Reconciliation is often one of the most time-sensitive and resource-heavy tasks in back-office operations—especially when it comes to verifying payment evidence. That’s why we built PAY-PRO: a smart, autonomous agent designed to handle the complexity, cut through the noise, and bring real clarity and control to the process.
In an era of automation and AI-driven transformation, some operational challenges still rely heavily on human back-office teams, consuming time, attention, and precision. One of the most overlooked yet complex among these is the verification and reconciliation of payment evidence—especially within sectors like utilities, where overdue bills, instalment plans, and fragmented customer communications are the norm.
At Dazerolab, we’ve introduced PAY-PRO: a powerful multiagent system (MAS) built to address this exact challenge, transforming what is traditionally a labour-intensive and time-sensitive task into an orchestrated, intelligent, and scalable process. More than just an AI agent, PAY-PRO acts as a complete digital workforce embedded within BotMasterAI, harnessing the full strength of multiagent collaboration to optimise financial operations.
A real-world challenge
When customers respond to payment reminders—whether for overdue bills or unresolved balances—they often do so by emailing payment confirmations, uploading screenshots, attaching receipts, or sending PDF statements. These messages typically arrive via various designated inboxes, creating a growing queue of manual tasks for back-office teams.
Each case requires validation:
- Has the customer truly paid?
- What is the payment referring to—a bill, an instalment, a partial settlement?
- Does the amount match any open item in the billing system?
- Are the attached documents valid, legible, and sufficient?
This cascade of micro-decisions, repeated thousands of times per month, drains teams, slows down resolution cycles, and introduces room for inconsistency.
From manual verification to autonomous reconciliation
PAY-PRO is engineered to take over this workload. As an autonomous Gen-AI agent, it’s trained to receive and analyse unstructured inputs—emails, attachments, scanned receipts, even images of bank transfers—and classify them intelligently.
How does it work? It’s easy, let’s look into it together.
Its first task is to determine what kind of evidence has been received. It validates the documentation, ensuring that nothing essential is missing. If the submission is incomplete or unclear, PAY-PRO doesn’t just stop—it triggers a request for additional information, acting proactively to move the case forward.
Once the data is complete, PAY-PRO proceeds with reconciliation. It cross-references the extracted information with the client’s billing database to find a match:
- Who made the payment?
- What is being paid (invoice, instalment, penalty)?
- Does the amount match any outstanding balance?
- Is the payment partial, final, or incorrectly attributed?
The agent doesn’t operate on rigid rules—it reasons, draws correlations, and performs advanced checks to distinguish legitimate evidence from errors or even fraudulent attempts.
A smarter MAS, a lighter back-office
What sets PAY-PRO apart is not just its intelligence, but the system it works within.
Powered by BotMasterAI, PAY-PRO is a Multiagent System (MAS): a decentralised architecture where multiple AI agents, each with a distinct responsibility, work collaboratively. Within this MAS, PAY-PRO may be paired with other agents—like one handling email parsing, another dealing with metadata extraction, and yet another responsible for routing outcomes to credit recovery systems or CRMs.
This orchestrated approach means that back-office operators only intervene when human judgment is genuinely required. Thanks to configurable thresholds and decision rules, businesses can define exactly when an agent should escalate a case for manual review, maintaining full control over the workflow and agent behaviour. In practice, thousands of monthly tasks are reduced to just hundreds—those that are truly ambiguous or require human oversight.
It’s a shift in paradigm: the AI doesn’t just support—it leads. It works autonomously, escalates when needed, and continuously improves based on feedback and new data inputs.
Embedded flexibility, enterprise-ready
PAY-PRO has been designed with enterprise-grade architecture in mind. It integrates easily with existing systems—whether you’re managing customer care via a CRM or orchestrating collections through specialised platforms.
Its Gen-AI core makes it template-free and highly adaptable: whether the payment evidence comes from a scanned image, a screenshot, or a PDF with inconsistent formatting, PAY-PRO can process, interpret, and act accordingly.
As with every BotMasterAI agent, PAY-PRO benefits from:
- Rapid integration via API, batch, or widget modes.
- GDPR-compliant infrastructure, hosted on AWS Europe (Frankfurt zone).
- Real-time performance, powered by microservices and event-driven architecture.
Built for real business impact
In sectors where payment verification can make or break operational cash flow, PAY-PRO offers not just automation, but assurance. It frees up human teams, reduces error rates, and accelerates time-to-resolution.
But more importantly, it brings structure to unstructured processes. It’s no longer about dealing with each email or attachment individually—it’s about embedding that entire workflow into a smart, AI-powered system that scales.
PAY-PRO is currently in development but already being shaped through real-world scenarios and business needs. As it joins the BotMasterAI workforce, it carries with it the mission that defines every Dazerolab solution: solving real problems, at scale, with intelligence. Full release is expected by the end of 2025, allowing organisations to integrate PAY-PRO into their operations and redefine the way they manage payment evidence reconciliation.
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