Estavita: Transforming Real Estate Transaction Quality Control with Upsonic's AI Framework

Customer Challenge

Estavita, a leading provider of real estate transaction services, was facing significant challenges with its quality control processes. In an industry where precision and compliance are paramount, the company's reliance on manual quality assurance methods was becoming increasingly problematic as transaction volumes grew.

Real estate transactions involve countless documents, verifications, and approvals that traditionally required human eyes on every step

The company's challenges fell into several critical categories:

Manual Workflow Inefficiencies Real estate transactions are document-intensive, with each deal requiring multiple checkpoints and approvals.

Complex Stakeholder Communication Each transaction involved coordination with numerous stakeholders, including homeowners associations (HOAs), municipal offices, utility companies, and financial institutions. Managing the different documentation requirements and communication protocols for each entity created layers of complexity that were difficult to standardize in a manual quality control process.

A transaction in California might have completely different requirements than one in Florida, and a condo purchase has different stakeholders than a single-family home. Our quality control team was essentially managing hundreds of different workflows simultaneously.

Rush Order Complications Particularly challenging were rush orders—transactions that needed to close faster than standard timelines. These high-priority deals required special handling, different verification sequences, and often involved premium fees that needed their own verification. The manual process struggled to adapt to these variations, leading to inconsistent handling and occasional errors.

Upsonic AI Solution

Estavita's journey to solve these challenges began with early experiments in AI, before ultimately finding a breakthrough solution with Upsonic's agent framework.

Initial Approach: Single-Prompt LLM Checks The company's first attempt at leveraging AI involved implementing various single-prompt Large Language Model (LLM) checks to verify document accuracy, customer expectation management, workflow timeliness (SLA compliance), and cost controls.

While this approach showed initial promise, its limitations quickly became apparent. Single-prompt LLMs struggled with the complexity of real estate workflows because they:

• Couldn't comprehend the full scope of a transaction workflow

• Had limited context about specific transaction requirements

• Failed to navigate correctly through multi-dimensional scenarios

"The single-prompt approach was like using a flashlight to inspect a house," explains Chen. "You could see one area clearly, but you couldn't understand how everything connected or get a complete picture of the property."

Transition to Upsonic: Precision and Control The breakthrough came when Estavita transitioned to Upsonic, which allowed them to design specialized decision paths for various scenarios. As a controllable agent framework, Upsonic provided Estavita with:

• Seamless integration of human-machine collaborative workflows

• Robust state management

• A tree-like structure allowing for loops and branches in decision making

"Upsonic gave us the ability to create sophisticated decision trees that could handle the complexity and variability of real estate transactions Instead of trying to force every transaction through the same linear process, we could design intelligence pathways that adapted to the specific requirements of each transaction type."

Using Upsonic, Estavita developed a tree-like structure for their Quality Control application that allowed for loops and branches. This structure enabled the application to follow different paths depending on rush order requirements.

For example:

• When the application detected a rush order, it was directed to the "Rush Order" branch of the tree, which implemented specialized verification sequences

• For standard orders, the application followed a different branch focusing on regular transaction checks

Results and Impact

The tree-like structure provided by Upsonic significantly improved the accuracy and completeness of Estavita's Quality Control process:

Enhanced Decision Making

• More deterministic decision processes with clearly defined pathways

• Reduced randomness of agents going down incorrect paths

• Greater consistency in outcomes across similar transaction types

• More accurate and efficient completion of workflows

Quantifiable Business Improvements

• Reduction in quality control processing time

• Decrease in false positives and false negatives

• İmprovement in rush order handling efficiency

• Reduction in customer escalations related to transaction errors

What used to take team hours now takes minutes.