Panenco

A pragmatic, modern stack chosen for your context, not ours.

We combine proven engineering foundations with current AI and platform tooling to deliver secure, scalable products in real operating environments, from product UI through backends, cloud, LLMs, agents, connected systems, and infrastructure-as-code.

Panenco developer building a software product

Software engineering

  • Full-stack by default — front and back built together, decisions aligned, integration friction low.
  • React and Next.js for product UIs; Node.js for event-driven APIs, Python for data pipelines and AI workloads, Go where throughput and concurrency demand it.
  • Built for long-term ownership — maintainable foundations your team can extend, not just initial velocity.
Panenco developer integrating LLM capabilities

LLM integration

  • Higher AI output quality through measurable evaluation loops, monitoring, and iteration, not one-off prompts in production.
  • Controlled spend and latency as LLM features move from pilot traffic to steady-state usage across your product.
  • Model selection, routing, prompt strategy, and orchestration across providers so capabilities embed without unnecessary platform rewrites.
Panenco engineer reviewing cloud architecture

AWS / GCP / Azure

  • Operational resilience and predictable scalability through explicit cloud architecture and environment strategy.
  • Roadmaps for migration, observability, and cost-aware operations so spend and risk stay understandable as you grow.
  • Fewer surprises in production through explicit architecture, observability, and operational playbooks.
Panenco engineer working on IoT and connected systems

IoT & connected systems

  • Sensor data ingestion and device-to-cloud pipelines designed for unreliable connectivity and high-volume telemetry.
  • Real-time monitoring, alerting, and anomaly detection so operations teams see issues before they become outages.
  • Zero-downtime cloud patterns for connected products and field-deployed software.
Panenco developer building agentic AI systems

Agentic AI

  • Multi-step agents that can act on your behalf with clear boundaries, escalation paths, and human oversight where it matters.
  • Tool use, memory, and orchestration patterns suited to real workflows, not demos that fall apart under edge cases.
  • Eval frameworks and guardrails to keep agent behaviour on-track as usage and surface area expand.
Panenco engineer managing infrastructure as code

Terraform / Pulumi

  • More reliable releases through repeatable infrastructure workflows and environments your platform team can own.
  • Infrastructure-as-code baselines for provisioning, deployment, and drift control, Terraform and Pulumi where they fit best.
  • Automation and governance that shorten release cycles without trading away security or auditability.

Relevant case studies

A long-standing collaboration in Audit & Assurance technology

A long-standing collaboration in Audit & Assurance technology

Building an LLM pipeline to extract insights from DataCamp's learning videos

Building an LLM pipeline to extract insights from DataCamp's learning videos

Early disease detection in pig farms through sound data and AI

Early disease detection in pig farms through sound data and AI

Measuring every cooking move using computer vision to scale offshore chef training

Measuring every cooking move using computer vision to scale offshore chef training

Developing a web interface for a simulation and testing platform

Developing a web interface for a simulation and testing platform

Building AI agents to manage the office of the CFO

Building AI agents to manage the office of the CFO

Working with Panenco has allowed us to accelerate our product development roadmap across several key areas. Their technical team integrates seamlessly with ours, as we leverage our combined expertise to build innovative solutions for our teams and clients.

Martijn Smet

Martijn Smet

Director Financial Services at PwC Belgium

Talk to us about your technology stack

We can help you move from strategy to implementation with a team that ships.