AI-prioritized collections worklists
Machine learning scores open invoices using payment history, customer risk, aging, and behavioral signals so collectors can work from a prioritized queue instead of manual spreadsheets.
Tesorio is an agentic financial operations platform for enterprise finance teams, automating collections, cash application, AR forecasting, and supplier portal management.
Tesorio is an agentic financial operations platform for enterprise finance teams. The site positions it as AI agents that automate parts of the order-to-cash lifecycle, including collections, cash application, forecasting, and supplier portal management.
Its collections workflow prioritizes open invoices, reads and drafts AR email responses, extracts payment promises, and escalates at-risk accounts. The cash application workflow matches incoming payments to invoices, while forecasting and portal-management views help teams monitor expected collections and supplier-side payment work.
Machine learning scores open invoices using payment history, customer risk, aging, and behavioral signals so collectors can work from a prioritized queue instead of manual spreadsheets.
The system reads incoming AR email, classifies routine messages, and drafts contextual replies for payment confirmations, disputes, questions, and escalations.
When customers reply with payment commitments, the platform extracts promise-to-pay dates, confidence, and source information and surfaces them in the dashboard.
Incoming payments are matched to open invoices in seconds, with a reported 95%+ auto-match rate across 200+ customers and automatic handling of partial payments and exceptions.
Forecasting views show collected, forecast, and variance data across week, month, and quarter views so finance teams can compare actuals against goals.
The platform states that Coupa and Ariba portal workflows can be handled autonomously, including invoice submission, payment status tracking, and remittance download.
Use the collections agent to sort overdue invoices, prioritize follow-up, draft replies, and track payment promises when a team is managing a large AR backlog.
Use cash application automation to match wires and other incoming payments to open invoices, then flag partial payments and exceptions for review.
Use AR forecasting views to compare forecasted collections against actual collections and variance across week, month, and quarter time frames.
Use supplier portal automation to submit invoices, track payment status, and download remittance from Coupa and Ariba portals.
Use collector analytics to review contact rates, promise-to-pay conversion, resolution, and dollars collected across a portfolio.
Tesorio’s materials show an enterprise finance platform focused on collections, cash application, AR forecasting, and supplier portal management. It is presented as AI agents that handle parts of the order-to-cash lifecycle for finance teams.
The source does not describe a self-serve signup flow. The pricing page is public, but it does not expose detailed plans or pricing numbers in the provided text, so the site appears to route interested buyers toward a sales conversation.
For collections, the site describes AI that prioritizes accounts, reads incoming AR email, drafts responses, extracts payment promises, and escalates at-risk invoices. For cash application, it matches incoming payments to open invoices and flags partial payments and exceptions. For forecasting, it shows AR forecast and collected-vs-goal views. For supplier portals, it mentions autonomous handling of Coupa and Ariba workflows.
The collection page specifically mentions machine learning priority scores, email triage, promise-to-pay extraction, and collector performance analytics. The home page also references cash application and supplier portal management, while the forecasting page focuses on collected, forecast, and variance views.
The provided sources do not list the full integration ecosystem. They explicitly mention Coupa and Ariba on the supplier portal side, but other connectors are not named in the collected text.