Glossary

Machine learning (ML) is a branch of artificial intelligence that enables systems to learn from data, detect patterns, and improve their performance without explicit programming. Instead of following fixed rules, ML models identify trends and correlations through experience, making automation smarter, faster, and more adaptable over time.

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In finance and administration, machine learning transforms static workflows into dynamic, data-driven systems. For example, Phacet’s AI agents use ML to refine document extraction accuracy, detect anomalies in supplier billing, and match complex financial transactions across multiple sources. Each correction or validation from users strengthens the underlying model, creating a self-improving loop of precision and efficiency.

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Unlike traditional automation, which relies on predictable inputs, ML thrives in the messy, real-world data environment of finance, invoices with different formats, supplier names with variations, or recurring errors in reconciliation. This adaptability is what allows Phacet’s technology to deliver consistent results across diverse business contexts.

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Through document processing and reconciliation workflows, Phacet leverages ML to build trust in automation: every output becomes explainable, traceable, and continuously optimized. The result is a finance function that doesn’t just automate, it learns.