AI-native products
We build proprietary software products with AI at the core: autonomous agents, intelligent data processing, and automation, trained and validated in our own lab.
// AI products built in Argentina
Argencode is a product company: we build our own software and IP on NVIDIA-accelerated computing. A team of certified systems engineers researching, training, and integrating AI models in our own lab, on NVIDIA DGX Spark hardware.
Of in-house AI compute
Technologies mastered
IP developed in-house
Parameters fine-tuned locally
// Technology
Everything we develop is our own intellectual property: products designed, trained, and built in-house by our engineering team.
We build proprietary software products with AI at the core: autonomous agents, intelligent data processing, and automation, trained and validated in our own lab.
Our IP is built on NVIDIA-accelerated computing: local model fine-tuning and inference on our own DGX Spark hardware with the Grace Blackwell architecture.
Our products ship as modern web platforms — fast, scalable, and built with React, Next.js, and the best stack in the ecosystem.
We bring our technology to iOS and Android with high-quality native and cross-platform applications.
We use cloud infrastructure (AWS, Vercel, Google Cloud) to deploy and scale our own products. We are not a cloud services provider or a reseller: the cloud is our tool, not our business.
We design the APIs, integrations, and data architectures that power our products, built to grow with every release.
// About the company
Argencode is a young, privately held company officially incorporated in Argentina, dedicated to building proprietary software products and IP on artificial intelligence and accelerated computing.
To democratize access to state-of-the-art artificial intelligence by building products that bring accelerated computing to organizations that cannot leverage it today.
We are one of the few teams that combine deep enterprise systems expertise (IBM i, AIX, COBOL, RPG) with applied AI research on our own NVIDIA hardware: we build products that connect the legacy world with the next generation of computing.
Our business model is building proprietary technology and products. The intellectual property we create — fine-tuned models, agents, platforms — is the heart of the company.
// Who we are
A fully in-house engineering team: we combine the reliability of developers with long track records in mission-critical systems and a new generation building artificial intelligence products and exploring quantum computing.
Our team is made up of systems engineers and certified professionals who guarantee quality in every delivery.
Our team masters technologies like COBOL, RPG, Pascal, C, C++, C#, Python, and Go: that enterprise-world knowledge feeds the products we build to connect it with AI.
Proven experience on IBM i, AIX, Linux, and Windows Server: we are equally at home in mission-critical enterprise environments and modern infrastructure.
A new generation of talent pushes us beyond the limits, integrating AI into real products and processes, with our own AI lab running on NVIDIA DGX Spark.
We explore the next frontier of computing so your business is ready for what comes next. Our team includes professionals certified in quantum computing and Qiskit.
// AI Lab
The heart of Argencode is our AI lab, equipped with an NVIDIA DGX Spark: the personal AI supercomputer built on the Grace Blackwell architecture. This is where we research, train, and validate the models and agents that power our products: fine-tuning, local inference, and autonomous agent development on our own hardware. We also run live demos and hands-on labs to show our technology working in real time.

Prototyping and validating our AI products on real hardware, with fast experimentation cycles and no cloud dependency.
We build agents that plan, use tools, and execute tasks continuously: the core of our local AI product line.
The GB10 superchip delivers up to 1 petaFLOP of AI performance and 128 GB of unified memory for large-scale models.
Fine-tuning of models up to 70B parameters and optimized local inference with frameworks like vLLM, llama.cpp, and Ollama.
Multiple DGX Spark units can be connected in a multi-node cluster to run larger models and scale inference and fine-tuning workloads.
Your data never leaves the lab: ideal for testing with sensitive or regulated information.
Book a live demo of our AI products running on the DGX Spark.
// Products in development
Argencode invests in R&D to create artificial intelligence products that solve regulatory and healthcare challenges, combining profitability with social impact.
A product in development that uses machine learning algorithms to help pharmaceutical lab teams comply with ANMAT regulations and quality standards such as ISO 9001: support for regulatory documentation, process traceability, early deviation detection, and fewer quality-control errors.
A commercial solution focused on creating value for the industry. It does not imply an agreement with ANMAT: we help companies comply with its regulations.
An initiative aimed at collaborating with Argentina's National Cancer Institute, applying classification models to organize and prioritize screening data. Two Argencode team members previously worked at the Institute, giving us first-hand knowledge of the domain, its processes, and its real needs.
All work with sensitive health data happens in the local, secure environment of our lab: the data never leaves it.
// Dual purpose
We build cutting-edge AI applications that solve concrete problems in regulated industries, generating the revenue that sustains and scales our R&D investment.
We contribute to public institutions by applying our technology to the common good: the same compute and engineering capability, put to work for the population's health.
Argencode is a constant pipeline of talent: several of our team members teach Programming at Universidad Abierta Interamericana (UAI), which lets us train and bring in new generations of developers while strengthening the bond between academia and industry. Combining real domain experience — like that of our former National Cancer Institute members — with active academic teaching is one of the pillars of our team.
// How we create
We identify real market problems and explore how AI and accelerated computing can solve them better than existing solutions.
We prototype and validate on our DGX Spark: model fine-tuning, agents, and benchmarks on our own hardware, with controlled data.
We turn validated experiments into robust products: short sprints, frequent releases, and engineering quality in every iteration.
We take the product to production, measure real-world usage, and evolve it continuously. Every release strengthens our IP.
// Contact
Reach out to book a demo of our AI products or to explore partnerships and opportunities. We reply within 24 hours.