AI-Powered Development with Claude Code, Copilot & Codex
Our engineers use Claude Code, GitHub Copilot, OpenAI Codex and Gemini to ship production-grade code 30–50% faster without sacrificing quality.
Core Capabilities
30–50% Faster Delivery
AI-assisted code generation, boilerplate elimination and rapid prototyping — without cutting corners on quality or tests.
Production-Grade Quality
Every AI-generated line is reviewed, tested and refactored by senior engineers. We never ship unreviewed AI output.
AI-Assisted Testing
Automated test generation with AI — unit tests, integration tests and edge case identification at scale.
Auto-Documentation
AI-generated JSDoc, PHPDoc, README files and architecture diagrams keeping your codebase self-documenting.
Faster Debugging
AI-powered code review and bug detection catches issues before they reach production, reducing QA cycles by 40%.
Architecture Guidance
We use AI to evaluate architectural decisions, spot scalability issues and generate PoC code for evaluation.
Tools & Platforms
Technical Questions
Answered
Can't find your answer? Talk to our team directly →
Never. Every line of AI-generated code is reviewed, tested, and approved by a senior engineer before it enters our codebase. AI tools are used to accelerate specific tasks — boilerplate, test generation, documentation — not to replace engineering judgement. Our quality standards are unchanged.
Our primary tools are Claude Code for agentic multi-file tasks, GitHub Copilot for in-editor suggestions, and Cursor for codebase exploration. We also use v0 for rapid UI prototyping and Devin for automated PR review. Tool choice depends on the task type.
Yes — faster delivery with the same senior talent means lower overall project cost for equivalent scope. You get production-grade code, faster. Many clients reinvest the saved budget into additional features within the same engagement.
AI tools can occasionally suggest insecure patterns (SQL injection vectors, weak authentication). Our engineers are trained to identify these and our code review process includes OWASP-aligned security checks on all AI-generated code before it merges.
In-Depth Technical Reads
Multi-Tenant Telephony: What Tenant Isolation Actually Requires
A SIP domain per customer is where isolation starts, not ends. The switch, the dialplan, carrier calls, the database and webhooks each need a boundary.
Read Article →Building a Browser Softphone on FreeSWITCH and JsSIP: What Actually Broke
A case study from our own call-centre platform: SIP over WebSocket behind a TLS proxy, transfers that raced the audio, and SIP isolation between workspaces.
Read Article →LiveKit vs Jitsi in 2026: Architecture, Scaling and What Each Actually Costs
Two Apache-2.0 SFUs that are not interchangeable. Architecture, how each scales, and why LiveKit Cloud and Jitsi as a Service bill on meters that do not convert.
Read Article →Start an AI-Powered Project
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