What We Do
Capabilities Overview
A comprehensive look at our technical expertise, tools, and processes that power successful software projects.
Development
- React / Next.js / Vue
- Node.js / Python / Go / Java
- .NET / Ruby on Rails
- TypeScript across the stack
- Microservices and monolith to micro migrations
Cloud & Infrastructure
- AWS / Azure / GCP
- Kubernetes & Docker
- Terraform & Pulumi IaC
- CI/CD pipelines
- Serverless architectures
AI & Data
- Machine Learning / Deep Learning
- NLP & Computer Vision
- LLM integration and fine tuning
- Data pipelines (Spark, Airflow)
- Real-time analytics
Mobile
- React Native / Flutter
- Swift / Kotlin native
- Progressive Web Apps
- App Store optimization
- Push notifications & analytics
Data Engineering
- ETL/ELT pipelines
- Data warehousing (Snowflake, BigQuery)
- Stream processing (Kafka)
- Data quality & governance
- BI & visualization
Team & Process
- Agile / Scrum / Kanban
- DevOps & SRE practices
- Quality assurance & testing
- UX/UI design
- Technical architecture
Questions? We've Got Answers
Your Capability Diligence Questions, Answered.
Direct answers on which technical capabilities are worth verifying carefully for your specific project type.
Featured Answer
Which technical capabilities are most worth verifying carefully for a specific project?
Verification priority depends on project type. For AI and ML projects, verify production deployment experience and MLOps capability, not just notebook work. For cloud and DevOps, verify capability at the scale you actually need, since experience differs significantly between small and enterprise. For mobile, verify recent App Store and Play Store launches with the specific platforms you target. For data engineering, verify pipeline reliability under real load rather than ad-hoc query work. Tailoring verification to project type produces better diligence than checking every capability uniformly.
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