From Al- powerred backends to on-premisses LLM and real-time video - the full stack behind 120 + delivered projects
OUR STACK
Hands-on experience across 120+ projects - not just familiarity, but production-grade delivery.
At AMCOLAB, we work with the best technologies available to provide nothing less than code excellence.
Everything you need to know about our technology approach and delivery process.
We start from requirements, team workflow, and long-term maintenance. We balance innovation with stability, ensuring the selected technologies align with your business goals and future scalability needs.
Yes. We can maintain and extend existing systems. Our team is experienced in auditing legacy code and implementing modern features or integrations while preserving the integrity of your current operations.
We use n8n, Make, Yoom, Zapier, and Google Apps Script for workflow automation — depending on client environment and budget. For platform integrations, we work with Shopify, Kintone, LINE API, Stripe, GMO Payment, Ship&Co, Salesforce, and more. Where no-code doesn't cover the requirement, we build custom API connectors.
Yes — when it clearly improves operations. Our AI capabilities span: LLM integration (OpenAI, local models via Ollama/vLLM), RAG document search, computer vision (Mask R-CNN, YOLO), speech-to-text, OCR (PaddleOCR, Tesseract), and AI workflow orchestration (Dify, LangGraph). We've built AI systems ranging from LINE chatbots to on-premises enterprise RAG over 40TB of data. We recommend AI where it reduces real manual work — not where it adds complexity.
Code review, testing, staging releases, and monitoring-ready practices are core to our workflow. We implement automated CI/CD pipelines (GitHub Actions, CircleCI) to ensure every update is verified before reaching production.
We support AWS (primary) and GCP, tailoring the infrastructure to your specific regulatory and performance needs. We also handle on-premises and air-gapped deployments for enterprises with strict data residency requirements.
We build agentic AI systems — LLMs that don't just answer questions but take sequences of actions across tools and systems. Our stack includes MCP (Model Context Protocol) for structured tool-use, Claude Code and OpenAI Codex CLI for AI-assisted code generation, Gemini CLI and OpenClaw for multi-step agent workflows, and Dify for visual orchestration of multi-agent pipelines. We apply these to internal automation, document processing, report generation, and developer productivity — where the agent handles multi-step tasks that previously required human judgment at each step.
