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Applied artificial intelligence

AI that solves real business problems.

We integrate AI and machine learning solutions that automate processes and create real competitive advantage.

  • Human review where it matters
  • Data protected, in the EU
  • Integrated with your systems
agente · bandeja de soporteExample
Four ways to apply AI

Choose by the problem, not the technology

Which one do I need?

What is happening today?

Your fit

Agentes de IA para empresas

Desarrollamos agentes de IA que leen correos, consultan tus sistemas y ejecutan tareas, con revisión humana donde importa. Del diagnóstico a producción.

See solution
What it includes

Capabilities

Artificial intelligence has stopped being a promise and become a practical tool. We help companies identify where AI creates the most value and build concrete solutions: from intelligent chatbots to predictive models and computer vision systems.

It fits if…

  • You have repetitive processes eating the time of qualified people
  • You want to predict customer behaviour or operational anomalies
  • You need to process natural language: documents, emails, contracts
  • You have untapped data that could create value
  • You want to embed LLMs in your products or internal workflows

What it includes

  • Custom machine learning and deep learning models
  • LLM and generative AI integration into products
  • Natural language processing (NLP)
  • Computer vision and image analysis
  • Personalised recommendation systems
  • MLOps: model deployment, versioning and monitoring
Tech stackPythonPyTorchScikit-learnLangChainOpenAI APIFastAPIMLflowHugging FaceFAISS
How we work

From assessment to production

  1. 01

    Use case diagnosis

    We assess technical feasibility and potential ROI before committing resources. Many AI projects fail because they start the other way round.

  2. 02

    Data analysis

    We audit the quality, quantity and accessibility of the available data. Without good data there is no good AI.

  3. 03

    Model development

    Choosing and tuning the approach: pre-trained models, RAG, fine-tuning or training from scratch, depending on the case.

  4. 04

    Evaluation and validation

    Evaluation metrics defined, testing with real data and tuning until the agreed quality threshold is met.

  5. 05

    Integration and MLOps

    Model deployed as an API, integrated into your existing systems, with performance and drift monitoring in production.

Why Polaris

What sets us apart

01

Applied AI, not theoretical

We focus on use cases with measurable ROI, not research projects with nowhere to land.

02

Integrated with your systems

Models plug into your existing applications through standard APIs.

03

Models in production

Real experience deploying, monitoring and maintaining models in production environments.

Frequently asked questions

Everything you need to know

It depends on the use case. Many generative AI solutions and pre-trained models need little data of your own. For custom models we assess feasibility against the data volume you have.

We work with architectures that process sensitive data without sending it to third parties, using on-premise models or our own infrastructure inside the EU.

A generic LLM knows neither your business nor your data. We build systems that combine language models with your knowledge base, integrations with your systems and quality controls specific to your use case.

Where to start?

In the free assessment we review your processes, pick the case with the best return and tell you what it would take to put it into production.