Pielabs is an engineering-first company focused on building real, production-grade systems. We work with ambitious teams to modernize their technology stack, implement practical AI solutions, and develop hardware products that scale. Our approach is simple: no hype, no unnecessary complexity—just robust systems designed to perform in the real world.
Upskill your team and implement a modern, production-ready engineering stack, including Golang, Rust, and Python, alongside cloud-native infrastructure, CI/CD, microservices, and observability with Docker, Kubernetes, Prometheus, Grafana, and Graylog.
Build AI systems that deliver accurate, context-aware answers using your data, with Retrieval-Augmented Generation (RAG), vector databases, structured data pipelines, and secure LLM integrations deployed in scalable, production environments.
Design and deliver production-ready hardware + firmware systems, covering system architecture, component selection, PCB design, embedded software, and manufacturing—while ensuring every decision aligns with performance goals and meets global ISO compliance standards.
Modern engineering requires more than just coding—it demands the right tools, architecture, and operational discipline. We set up your developer infrastructure, CI/CD pipelines, and software architecture to maximize speed and reliability so your team can focus on shipping features safely.
We help businesses move beyond AI experimentation to real, production-ready systems. Our focus is on building Retrieval-Augmented Generation (RAG) solutions that provide reliable, authoritative answers based on your internal data.
We help businesses move from early concepts to fully realized, production-ready hardware products. Our focus is on building reliable, scalable embedded and IoT systems while guiding the right technical decisions at every stage—from architecture to manufacturing.
We train your in-house team to adopt and effectively use modern technologies, including: - Programming: Python, Golang, Rust - AI Systems: LLMs, RAG architectures - DevOps: Docker, Kubernetes - Observability: Prometheus, Grafana and Graylog
01Understand your goals, constraints, and current systems
02Create scalable architectures and implementation plans
03Develop with a focus on quality and maintainability
04Ship production-ready systems
05Optimize, monitor, and continuously improve
