Technology value creation across the full portfolio.

A TypeScript-based framework for building web applications, maintained by Google. It offers a complete, opinionated structure with built-in tools for routing, forms, state management, and dependency injection. Well-suited for large, enterprise-scale single-page apps that benefit from consistent conventions.

A comprehensive cloud computing platform offering on-demand services like compute, storage, databases, networking, and machine learning. Businesses rent scalable infrastructure on a pay-as-you-go basis instead of maintaining physical servers, supporting everything from small websites to enterprise-scale applications.

Microsoft's cloud computing platform providing on-demand services like compute, storage, databases, networking, and AI. It supports building, deploying, and managing applications across a global network of data centers, with strong integration for enterprise tools and Windows-based environments.

A Microsoft cloud service that provides access to OpenAI's models, such as GPT and embeddings, through enterprise-grade infrastructure. It adds security, compliance, regional hosting, and integration with other cloud services, letting organizations build generative AI applications within a managed, scalable environment.

A fast JavaScript runtime, bundler, package manager, and test runner in one tool. Built on Apple's JavaScriptCore engine, it's designed as a faster alternative to Node, with quicker startup, built-in TypeScript support, and native tooling that reduces reliance on external dependencies.

A conversational AI assistant developed by OpenAI, powered by large language models. It generates human-like text to answer questions, write and debug code, draft content, and assist with analysis. Accessible via web, apps, and API, it's widely used for productivity, support, and automation.

Anthropic's agentic coding tool that lets developers delegate software tasks from the command line, IDE, or desktop and mobile apps. It reads codebases, edits files, runs tests, and executes commands with oversight. It supports MCP integration and can run multiple tasks in parallel across projects.

OpenAI's AI coding agent for software engineering tasks like writing features, fixing bugs, and reviewing code. It works across a terminal CLI, IDE extensions, a web/cloud environment, and desktop apps, running tasks autonomously in sandboxes. It supports parallel task execution, MCP integration, and repo-scale reasoning.

An AI-first code editor built by Anysphere as a fork of VS Code. It layers AI throughout the workflow with multi-line autocomplete, natural-language chat, whole-repository indexing, and an autonomous agent mode that plans, writes, tests, and fixes code across multiple files. It also supports MCP and parallel agents.

A cloud-based data and AI platform built around Apache Spark. It unifies data engineering, analytics, and machine learning in a "lakehouse" architecture that combines the flexibility of data lakes with the structure of data warehouses. Widely used for large-scale processing, collaboration, and AI workloads.

A collaborative, browser-based tool for interface and product design. It lets multiple people edit the same file in real time, supports prototyping, design systems, and developer handoff, and has expanded into whiteboarding, slides, and website building.

Google's cloud computing platform offering on-demand services like compute, storage, databases, networking, and machine learning. Known for strengths in data analytics, containers, and AI, it lets businesses build and scale applications on the same infrastructure that powers Google's own products.

A statically typed, compiled programming language developed at Google. Designed for simplicity and efficiency, it excels at concurrent programming through lightweight goroutines. Fast to compile and easy to deploy as a single binary, it's popular for cloud services, networking tools, and backend infrastructure.

A widely used, object-oriented programming language known for portability through its "write once, run anywhere" model. Compiled to bytecode that runs on a virtual machine, it powers enterprise systems, Android apps, and large-scale backend services, valued for stability, performance, and a mature ecosystem.

A React-based framework for building web applications. It adds server-side rendering, static site generation, routing, and API endpoints out of the box, improving performance and SEO. Widely used for production-grade sites, it handles much of the configuration developers would otherwise set up manually.

A JavaScript runtime that lets developers run code outside the browser, typically on servers. Built on Chrome's V8 engine, it uses an event-driven, non-blocking model well-suited for scalable network applications, APIs, and real-time services. It also powers much of modern JavaScript tooling.

A category of databases designed for flexible, non-relational data storage. Instead of fixed table schemas, they use models like documents, key-value pairs, graphs, or wide columns. Built for scalability and handling large or unstructured data, examples include MongoDB, Cassandra, Redis, and DynamoDB.

A Microsoft business analytics platform for visualizing data and sharing insights. It connects to many data sources, transforms and models data, and builds interactive dashboards and reports. Widely used for business intelligence, it integrates tightly with Excel and other Microsoft tools.

Amazon's cloud-based business intelligence service for building interactive dashboards and visualizations. It connects to AWS and other data sources, scales automatically, and uses a pay-per-session pricing model. It includes machine-learning-powered insights and natural-language querying for exploring data without deep technical expertise.

A JavaScript library for building user interfaces, primarily for web applications. It uses a component-based architecture and a virtual DOM to efficiently update what users see. Widely adopted for single-page apps, it emphasizes reusable UI pieces and declarative code.

A statically typed, compiled programming language focused on performance and memory safety. Its ownership system prevents common bugs like null-pointer errors and data races without a garbage collector. Popular for systems programming, game engines, embedded devices, and performance-critical backend services.

A cloud-based data platform for storage, processing, and analytics. It separates compute from storage for independent scaling, runs across multiple cloud providers, and handles structured and semi-structured data. Widely used for data warehousing, it supports data sharing, and increasingly, AI and machine learning workloads.

A relational database that stores data in structured tables of rows and columns, queried using SQL. It enforces schemas and relationships between tables, supports transactions for data integrity, and underpins countless applications needing reliable, structured storage. Examples include PostgreSQL, MySQL, and SQL Server.

We have the ability to adopt and support additional tools, platforms, or frameworks based on specific project needs, accommodating specialized or emerging requirements outside our standard stack.