Technology-Agnostic Approach
We select the right tools for your specific needs, not limit you to our preferences
Our team has experience across numerous languages, frameworks, and platforms. We evaluate your project requirements, existing infrastructure, and team expertise to recommend the best technical approach—whether that's cutting-edge or battle-tested, popular or specialized.
Our Capabilities
Broad expertise across technology domains to serve your needs
Web Technologies
Modern frameworks, legacy systems, or anything in between
We work with the full spectrum of web technologies—from cutting-edge frameworks like React, Next.js, and Vue to battle-tested solutions like PHP and Ruby on Rails. Whether you need a modern SPA, a traditional server-rendered application, or progressive enhancement, we select the right approach for your requirements.
Mobile Platforms
Native iOS/Android, cross-platform, or progressive web apps
From native Swift and Kotlin development to cross-platform solutions like React Native and Flutter, we build mobile experiences tailored to your needs. We evaluate factors like performance requirements, team expertise, and time-to-market to recommend the optimal approach.
Cloud & Infrastructure
AWS, Azure, Google Cloud, or on-premise solutions
We design and implement cloud infrastructure across all major providers—AWS, Azure, and Google Cloud—as well as hybrid and on-premise solutions. Our recommendations are based on your existing infrastructure, compliance requirements, cost considerations, and scaling needs.
Data Solutions
SQL, NoSQL, graph databases, or specialized data stores
We work with the full range of database technologies: relational databases like PostgreSQL and MySQL, document stores like MongoDB, key-value stores like Redis, graph databases like Neo4j, and specialized solutions for time-series, search, and analytics. We choose based on your data access patterns and scalability requirements.
AI & Machine Learning
Any ML framework, from TensorFlow to custom models
Our AI/ML work spans multiple frameworks and approaches: TensorFlow, PyTorch, scikit-learn for traditional ML, LangChain and custom implementations for LLM applications, and computer vision libraries for image processing. We select tools based on your specific use case, data availability, and deployment requirements.
Backend Systems
Any language or framework that fits your requirements
We build backend systems in whatever technology best serves your needs: Node.js, Python, Java/Spring Boot, Go, Ruby, .NET, or others. Our choice is guided by factors like team expertise, performance requirements, ecosystem maturity, and integration with existing systems.
Integration
Connect with existing systems regardless of technology
We excel at integrating diverse systems and technologies. Whether it's REST APIs, GraphQL, message queues, webhooks, or legacy protocols, we build bridges between your existing infrastructure and new solutions. We work with whatever integration patterns your ecosystem requires.
DevOps
CI/CD pipelines with any toolchain you prefer
Our DevOps expertise covers containerization (Docker, Kubernetes), CI/CD (GitHub Actions, GitLab CI, Jenkins, CircleCI), infrastructure as code (Terraform, CloudFormation), and monitoring. We adapt to your existing toolchain or help you build a new one from the ground up.
How We Choose Technologies
Our decision-making process prioritizes your needs over our preferences
Requirements First
We start by understanding your project requirements, constraints, and goals—not by pushing our favorite tools.
Context Matters
We evaluate your existing infrastructure, team expertise, and technical debt before making recommendations.
Balanced Decisions
We weigh tradeoffs between cutting-edge and battle-tested, between performance and developer productivity.
Pragmatic Choices
The best technology is the one that solves your problem effectively within your constraints—not the most hyped.
Our philosophy: The right technology stack is one that solves your problem effectively, integrates with your existing systems, matches your team's capabilities, and fits your budget and timeline. We don't believe in one-size-fits-all solutions or forcing technologies that don't align with your context.
Real-World Examples
How we match technologies to specific needs
Legacy System Integration
We work with your existing Java/Spring Boot backend instead of recommending a rewrite, adding new microservices that integrate seamlessly with your established architecture.
Rapid Prototyping
For quick market validation, we might suggest Next.js with Vercel deployment and a managed database—optimizing for speed to market over perfect scalability.
High-Performance Requirements
When milliseconds matter, we evaluate options like Go or Rust for backend services, choosing based on your team's learning curve and ecosystem needs.
Team Expertise
If your team is proficient in Python, we build on that foundation rather than introducing unfamiliar technologies—unless there's a compelling technical reason.
Budget Constraints
We design solutions using cost-effective open-source tools and serverless architectures when appropriate, rather than defaulting to expensive managed services.