Glossary

A large language model (LLM) is an advanced type of artificial intelligence trained on massive volumes of text data to understand and generate human-like language. By learning linguistic patterns, context, and reasoning structures, LLMs can process complex instructions, summarize information, and even make context-aware decisions.

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In finance and administration, LLMs represent a major leap forward, moving beyond basic automation to contextual intelligence. At Phacet, LLMs underpin how AI agents interpret natural language commands such as “reconcile supplier invoices with delivery notes” or “flag duplicate payments”. Instead of relying on rigid scripts, the model understands intent and adapts its actions to specific workflows.

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Unlike rule-based systems, an LLM doesn’t need to be told what every field or document means, it infers relationships and meaning across thousands of financial documents. This capability allows Phacet’s document automation agents to extract, classify, and verify information at scale while maintaining human-level precision.

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Phacet combines the power of LLMs with human-in-the-loop supervision to ensure full control, auditability, and compliance. Each action remains transparent: users can trace every extracted field, see the reasoning behind an AI decision, and validate results before export to their ERP or accounting system.

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In essence, LLMs are what make finance automation intelligent, enabling Phacet’s agents to not only perform tasks, but to understand the why behind them. This shift transforms back-office operations from reactive to proactive, setting the foundation for the next generation of AI-driven finance.