms, and establish responsibilities that support maintainability, scalability and reliable implementation.

Software Decomposition Layered Architecture Component Interfaces Communication Design Architecture Patterns Dependency Analysis

Business Benefits

  • Maintainable Software Structure Create modular software that is easier to understand, evolve and verify.
  • Reduced Implementation Risk Clarify interfaces, responsibilities and dependencies before detailed development begins.
  • Improved Development Efficiency Enable parallel development and clearer collaboration through well-defined software boundaries.

Detailed Design

We define software components, algorithms, interfaces, state behaviour and data structures in sufficient detail to support consistent implementation and efficient technical reviews.

Component Design Algorithm Design Interface Specifications State Modelling Data Structures UML Modelling

Business Benefits

  • Implementation-Ready Design Provide developers with clear technical guidance for consistent and reliable implementation.
  • Fewer Development Defects Resolve design ambiguities and interface issues before they become implementation problems.
  • Faster Technical Reviews Use structured models and specifications to improve review efficiency and engineering alignment.

Design Validation and Verification

We review and assess system and software designs to confirm they satisfy allocated requirements, remain internally consistent, and are complete and ready for implementation.

Design Reviews Requirements Compliance Interface Consistency Dependency Analysis Risk Assessment AI-Assisted Checks

Business Benefits

  • Higher Design Confidence Confirm that the design is complete, consistent and aligned with system requirements.
  • Earlier Risk Detection Identify architectural gaps, interface conflicts and design weaknesses before implementation.
  • Reliable Implementation Basis Provide development teams with a reviewed and technically sound design foundation.

AI-Assisted System and Software Design

Our engineers use AI to support architecture analysis, consistency checking, dependency identification, design documentation and technical reviews. AI accelerates repetitive analysis and highlights potential issues, while engineering decisions and responsibility remain with experienced system and software engineers.

Design Insights

AI supports the comparison of design alternatives and helps surface relevant patterns, constraints and engineering considerations.

Architecture Consistency

AI-assisted checks help identify inconsistencies between requirements, architecture elements, interfaces and detailed design artifacts.

Dependency Analysis

Complex relationships between components, interfaces and requirements can be analyzed faster to improve impact assessment and change decisions.

Quality and Risk Assessment

AI helps detect missing information, design risks and review priorities earlier in the engineering lifecycle.

Why Better Design Matters

Clear architectures and implementation-ready designs reduce technical risk, improve collaboration, and create a reliable foundation for development, integration and verification.

Key Benefits

  • Improve architectural clarity and consistency
  • Reduce implementation and integration risk
  • Strengthen interfaces and component boundaries
  • Enable scalable and maintainable solutions
  • Accelerate design reviews and decisions
  • Maintain traceability from requirements to design

Validation and Verification

Requirement-based verification that builds confidence in product quality.

Effective verification begins with a clear understanding of the requirements and the behaviours, conditions, interfaces, and constraints that must be tested. We develop traceable verification strategies that connect requirements directly with test cases, execution environments, and objective evidence.

We combine structured test engineering with AI-assisted generation, validation, and results analysis to improve coverage, accelerate verification cycles, and identify quality risks earlier while maintaining full engineering oversight.

Requirements Analysis

We analyze requirements to identify testable behaviours, operating conditions, interfaces, constraints, and expected outcomes. Clear traceability is established from each requirement to the verification activities needed to demonstrate compliance.

Testability Analysis Behaviour Identification Condition Analysis Interface Analysis Acceptance Criteria Requirements Traceability

Business Benefits

  • Clear Verification Scope Define exactly what must be demonstrated for each requirement and operating condition.
  • Stronger Test Traceability Connect requirements directly with test objectives, cases, execution results and evidence.
  • Earlier Testability Issues Identify unclear, incomplete or unverifiable requirements before test implementation begins.

AI-Driven Test Generation

We use AI to analyze requirements and relevant design information, generate test scenarios and detailed test cases, and propose representative test data. Engineers review and refine all generated outputs before they enter the verification baseline.

Test Scenario Generation Test Case Generation Boundary Value Analysis Test Data Generation Negative Testing AI-Assisted Authoring

Business Benefits

  • Faster Test Development Accelerate the creation of structured test scenarios, cases and representative data.
  • Broader Test Coverage Explore normal, boundary, negative and exceptional behaviours more systematically.
  • Reduced Manual Effort Automate repetitive specification work while engineers retain review and approval responsibility.

Test Case Validation and Review

We review test cases for completeness, correctness, consistency, and traceability. AI-assisted checks help detect gaps, overlaps, redundancies, and inconsistent acceptance criteria, while engineers validate the final verification intent.

Completeness Checks Consistency Reviews Coverage Analysis Redundancy Detection Acceptance Criteria Review Engineer Approval

Business Benefits

  • Higher Test Quality Ensure test cases are complete, consistent, understandable and aligned with verification objectives.
  • Fewer Coverage Gaps Detect missing scenarios, duplicate tests and inconsistent expected results before execution.
  • Reliable Verification Baseline Establish reviewed and approved test specifications for repeatable verification activities.

Test Execution

We implement and execute tests across the appropriate verification levels, from unit and component testing to integration, system, SIL, PIL, HIL, and regression testing. Automation improves repeatability, execution speed, and evidence quality.

SIL PIL HIL Unit Testing Integration Testing Software Testing System Testing Regression Testing Test Automation

Business Benefits

  • Repeatable Test Execution Run tests consistently across environments, variants and development iterations.
  • Faster Verification Cycles Use automation to shorten execution time and provide feedback earlier.
  • Stronger Quality Evidence Generate traceable results that support engineering, safety and release decisions.

Results Analysis and Assessment

We analyze test results to identify failures, recurring patterns, probable root causes, coverage gaps, and quality risks. AI-assisted analytics support faster interpretation, while engineers assess impact and determine the appropriate actions.

Issue Documentation Failure Analysis Root Cause Support Pattern Detection Coverage Assessment Risk Assessment Test Report

Business Benefits

  • Faster Failure Understanding Identify relevant patterns and probable causes across large volumes of test results.
  • Better Quality Decisions Use coverage, failure and risk insights to prioritize corrective actions effectively.
  • Greater Release Confidence Provide transparent verification evidence for informed readiness and release decisions.

AI-Assisted Validation and Verification

AI supports the verification lifecycle by analyzing requirements, generating and reviewing test cases, optimizing repetitive execution activities, and interpreting large volumes of results. This improves speed, consistency, and insight while engineers remain responsible for verification strategy, technical approval, safety, and final product assessment.

Intelligent Test Generation

AI transforms structured requirements and design information into candidate test scenarios, cases, and test data for engineering review.

Automated Quality Checks

AI-assisted reviews identify missing coverage, inconsistent expectations, overlaps, and redundancies before test execution.

Execution Optimization

Automated prioritization, regression selection, and workflow support help teams use verification resources more efficiently.

Analytics and Decision Support

AI helps interpret failures, coverage trends, and quality risks to support faster and better-informed engineering decisions.

Why Effective Verification Matters

Requirement-based verification provides objective evidence that the product behaves as intended, satisfies its requirements, and is ready for the next development or release decision.

Key Benefits

  • Strengthen requirements-to-test traceability
  • Improve verification coverage and consistency
  • Detect defects and quality risks earlier
  • Accelerate test development and execution
  • Generate reliable engineering evidence
  • Increase confidence in release decisions

AI-Enhanced Engineering

Automated code generation and verification based on requirements.

AI-enhanced engineering connects structured requirements with implementation and verification activities. We help teams transform clear engineering inputs into consistent code, tests, documentation, and traceability evidence through controlled and repeatable workflows.

Our approach combines AI-assisted generation with automated quality checks, static analysis, dynamic verification, and human approval. This accelerates delivery while preserving safety, reliability, compliance, and full engineering responsibility.

Requirements Analysis

We analyze and clarify requirements to extract functional behaviour, operating conditions, constraints, interfaces, and expected outcomes. Structured inputs and traceability provide a reliable basis for automated implementation and verification.

Intent Extraction Behaviour Analysis Constraint Identification Interface Definition Acceptance Criteria Requirements Traceability

Business Benefits

  • Reliable Engineering Inputs Create clear and structured requirements suitable for controlled automation.
  • Reduced Interpretation Risk Identify ambiguities, missing constraints and interface gaps before code generation begins.
  • End-to-End Traceability Maintain direct links from requirements to implementation, tests and verification evidence.

Code Generation

We apply model-to-code and AI-assisted generation workflows to produce consistent, standards-aligned implementation from structured requirements and design information. Generated code remains reviewable, traceable, and under engineering control.

Model-to-Code Generation AI-Assisted Coding Pattern Selection Coding Standards Automated Documentation Generation Traceability

Business Benefits

  • Faster Implementation Reduce repetitive development effort and accelerate delivery of implementation-ready code.
  • Consistent Code Quality Apply repeatable patterns, conventions and standards across generated components.
  • Improved Engineering Productivity Allow engineers to focus on architecture, behaviour and critical design decisions.

Code Review and Static Verification

We combine automated code inspection, static analysis, standards compliance checks, and AI-assisted review to detect defects, vulnerabilities, inconsistencies, and maintainability issues before dynamic testing.

Automated Code Review Static Analysis Coding Standards Compliance Defect Detection Security Analysis Issue Reporting

Business Benefits

  • Earlier Defect Detection Identify implementation issues before integration and dynamic test activities.
  • Stronger Standards Compliance Assess generated and manually developed code against defined quality rules.
  • Lower Verification Effort Reduce downstream rework by resolving static quality issues earlier.

Automated Testing and Dynamic Verification

We generate, implement, and execute automated tests across unit, component, model, software, and regression levels. Requirements and code context are used to create relevant test scenarios and assess runtime behaviour.

Unit Testing Component Testing Model-in-the-Loop Software-in-the-Loop Regression Testing AI-Generated Test Cases

Business Benefits

  • Faster Verification Cycles Automate test creation and execution to provide feedback earlier.
  • Improved Behavioural Coverage Test normal, boundary, negative and regression scenarios more systematically.
  • Repeatable Quality Evidence Produce consistent results across variants, releases and execution environments.

Verification Summary and Traceability

We consolidate requirements coverage, test results, quality metrics, traceability information, and unresolved issues into clear verification summaries that support technical assessment and release decisions.

Requirements Coverage Test Results Quality Metrics Traceability Reports Risk Assessment Release Readiness

Business Benefits

  • Transparent Verification Status Provide a clear view of coverage, results, open issues and remaining risks.
  • Better Release Decisions Use consolidated engineering evidence to assess product readiness with confidence.
  • Stronger Compliance Evidence Maintain traceable records from requirements through implementation and verification.

AI-Assisted Support Throughout the Lifecycle

AI supports the complete development lifecycle by understanding requirements, generating code, reviewing implementation quality, creating tests, and analyzing verification coverage. Engineers remain responsible for architecture, approval, safety, reliability, and compliance.

Requirements Understanding

AI extracts intent, behaviours, rules, interfaces, and constraints from structured and natural-language engineering inputs.

AI-Assisted Code Generation

AI helps generate implementation candidates aligned with defined models, patterns, coding standards, and engineering constraints.

Intelligent Code Analysis

AI-assisted analysis identifies defects, vulnerabilities, inconsistencies, and opportunities to improve maintainability and performance.

Quality and Coverage Insights

AI summarizes quality, risk, test results, and verification coverage to support faster and better-informed engineering decisions.

Why AI-Enhanced Engineering Matters

Controlled automation connects requirements, implementation, and verification into a consistent engineering workflow that improves productivity without compromising technical rigor.

Key Benefits

  • Accelerate implementation and verification
  • Reduce repetitive engineering effort
  • Improve consistency and standards compliance
  • Detect defects and risks earlier
  • Strengthen end-to-end traceability
  • Maintain human engineering oversight

Processes & Tools

Engineering excellence through optimized processes, integrated tools and responsible AI.

Strong engineering depends on more than technical expertise. We help organizations establish scalable engineering processes, integrated toolchains and practical automation that improve quality, collaboration and delivery.

Our services combine process consulting, custom tool development, tool integration and AI adoption to create efficient, traceable and future-ready engineering environments.

AI Across the Engineering Toolchain

AI supports engineering teams by automating repetitive work, improving decision support, strengthening traceability and integrating seamlessly into existing engineering processes while maintaining full human oversight.

Process Definition

Engineering workflows, roles, quality gates and lifecycle definition.

Process Optimization

Workflow improvement, KPI analysis and continuous optimization.

Tool Development

Custom engineering applications and automation utilities.

AI Integration

Engineering assistants, document intelligence and workflow automation.

Why Processes & Tools Matter

Well-defined processes and integrated tools create the structure needed for consistent, efficient and scalable engineering execution. They improve collaboration across teams, strengthen traceability and quality control, and provide the foundation for responsible automation and AI adoption throughout the development lifecycle.

Key Benefits

  • Standardize engineering workflows
  • Increase engineering productivity
  • Reduce manual engineering effort
  • Improve tool interoperability
  • Accelerate digital transformation
  • Enable responsible AI adoption