Self-Hosted AI Agents for Your Business in Malaga, Spain

We deploy AI agents for every department in your Malaga business on your own hardware. No cloud fees, full privacy.

Self-Hosted AI Agents Benefits for Malaga Businesses

• Works with the Hardware You Already Have: Malaga's tech park (PTA) is Spain's largest, hosting over 630 companies and 20,000 workers. The city's bet on becoming Europe's 'Silicon Valley of the South' has attracted billions in investment and created massive demand for software development services.
• One Agent per Department: Marketing, sales, HR, finance, support and ops each get their own agent, scoped data, scoped tools, scoped permissions. They share hardware, not secrets.
• Zero Per-Token Fees: Once the hardware is paid for, every inference is free. Teams running at volume typically save 70-90% vs. cloud APIs within the first year.
• Full Data Privacy: Prompts, documents, conversations and outputs never leave your network. Perfect for legal, healthcare, fintech or any sector with confidentiality constraints.
• Tuned on Your Data: We fine-tune smaller open-source models (Llama, Qwen, Mistral, Phi) on each department's historical data and tone. Smaller model + your data often beats GPT-class models on your specific tasks.
• MLOps Included: Prometheus + Grafana dashboards for GPU utilisation, inference latency, cost/inference and accuracy drift. Scheduled model updates and rollback plans baked in.
• Fits the Tools You Already Run: Our Spanish team is perfectly positioned to serve Malaga's international tech community, working fluently in both English and Spanish.

How We Build Your Self-Hosted AI Agents in Malaga

1. Department & Workflow Audit: We map each department in your Malaga company and identify the top 3 AI-automatable workflows per team.
2. Hardware Sizing (or Audit): We benchmark the models required against what you own. If hardware is missing, we recommend exact SKUs (Mac Mini M4, DGX Spark, RTX 5090, H100) with a clear cost/benefit.
3. Install & Harden: We install the runtime stack (Ollama, vLLM, TensorRT-LLM, MLX on Apple Silicon), harden the network (no egress, VLAN per agent) and set up backups.
4. Agent Build per Department: Each agent gets its own knowledge base (RAG), tool set (your APIs, not the internet) and permission scope. Marketing can't read HR data, and vice versa.
5. Fine-Tuning & Evaluation: We fine-tune on each department's historical data and benchmark against the commercial cloud alternative on your specific tasks.
6. MLOps & Ongoing Care: Dashboards, alerts, scheduled model upgrades, quarterly fine-tune refreshes. On-call support when something breaks.

AI Technologies We Use

From self-hosted open-source models to cloud APIs, we choose the right tool for each self-hosted ai agents use case.

Related services

Neighbouring problems we also solve, in case the one that brought you here is not the first to tackle.

• AI Consulting
• AI Agents & Automation
• AI Task Automation
• All our services: The full catalogue, from web and mobile to AI, data and maintenance.

Self-Hosted AI Agents in Malaga: FAQ

Can you really run this on a Mac Mini?

Yes, a cluster of 4-8 Mac Mini M4 Pro runs department-level agents very comfortably for small-to-mid teams. Apple Silicon with MLX is surprisingly strong on LLM inference per watt and per euro. For heavier workloads we graduate you to NVIDIA DGX Spark (a desktop-sized AI workstation) or RTX 5090 rigs, and further up to H100/H200 servers.

What's the NVIDIA DGX Spark?

A desktop-format AI workstation from NVIDIA, ~1 petaflop of AI compute, 128GB unified memory. Enough to run Llama 70B and similar models locally. Perfect for mid-size companies that want serious on-prem AI without the cost and complexity of an H100 server.

Can agents from different departments really stay isolated?

Yes, each agent runs as a separate process, with its own VLAN, its own permission scope, its own tool manifest and its own RAG index. Marketing's agent can't read the payroll folder; HR's agent can't post to your ad platforms. Hard boundaries enforced at the OS + network layer, not just prompt-engineering.

Which open-source models do you use?

Whichever open-weight model is the best available for your task on the day we deploy, meaning one you can download and run on your own server without going through anyone else's API. The list is deliberately not fixed. This field moves every few months and pinning a name here would age badly. In practice we pick from the main open families (Meta, Alibaba, Mistral, Microsoft and the specialised speech and vision projects), sizing the model to your hardware, a large one for a department agent on a proper GPU server, a small one for a compact machine. Everything we deploy is under a permissive licence, and swapping the model later is a configuration change, not a rebuild.

When does it make financial sense vs. using OpenAI/Anthropic APIs?

Roughly, if your team uses AI for more than ~30€/day of cloud API, self-hosting pays for itself inside 12-18 months on a Mac Mini cluster or a DGX Spark. For enterprise volumes, H100 servers break even in 4-6 months. We run the math honestly. We'll tell you if cloud is cheaper for your case.

Can you combine on-prem with cloud for peak load?

Yes, hybrid is a common pattern. On-prem handles baseline load (cheap, private); cloud fallback catches peaks (expensive, but only when needed). We set up automatic routing with a circuit-breaker so your system stays responsive even if your on-prem hardware fails.

How much does a deployment cost?

It depends on the tier you need, a Mac Mini M4 Pro cluster for a handful of department agents, an NVIDIA DGX Spark setup, or RTX 5090 rigs and H100 servers once you are running many agents. We quote hardware transparently at cost, and charge for deployment and ongoing MLOps, so the number tracks the machines you actually need.

Do you work with Malaga businesses remotely?

We work with companies across Malaga's tech ecosystem, from the PTA technology park to the growing startup scene in Soho and the digital businesses along the Costa del Sol.