Artificial intelligence
P-LAB's AI division develops solutions for the automation, optimization, and continuous improvement of business processes.
Thanks to an approach oriented towards study, experimentation, and innovation, we have successfully applied AI technologies in diverse contexts, demonstrating our ability to rapidly adapt new tools to the most diverse scenarios.
Our AI applications
Data extraction from unstructured documents
PDFs, emails, business documents.
Chatbots and virtual assistants
Instant multilingual support for customers and internal users with standardized internal documentation production.
Natural language queries
Talk to your data: Access databases and BI with natural language queries.
Support for predictive analytics
We use historical series and actual data to evaluate future scenarios.
Translation tools
Multilingual online translation, user support, and translation of technical manuals—all integrated into your business workflow.
Process Automation
We support clients in streamlining processes, particularly in the back office, reducing dependence on the proliferation of non-standard Excel spreadsheets or those requiring extensive data entry and lengthy processing times.
LLM-Agnostic Approach
We adopt an LLM-agnostic approach, selecting the most suitable language model based on the objectives, application context, and client requirements, without vendor constraints.
P-LAB supports its clients throughout the entire project lifecycle, ensuring scalable, reliable, and high-value solutions.
Advanced Technologies
Retrieval-Augmented Generation
Strengthen the generative capabilities of LLMs through access to up-to-date and contextualized information sources
Intelligent Agents
To automate complex tasks and orchestrate complex workflows
Model Context Protocol
For the orchestration and centralized management of AI components
Development and Refactoring
P-LAB is also integrating artificial intelligence into software development and maintenance, with a particular focus on code quality and security.
We use and develop AI-based tools that support code analysis, helping to identify potential issues and suggest improvements, especially during refactoring or upgrade phases.