Technologies

Technologies We Use and Work On

ChampSoft engineers work across the full technology stack, selecting tools based security, scalability, operational maturity, and long-term maintainability, applying AI selectively within a governed engineering lifecycle. 

Frameworks & Libraries (modern stack)

React Angular Vue.js Svelte Next.js Nuxt Remix SvelteKit Tailwind CSS Material UI

Legacy & Modernization

Ember Backbone jQuery

Core Web Technologies & Tooling

TypeScript JavaScript HTML5 CSS3 Web Components Vite Webpack

Languages & Runtimes

C# Java Kotlin TypeScript Node.js Python Go Rust PHP

Frameworks & Platforms

.NET / ASP.NET Core .NET 8+ APIs Spring Boot Express.js NestJS FastAPI Django Flask Ruby on Rails Laravel Symfony Gin Echo

API Styles & Architecture Patterns

REST APIs GraphQL gRPC Microservices Event-Driven Architecture Domain-Driven Design (DDD) CQRS

Native Mobile

Swift SwiftUI Kotlin Jetpack Compose Objective-C Java

Cross-Platform & Hybrid

Flutter React Native .NET MAUI Kotlin Multiplatform Ionic

Mobile Backends & BaaS

Firebase AWS Amplify Azure App Service Azure Functions Supabase Backendless Parse Platform Apple CloudKit Back4App PocketBase

Cloud Providers

Microsoft Azure AWS Google Cloud Platform (GCP) IBM Cloud

Containers & Orchestration

Docker Kubernetes AKS EKS GKE AWS ECS Fargate Google Cloud Run Azure Container Apps

Serverless & API Management

AWS Lambda Azure Functions Google Cloud Functions AWS API Gateway Azure API Management Apigee Kong Serverless Framework AWS SAM

Relational Databases

SQL Server PostgreSQL MySQL Oracle Database Amazon Aurora

NoSQL & Distributed Stores

MongoDB DynamoDB Cosmos DB Cassandra Redis Elasticsearch OpenSearch

Cloud Data & Analytics Platforms

Snowflake Google BigQuery Databricks Amazon Redshift Azure Synapse Analytics Apache Spark dbt Airflow Power BI Tableau Looker Superset

Platforms & Services

Azure AI Azure ML Azure OpenAI AWS SageMaker AWS Bedrock Google Vertex AI OpenAI API IBM Watson

Frameworks, Libraries & MLOps

pandas NumPy scikit-learn TensorFlow PyTorch XGBoost LightGBM Hugging Face Transformers LangChain Pinecone MLflow Kubeflow

Identity & Access Management

Azure AD Entra ID Okta Auth0 Keycloak OAuth2 OIDC SAML

Secrets & Key Management

Azure Key Vault AWS KMS AWS Secrets Manager HashiCorp Vault

Application Security Tooling

GitHub Advanced Security Snyk OWASP ZAP Dependency Scanning Policy Enforcement HIPAA GDPR SOC 2

CI/CD & Automation

GitHub Actions Azure DevOps GitLab CI Jenkins CircleCI Argo Workflows Tekton

Containers & Orchestration

Docker Kubernetes Helm Kustomize Argo CD Flux (GitOps) Istio Linkerd

Infrastructure-as-Code & Configuration

Terraform Bicep ARM Templates CloudFormation Pulumi Ansible

Monitoring & Observability

Prometheus Grafana ELK EFK OpenTelemetry Azure Monitor AWS CloudWatch Google Cloud Monitoring Datadog New Relic Sentry

Test Automation Tooling

Jest Mocha JUnit NUnit xUnit PyTest REST Assured Karate Selenium Cypress Playwright Appium Postman Newman Pact JMeter k6 Gatling

Testing Types & Practices

Unit Testing Integration Testing End-to-End Testing Contract Testing Performance Testing Load Testing Security Testing Regression Testing Accessibility Testing Static Analysis AI-Assisted Test Design

Messaging & Streaming

RabbitMQ Apache Kafka Azure Service Bus AWS SQS AWS SNS Azure Event Hubs AWS Kinesis Google Pub/Sub NATS

Integration

REST APIs GraphQL APIs Webhooks Enterprise Integration Patterns Apache Camel MuleSoft Boomi Azure Logic Apps

RPA & Workflow

UiPath Automation Anywhere Blue Prism Microsoft Power Automate Camunda Temporal n8n

Low-Code / No-Code

Microsoft Power Apps Mendix OutSystems Retool Appian

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Get solutions chosen for your needs not forced by a single stack. We evaluate the full technology landscape and apply AI only where it delivers measurable value, helping you build the most efficient and cost-effective path forward.
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Frequently Asked Questions

Does ChampSoft use a fixed tech stack?
No. ChampSoft selects technologies based on requirements, constraints, security, and long-term maintainability rather than forcing a single stack.
Choices are evaluated for security, scalability, team fit, operational maturity, and total cost of ownership to support long-lived systems.
AI supports engineering across the lifecycle, but it is applied only where it delivers measurable value and can be governed safely.
Yes. We modernize incrementally to reduce risk, maintain continuity, and improve maintainability and security.
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