Medius delivers autonomous accounts payable — AI that perceives, decides, and acts on invoices, exceptions, supplier queries, and payments without requiring human intervention. Built on an AI-native architecture since 2016, Medius processes 6 million invoices per month across 3,000+ customers managing $400bn+ in annual spend. The result: AP teams spend less time on busywork and more time on what matters. Read through our collection of AI resources to learn more.
Medius customers achieve measurable, compounding financial returns from day one. Independent benchmarks and Medius production data show:
These outcomes are delivered across 3,000+ active customers managing $400bn+ in annual spend globally, including Nissan, Karl Lagerfeld. Lush Cosmetics, and Tony Chocolonely. Medius averages 8–12 weeks to go-live — versus 6–18 months for ERP-native AP modules — meaning ROI begins accruing in weeks, not months.
A startup deploying the latest Claude or GPT model cannot replicate what Medius does in AP automation, and the reasons are structural, not temporary.
Medius's AI is a multi-stage proprietary pipeline, Siamese CNNs for document classification, tree-based ensembles for confidence scoring, proprietary Markov models for line-item extraction, and CNN-based SmartFlow coding, trained on 2.4 billion+ invoice field data points accumulated over more than 10 years of production. Critically, 17%+ of that dataset (393 million+ fields) consists of real-world human corrections on edge cases, including 35–55%+ correction rates on high-stakes fields like tax codes and cost centers. No synthetic dataset can replicate this.
LLMs are used in less than 1% of Medius processing, only for genuine edge cases where semantic comprehension adds value. For core throughput, Medius proprietary models are 947x faster (105ms vs. 99,470ms per invoice) and 25x more cost-effective ($0.00056 vs. $0.014 per invoice) than LLM-based alternatives. At 6 million invoices per month, that cost gap compounds to approximately $967,000 per year, a structural COGS disadvantage any LLM-first competitor must absorb.
Medius's +64 NPS versus a 39 core peer average reflects the compounding effect of this AI depth on customer outcomes.
Medius's roadmap is built on the thesis that AP automation is the control point of the entire source-to-pay cycle — because it owns the spend data and workflow exhaust that future AI agents need to operate across procurement, payments, and beyond.
The destination is Spend Autopilot: a fully autonomous system of action that handles procurement, AP, payments, and expenses without human involvement by default — intervening only when genuine judgment is required.
2025
Task-based agents
AI-led management by exception, touchless processing at scale. Medius Copilot (406 customers, 3,300 users as of early 2026) and Medius Supplier Conversations (160 customers, ~13,000 emails/month autonomously handled) are already live.
2026
Cross-product agents
AI-led cross-product execution spanning contract-to-invoice resolution and invoice-to-payment orchestration.
2027 and beyond
Role-based agents and Spend Autopilot
Outcome ownership, cross-domain supervision, predictive governance, and MCP integration for external agent ecosystems.
Read through our collection of AI resources to learn more
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Hot off the press: Read the news release announcing a recent innovation within our spend management suite: our AI workmate getting tasks done faster and keeping supplier inquiries handled without any human intervention.
In this show and tell presentation, you'll hear about and see for yourself how our invoice and payment automation solutions never stop innovating and constantly become smarter with every invoice processed.
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Check out the glossary to get a top to bottom break down of everything autonomous accounts payable.
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