Accounts receivable has long been one of the most stubbornly manual functions inside a business. Teams wake up to spreadsheets of aging invoices, overloaded inboxes, and a daily chase for payments that feels more like groundhog day than a strategic finance role. Despite a decade of innovation on the accounts payable side, the receivables workflow has remained almost unchanged. Companies with massive volumes of transactions still depend on manual outreach, fragmented systems, and unstructured communication that finance teams must decipher.
Stuut was founded to solve this gap. The company is building an autonomous AR platform that uses modern AI techniques to understand unstructured data, act on it, and eliminate the repetitive grind that has defined AR for decades. For co-founder and COO Ben Winter, the opportunity surfaced at the moment when new AI capabilities finally made it possible to take action rather than simply digitize steps.
“Five years ago this product could not have existed,” Winter explained. “So much of AR is unstructured. It is customer communication, email intent, cash application data, and patterns that were never in a format technology could use effectively. Once we saw that large scale models could read and reason through this information, we knew AR was the place where AI could make a material impact.”
The Pain of AR and the Insight Behind Stuut
AR teams face a unique mix of volume, variability, and urgency. A large CPG brand might handle thousands of deductions each month. A manufacturer may process thousands of small customer invoices where accuracy and timing matter. Other companies face disputes, incomplete documentation, or differences between ordered and received goods. The workflows vary by industry, but the pattern is always the same: too much information, too many exceptions, and too little time.
Winter described the reality in stark terms. Without Stuut, an AR professional starts the day with a static spreadsheet and an impossible list of accounts to chase. They work from the oldest and largest balances downward, try to call or email as many people as possible, and spend the rest of the day triaging inbox chaos.
“It never ends,” he said. “The feeling we heard repeatedly from early customers was that they could never get ahead. The work always wins.”
With Stuut, the experience changes entirely. The agent has already reached out to customers through phone, email, or text. Responses arrive in context, often handled automatically with invoice copies, promise to pay dates, or delivery clarifications already drafted. What once took eight hours can compress into 30 minutes. The AR professional shifts from manual execution to strategic oversight.
A System Built to Understand, Not Template
One of Stuut’s defining engineering principles is the ability to understand and act on intent. When a customer emails asking for a copy of an invoice, the system does not trigger a notification for a human to respond. It identifies the request, finds the invoice, composes a reply, and sends it. When a customer disputes pricing, Stuut drafts a detailed response that the AR team can review and finalize.
Avoiding robotic or intrusive communication was a core design goal.
“If you told an AI agent to collect payments with no guardrails, it would call a customer fifteen times a day,” Winter said. “It has no natural sense of relationship. We built controls, pacing logic, and learning loops so the agent improves the relationship rather than damages it.”
Stuut’s models learn from the behavior of each AR team, their tone, their patterns, and the nuances that shape strong customer relationships. A long standing enterprise account is handled differently from a small recurring account. A high risk customer with a history of late payments triggers a different cadence than a reliable partner.
The system also holds state across modules. Collections, cash application, deductions, and disputes are connected rather than siloed. If a customer requests documentation during a dispute, the agent incorporates that context into future outreach and actions.
Letting Customers Guide the Product
Winter emphasizes that customer feedback is not a marketing buzzword inside Stuut. He and the team sit in dedicated Slack or Teams channels with customers, reviewing interactions, surfacing pain points, and shaping product direction based on real world workflow friction.
“Our customers talk to us daily,” he said. “Their feedback is the reason the product works. We do not just digitize steps. We want to take work off their plate in a way that feels native to their own process.”
Industries with deep deductions workflows guide one set of features. Industries with high volume collections shape another. Stuut encourages customers to adopt multiple modules so the system can stitch context across entire lifecycle events.
The Evolution of the AR Professional
Winter believes that AR teams will evolve into control centers rather than task execution centers. Instead of racing through lists of overdue accounts, they will monitor patterns, identify risk early, and collaborate with finance leadership on strategic decisions that influence credit terms, cash forecasting, and revenue quality.
Some customers already use early pay discounts or strategic outreach windows to improve cash flow. Stuut aims to widen access to those tactics by freeing teams from the daily grind.
“Advanced organizations do this today, but not at scale,” Winter noted. “Every AR team should have the capacity to operate at that level.”
New Product Releases and the Credits Module
One of the company’s upcoming releases is a new credits module, which Winter sees as crucial for long term financial health. Many companies perform an initial credit check when onboarding a customer and then allow credit terms to drift upward simply due to transaction volume. This creates hidden risk, especially when a customer begins to face financial pressure or signals distress.
Winter explained that credit decisions should reflect a mix of internal patterns, external data, payment history, and real time behavior. The credits module is designed to detect trends that require a change in outreach timing, a credit hold, or a proactive conversation that prevents losses downstream.
“You cannot collect from a customer who should never have been granted those terms in the first place,” he said. “We want to help companies avoid unintentional lending.”
A Brand Built Around Real Human Pain
The company recently refreshed its brand to reflect the lived experience of AR teams. Their messaging embraces humor and nostalgia, acknowledging that AR professionals are often overworked, underappreciated, and stretched thin.
“We want people to get home at five, see their kids, enjoy their lives,” Winter said. “There is a lot of talk about AI replacing jobs. We think AR professionals carry knowledge that models cannot replicate. We want to amplify that knowledge, not erase it.”
Jaimen Sfetko, who leads communications, summed up the value proposition simply. Stuut has already helped customers collect millions of dollars they would not have otherwise collected, and it often happens within days. The company measures its success in outcomes: reduced overdue balances, fewer hours spent on manual work, and improved customer relationships.
The Future of Autonomous Finance
Winter sees AR as the foundation of a new class of finance operations. Once an agent can understand messy data, communicate intelligently, and act reliably, it becomes possible to extend that capability to other financial workflows that suffer from the same fragmentation.
But for now, Stuut remains focused on delivering depth in AR. It is a category that touches cash flow, customer experience, and financial stability. It is also a category where even small improvements can have disproportionate impact.
Stuut is not building tools for AR teams. It is building teammates. And if the company succeeds, the drudgery of chasing invoices may finally become a relic of the past.
