AI Agent

Accounts Receivable AI Agent

Stop chasing payments and start getting paid on time

45 days average to collect. Teams spending 30% of time on follow-ups. Now: automated reminders, prioritized collections, and DSO cut by 12 days.

Benefits

Accelerate cash flow without adding headcount

Late payments tie up working capital and strain customer relationships. Manual follow-ups are inconsistent and time-consuming. The AR Agent automates collections while maintaining professional customer communication.

25%

DSO reduction

40%

Fewer overdue accounts

12

Days faster payment

Agentic Flows

End-to-end receivables management

Automated collections workflow: real-time aging analysis, customer payment behavior scoring, automated reminder sequences by segment, escalation triggers for high-risk accounts, payment plan negotiation support, and cash application matching.

How it works

Intelligent collections automation

The agent monitors aging reports, prioritizes accounts by risk and value, sends personalized reminders at optimal times, escalates strategically, and tracks every customer interaction for your team.

Self-learning agents

The agent improves with every task, adapting to outcomes, applying feedback, and self-correcting using Constitutional AI.

Upto 98% accuracy

As a result of constant feedback loops, Beam AI Agents refine their approach with every cycle, leading to 98% accuracy across flows.

Smart model switching

We call it ModelMesh. Each agent selects the right model for the task, balancing speed, accuracy, and cost in real time.

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Self-learning agents

The agent improves with every task, adapting to outcomes, applying feedback, and self-correcting using Constitutional AI.

Upto 98% accuracy

As a result of constant feedback loops, Beam AI Agents refine their approach with every cycle, leading to 98% accuracy across flows.

Smart model switching

We call it ModelMesh. Each agent selects the right model for the task, balancing speed, accuracy, and cost in real time.

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Integrations

Connects to your financial systems

Native integration with NetSuite, SAP, Oracle Financials, QuickBooks, and Sage. Direct connections to billing platforms like Stripe, Chargebee, and Zuora. Email through Gmail and Outlook.

Implementation

Collecting faster in 10 Days

Connect your ERP and configure collection rules by customer segment. Set reminder templates and escalation triggers. Most teams see measurable DSO improvement within the first billing cycle.

Step 1

Agent discovery

Conduct workshop(s) with relevant stakeholders to identify and prioritize use cases and map the requirements

Step 1

Agent discovery

Conduct workshop(s) with relevant stakeholders to identify and prioritize use cases and map the requirements

Step 2

Agent setup

Develop and launch your first agent with basic logic and integration (process scoping and recording, test dataset of 30-50 examples, baseline agent running and testing with target output mapping)

Step 2

Agent setup

Develop and launch your first agent with basic logic and integration (process scoping and recording, test dataset of 30-50 examples, baseline agent running and testing with target output mapping)

Step 3

Agent training

Test performance and gather feedback from process users (agent optimization up to 80% against expected output, variable-level accuracy measurement and optimization, integrations setup, and feedback API interfacing)

Step 3

Agent training

Test performance and gather feedback from process users (agent optimization up to 80% against expected output, variable-level accuracy measurement and optimization, integrations setup, and feedback API interfacing)

Step 4

Agent live

Extend to more workflows and client teams (live and continuous monitoring, human-in-the loop interfacing, node auto-tuning for automated prompt enhancements, >90% accuracy improvement, weekly business logic improvements)

Step 4

Agent live

Extend to more workflows and client teams (live and continuous monitoring, human-in-the loop interfacing, node auto-tuning for automated prompt enhancements, >90% accuracy improvement, weekly business logic improvements)

Key Features

Smart collections technology

Payment risk scoring

ML-based scoring predicts which accounts will pay late. Prioritize outreach to maximize cash collection efficiency.

Dynamic reminder sequences

Personalized communication based on customer history. Adjusts tone and timing based on relationship and amount.

Cash application matching

Automatically matches incoming payments to open invoices. Handles partial payments and complex remittance.

Demo

See AR automation in action

Watch the agent analyze your aging report, prioritize accounts, send targeted reminders, and escalate appropriately. See how one team reduced their 90+ day balances by 60% in 45 days.