Custom Enterprise Software Development Services

One of the largest American retailers needed a system that would be able to predict the demand for their goods, estimate future purchasing behavior of customers, and provide recommendations on ideal inventory levels for hundreds of products.

Our team developed a machine learning-powered forecasting platform in only seven weeks. This solution can analyze historical sales data, generate demand forecasts, and provide actionable recommendations that help businesses maintain optimal stock levels while improving business intelligence solutions.

The client wanted a secure video interviewing platform that eliminates the need for manual-intensive screening and enables faster high-quality candidate identification.

We developed a web-based interviewing platform called Willo, where recruiters can create interview templates in a couple of minutes, and candidates can submit the video of their responses from any device without installing any extra software. This platform simplifies customer interactions for recruiters and candidates, as well as automates the early stage of the hiring process.

When the pandemic broke out, businesses had to find a way to ensure that their buildings were not overoccupied and that social distancing was properly followed.

We developed a computer vision application powered by AI called People Counter that recognizes different kinds of objects, counts visitors automatically, estimates social distancing, and works autonomously without human supervision.

Product managers used to take nearly 45 minutes to process vague requests into a structured project ticket, and this caused delays in sprint planning while increasing project risk levels.

To solve this issue, we built an AI assistant called RIV that converts natural language into structured subtasks, predicts delivery risks, extracts dates and project entities automatically, and integrates with Jira, PostgreSQL, Asana, and ClickUp, among other tools. The platform uses predictive analytics to identify risks before sprint planning begins.

Finance departments utilized manual checks and rules-based validation, which are not very effective in detecting costly accounting anomalies across ERP modules.

This made us develop an AI anomaly detection solution that performs continuous monitoring of ERP transactions with the use of unsupervised machine learning. The advantage of this solution is that it does not rely on predetermined rules but instead learns normal behavior and can flag any suspicious activity with explainable alerts and predictive analytics.

New sales representatives faced challenges during the training process of learning a customized CRM, leading to slow onboarding and reduction of data quality.

Our solution was an LLM-powered assistant built directly into the CRM. It is able to answer questions, log customer information, perform CRM updates through validated API calls, and automate routine workflows while improving customer interactions.

A medical clinic wanted to reduce the administrative workload that comes with scheduling appointments while enhancing the patient experience.

We developed an AI voice assistant that checks patient records, determines what the appointment is for, recommends available slots, books the appointment automatically, sets SMS reminders, and explains the necessary preparation before the visit. The assistant is integrated into the clinic’s scheduling system.