Software development, amplified by AI

Ship faster with modern tools and intelligent automation

From cloud-native infrastructure to AI-assisted coding, we help teams design, build, and deploy software that scales — without sacrificing quality.

Start building Explore stack
50+ Technologies
10× Faster iteration
AI Native workflows
Technologies

Built on a modern development stack

Production-grade tools across the full software lifecycle — from local dev to global deployment.

Languages & Frameworks

TypeScript, Python, Go, Rust — plus React, Node.js, and FastAPI for full-stack delivery.

  • TypeScript
  • React
  • Go
  • Python

Cloud & Kubernetes

Container-first architecture with Docker, Kubernetes, and infrastructure-as-code for reproducible environments.

  • Kubernetes
  • Docker
  • Terraform
  • Helm

DevOps & CI/CD

Automated pipelines, observability, and GitOps workflows that keep releases safe and predictable.

  • GitHub Actions
  • ArgoCD
  • Prometheus
  • Grafana

APIs & Data

REST, GraphQL, event-driven systems, and vector databases for traditional and AI-native applications.

  • PostgreSQL
  • Redis
  • Kafka
  • gRPC
Artificial Intelligence

AI woven into every stage of development

Intelligence isn't a bolt-on feature — it's embedded in how you write, test, review, and operate software.

  • 01
    AI-assisted coding Context-aware completions, refactors, and test generation in your IDE.
  • 02
    Intelligent code review Automated analysis for bugs, security issues, and style consistency.
  • 03
    LLM integrations RAG pipelines, agent workflows, and model serving on Kubernetes.
  • 04
    Ops intelligence Anomaly detection, log summarization, and incident root-cause analysis.
agent — devforge 
$ devforge analyze ./src

# Scanning 847 files across 12 modules...

✓ Suggested refactor: extract shared auth middleware
✓ Generated 23 unit tests (94% coverage target)
✓ Found 2 security findings — patch available

$ devforge deploy --env staging

# Building container → pushing → rolling update
✓ Deployed v2.4.1 to k8s/staging in 47s

$ devforge ask "Why did latency spike at 14:32?"

→ Correlated with Redis connection pool exhaustion.
  Recommend increasing max connections from 50 → 100.
Workflow

From idea to production in four steps

  1. 1

    Design & prototype

    Sketch architecture, define APIs, and validate with AI-generated scaffolding.

  2. 2

    Build & test

    Write code with intelligent assistance. Automated tests run on every commit.

  3. 3

    Deploy & scale

    Ship to Kubernetes with zero-downtime rollouts and environment parity.

  4. 4

    Monitor & improve

    Observe production, get AI insights, and iterate with confidence.

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