We have a portfolio of people and skills that allow us to tackle complex tasks and help customers at any point in their journey.

New!

Talent Acquisition and Technical Recruitment

Handling end-to-end recruitment from requirements gathering to candidate placement
 
  • Candidate Sourcing and Screening
    Multi-stage evaluation including coding assessments, system design reviews, and technical deep-dives.
  • Candidate Presentation and Shortlisting
    Curated candidate submissions with comprehensive profiles including technical evaluation summaries, salary expectations, notice periods, and fit analysis against specific role requirements.
  • Interview Coordination and Management
    Complete scheduling and logistics for customer interview rounds, candidate communication, feedback collection, and process management through to offer acceptance.
  • Relocation Support Services
    Optional comprehensive relocation assistance including visa sponsorship coordination, housing search support, family relocation logistics, and cultural onboarding for international hires.

De-risk digital transformation

Identify and mitigate technical, security, and operational risks before they impact your business.

  • Cloud Readiness Assessments
    Evaluation of applications, infrastructure, and organization for cloud migration with dependency mapping and risk identification.
  • Architecture Health Checks
    Deep-dive reviews identifying technical debt, scalability constraints, security vulnerabilities, and anti-patterns.
  • Well-Architected Reviews
    Framework-based assessments (AWS, Azure, GCP) covering operational excellence, security, reliability, and performance.
  • Change Management
    Structured processes for technology changes with approval workflows, risk assessment, and rollback procedures.

Cost optimization

Reduce cloud spend and improve resource efficiency without sacrificing performance.

  • Technology Stack Evaluation
    Objective analysis of technology choices, licensing costs, and cost-effective modernization paths.
  • Cloud Cost Optimization
    Continuous right-sizing, reservation planning, and architectural improvements to reduce cloud spend.
  • FinOps Implementation
    Financial governance for cloud with chargeback/showback models, budget controls, and cost accountability.
  • Observability Implementation
    Transform guess and feeling-based decisions into data-driven decisions with comprehensive monitoring and alerting.

Delivery acceleration

Ship features faster with automated pipelines, modern DevOps, and self-service platforms

  • DevOps Transformation
    CI/CD pipeline implementation, automated testing, and deployment automation for faster, safer releases.
  • Embedded CI/CD
    Specialized pipelines for embedded systems with hardware-in-the-loop testing and cross-compilation.
  • Internal Developer Platforms
    Self-service access to infrastructure, databases, pipelines, and monitoring – removing bottlenecks.
  • Platform Engineering
    Golden paths and paved roads that make the right way the easy way for development teams.

Systems modernization

Transform legacy systems into scalable and modern solutions that support growth

  • Modernization strategy
    Assessment-driven roadmaps for refactoring, re-platforming, or rebuilding based on business value.
  • Application modernization
    Containerization, microservices, and serverless implementations for improved scalability and resilience.
  • Legacy Migration
    Systematic migration of monolithic applications to modern platforms with minimal disruption.
  • Cloud Platform Engineering
    Design cloud foundations, including networking, security, identity management, and governance.

AI & ML

Leverage artificial intelligence, machine learning, and data platforms to create competitive advantages

  • Generative AI Integration
    LLM-based solutions, RAG systems, and AI-powered automation using public (f.e. OpenAI, Claude, Gemini) or custom models.
  • Custom ML Solutions
    Predictive models, recommendation engines, computer vision, and natural language processing applications.
  • Data Platform Engineering and MLOps
    Modern data lakes, lakehouses, and real-time streaming architectures for analytics and ML with end-to-end ML lifecycle management including training, versioning, deployment, monitoring, and retraining.
  • Knowledge Management
    AI-powered knowledge bases, intelligent search, and self-service support systems.