We converted millions of energy usage data points to visually consumable analyses.

Our client is an industry pioneer with over two decades of experience in energy management and sustainability services for hundreds of enterprises worldwide, including several Fortune 100 companies. They offer unique programs and services to help their customers navigate the volatility and diversity of the global energy markets. The client’s deep market expertise and technology solutions enable them to be pioneers at helping their customers view energy and sustainability challenges strategically and to make fact-based decisions supporting their financial and operational priorities.

Since Expeed Software has been retained as their strategic partner for the last 10+ years to provide end-to-end solutions, they presented us with a unique challenge they were facing. They wanted a platform that could unify all the millions of data they have collected over the years about energy consumption patterns and present analytical data that could be used to suggest sustainable energy programs.

Through their energy management services offering, our client had accumulated a wealth of data regarding their customers’ energy needs, usage, and spending. They then wanted to convert all of the data into meaningful information, insight, and services in the fast-emerging sustainability practices area. For this, they wanted several secure and scalable technology solutions to streamline data collection, analyze the vast amounts of data being collected, and securely disseminate the resulting information on a periodic and on-demand basis to the respective clients as well as to automate reporting of the customers’ sustainability practices and progress to various governmental and non-governmental entities providing regulatory oversight in the space. They also wanted to develop automated solutions for their customers to capture their sustainability-related goals and facilitate decision-making regarding short and long-term initiatives that would help achieve those goals.

The client database used vastly different energy data collection processes by customers, ranging from manual entry to automated data feeds, resulting in a lack of data integrity. There were also tremendous disparities in business practices, scale, and sophistication of operations among the customer base.

Expeed team analysed the functional and system requirements for the solution and came up with overall solution architecture and design approaches for the various functional groups. The solution delivery was creatively structured into a program with several concurrent projects deftly managed and executed in close collaboration with the client team.

Our platform has helped the client translate many years worth of data into sustainable energy action points, which they are using in collaboration with other organizations and the government to put in place sustainable energy practices and products. As their strategic partner, the team at Expeed continues to add features to their platform, increasing efficiency and ease of operation.

A module was created to help customers track their carbon emissions and maintain any caps, either self-imposed or government-imposed, on the corporation.

We developed a comprehensive platform capable of turning out millions of energy usage data points into actionable insights for a prominent energy management company.

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Energy Usage Analytics Platform

UTILITY & ENERGY

Logistics is definitely one of the most time-critical industries there is. It is also one that involves a lot of interdepartmental coordination, documentation processing, and compliance maintenance on the go. Hence, most logistics applications bear the burden of needing to enable quick access to multiple service functions without cluttering the app or compromising the compliance processes. Our client was facing a similar issue when they reached out for a UI/UX solution that would not only improve the efficiency of the application but also offer better user experiences.

Our client, who leases, services, and maintains semi-trailers to companies of all sizes, was unhappy with the layout and design of their existing application interface and requested a complete revamp. Based on the feedback they received from their clients, the application was difficult to navigate and time-consuming when trying to request time-critical services. Our client believed a design revamp would be instrumental in fixing the problems.

Our design team reviewed the application and quickly determined the app desperately needed a UX revamp, not just a design makeover. Here are some of the glaring issues we discovered during our initial analysis:

Information Density: The main user interface was densely cluttered with all kinds of information (some relevant and some redundant) about services and assets, making it very hard for users to quickly navigate within the application.

Unsatisfactory User Journey: At various points within the app, the user was required to complete redundant compliance steps to utilize time-critical features like ‘Request for Roadside Assistance’ or ‘Status Updates.’

Design Inconsistency: The existing UI was not supportive of the app’s functionality and intent, and needed major improvements. The core design was not empathetic to customer needs.

Like all UX projects we undertake at Expeed, this one too meticulously followed our UX Process – a tried and tested formula which was developed to ensure that the apps we create are robust and scalable. Client and stakeholder interviews were conducted to fully understand the scope of services being offered by the company, and to approximate the delivery timeline expectations. A user persona that was drawn from customer profiles of similar logistics company managers and entrepreneurs was then used to derive an empathetic understanding of the app’s requirements and use cases. The team recreated the emotional temperaments and expectations from a user standpoint to identify all touchpoints that would benefit the most from UX enhancements and help make the app significantly more intuitive.

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The research allowed the team to draw definitive conclusions about the ideal responses to various app scenarios – a critical element to generating the best user journey experience. This also paved the way for creating workflows and a design system that gave prominence to time-critical features and reduced redundant compliance processes.

Once user expectations and requirements were identified, we zeroed in on all the problems with the existing app and any potential additional issues that may crop up while revamping the application. The issues were first categorized broadly based on service functionalities and their significance and contribution to achieving the overall business goals of the client. Creative brainstorming sessions were then conducted to derive the most feasible solutions, keeping in mind the practical limitations users might experience under different circumstances. The iterative ideation process enabled us to come up with unique features, tied to more efficient workflows, that enabled the application to respond better and coordinate between user demands and business requirements.

Once the blueprint for the user journey was ready, we dove headfirst into the details of design and feature implementation, starting with the fleet dashboard. As the primary user interface, and as one that is expected to make or break app engagement, our first task was to simplify and bring order to the dashboard. We started by categorizing information and grouping them under related services/functions. All time-critical information, like locations of trailers, requests for roadside assistance, active routes, service maintenance updates, etc., were given more visibility, while less time-critical details like trailer contracts, asset information, etc., were tabbed. While the status of vehicle services was given priority on the dashboard, the details of the repairs were made accessible only upon clicking the ‘More Details’ button.

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A great UX is one that understands the importance of customizing solutions for user needs and improving the heuristics or the speed of use. It is essentially the time taken by an app to perform a task (or a set of tasks) requested by the user. This often goes hand-in-hand with customized solutions for specific user needs. For instance, the time taken and complexity involved in fixing a flat tire depend on the size of the vehicle and its location accessibility. The heavier the vehicle, the more urgently the app needs to push the request to concerned managers. Hence, we changed the task flow for flat tire requests and customized them based on vehicle type and location. Such improvements not only helped the user have a more satisfying experience whilst using the application, but also helped the business save costs by reducing response time to repair/service requests.

Here are a few other touchpoints within the app that benefited from process/navigational flow improvements:

: By removing some redundant steps, we reduced a 7-step ‘Complaint Registration’ process to a simple 3-step solution, without compromising on any compliance requirements.

: Users who needed their trailers checked for multiple non-critical repairs could make an appointment for a single day of maintenance and servicing based on when the trailer was available or not scheduled for any deliveries. To save more time and cost, a feature was added to suggest the nearest service facility based on the current location of the trailer.

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Updates, alerts and notifications are an app’s way of reminding its users that it is constantly working to serve customer needs. Our team integrated status updates and notifications onto the primary interface so that users could rest assured knowing the whereabouts of their trailers and the estimated time that would be taken to resolve any issues. Alerts about approaching lease contract expiration/renewal dates, DOT compliance check expirations, overdue service maintenance, and pending invoices were also added to the primary interface.

The status updates and alerts were designed into the application to support our client’s customer-first service approach and brand values such as trust and reliability. Additionally, the features supported the client’s offline customer service efforts by reducing actual man-hours and resource costs.

A very crucial UX feature that was missing in the app’s earlier version was one that allowed users a single point to access all expenses and costs incurred by various assets. Our team liaised with the data analytics team to pull up a comprehensive expense tracker that was visible on the dashboard.The tracker aggregated and maintained cost information about previous maintenance requests, services completed, complaints log, and other trailer-related expenses and presented a summary for the user with insights about trailer efficiency and health. This feature was particularly useful for customers to make informed decisions during lease renewals.

During the entire design process, we were parallelly creating a AAA standard design style guide to support the UI of the revamped application. From selecting the color palette that aligned with the brand’s identity to standardizing button sizes and shapes, we provided a complete and exhaustive style guide that was deep enough to accommodate any feature additions or service integrations in the future. A dark and light theme version was offered to improve scope for customization. The perfect typography and hierarchy to be used across the numerous content spaces within the application were selected based on ease of use and visual aesthetics. The entire work was in compliance with the Google Material Design System and followed Apple and Android guidelines. With attention to detail and an intuitive design direction, we created a roadmap for the application design use and implemented it in our prototypes. The result was a minimalistically designed, clutter-free navigational experience for the users.

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After numerous iterations, we developed a prototype based on the final wireframe and implemented usability testing. The feedback we received confirmed two very important things:

By eliminating rhetorical permission requests and repetitive user information validation, we 

increased the efficiency of the application by at least 50%

. The resulting fleet dashboard with real-time updates on trailers, routes, service requests, and compliance checks gave our client and their customers access to all time-critical information in one place, thereby increasing their internal productivity and customer satisfaction. As noted earlier, we also provided a style guide that complemented the client’s corporate persona. All in all, we offered a complete UX makeover for our client’s application that directly helped in improving operational efficiency.

We revamped our logistics client’s application with a focus on improved accessibility to time-critical features and heuristics for more efficient decision-making. By prioritizing user experience, we delivered a solution that simplified navigation, improved design consistency, and enhanced efficiency.

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Reduction in user navigation time across the app

Service-Oriented UX Revamp for Logistics Efficiency

LOGISTICS

An innovative platform to retrieve data directly from various IoT touchpoints and convert them into easily configurable user-specific dashboards.

With the plethora of information source points that IoT ecosystems have brought to the table, our team devised a data analytics solution that could gather all the information in one place and present real-time data using visual dashboards that can be configured according to industry specifications and preferred matrices. While data analytics services are available in plenty, an easily customizable solution that offered better connectivity to an IoT ecosystem is hard to come by for certain industries.

There was a need to integrate the IoT ecosystem more effectively to business processes by converting data points into industry-specific analyses. Data analysis platforms that were currently being used along with IoT also required to be updated when a new evaluation standard or process was added to the system, which was often time-consuming and fairly complex from the business/client perspective.

We designed and implemented an AI-enabled data analytics platform that offered better connectivity to the IoT ecosystem and let businesses configure their dashboards easily according to their requirements using stream and batch analytics solutions. The plug-and-play feature also enabled faster implementation of revisions or changes to analytical parameters.

Our solution has helped clients from various industries linked to the IoT ecosystem to quickly retrieve important data from all connected devices and draw decision-worthy conclusions in a speedy way. This leads to faster and efficient business processes and improved problem-solving capabilities.

The platform has the ability to fetch data directly from the data source and offer real-time analytical insights to businesses including data anomaly detection.

: Our solution accesses data at the management layer where information is received from IoT networks, channels and devices. From here the relevant data is then pushed to the application layer where businesses or users can quickly configure dashboards/KPIs/Reports based on their specific industry requirements.

: Many a time, clients end up spending too much time sifting through data analytics solutions that might be either too complex or irrelevant for their industry. Our platform offers them a simple data analysis solution where they can set custom conditions and criteria to configure actions and alerts.

: We have simplified the whole information processing flow leading up to consumable data analysis and reports and enabled clients to access real-time analytics reports. This data is presented in a visually cognitive dashboard that gives a comprehensive view in just a few glances. And since the dashboard is customizable to user requirements, our platform has helped businesses tied to IoT ecosystems improve their overall operational efficiency.

: The feature to plug-in predictive analytics modules enables clients to react proactively to even the slightest market changes and adapt their processes more efficiently to changing requirements.

The AI-enabled platform connects effortlessly with IoT ecosystems, providing customizable dashboards and real-time analytics for quick, data-driven findings.
 

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Custom Analytics Platform Using IoT Data Sources

We developed a platform that used data analytics to identify suspicious claims and reduce wrong claims.

With over 50 years of experience providing health insurance options to commercial businesses, individuals, and Medicare/Medicaid patients, our client was looking to update their platform and digitize their processes in order to increase efficiency, reduce computational errors, and identify fraud.

As a major player in the health insurance industry, our client was following business processes, practices and government regulations that had been in place for decades, thus resulting in more operational and resource costs. Additionally, their processes failed to capture misinformation or fraud thus resulting in losses through wrong insurance claims.

The Expeed team analyzed the problem areas and came up with multiple analytical solutions using Data Science, Machine Learning. We also developed a Web and Mobile application that allowed the new features to capture data and present them for evaluation in a much easier way.

The client started saving thousands of dollars every month which was otherwise lost on payments to wrong claims. The process also helped in better resource utilization resulting in long term patients getting better service. Improved customer satisfaction helped boost the brand value of the company.

We developed a solution using multiple Machine Learning techniques to identify all the suspicious claims. This prevented wrong claims from happening in the first place and also reduced the cost and effort spent on recovering wrong claims each year.

 The insurance industry in general, and our client in particular, receives a number of claims from healthcare providers with wrong amounts and wrong procedure codes.

Our client’s claims processing system failed to catch these invalid claims, resulting in hundreds of millions of dollars of payments towards these invalid claims. This had been a known problem and our client spent close to 200 million dollars in efforts towards recovering only a portion of these wrong payments.

We developed a solution using multiple Machine Learning techniques to identify all the suspicious claims based on the recent amendments to the underlying contracts, comparison of the distribution of claims across procedure codes between different pay periods, and comparison of price distribution for procedure codes between different pay periods. This gave a much smaller set of all claims with potential issues and the recovery team was able to act on all of them instead of randomly picking a few of the claims from the whole set. This reduced the cost of the effort to recover and prevented wrong claims from happening after a month. It resulted in significant financial savings to our client.

 Our client’s existing system was unable to meet the SLAs that were required in order to respond to customer complaints, resulting in penalties. To overcome this problem, our client outsourced the activity of manually reviewing each of the complaints and assigning them to the appropriate department. This manual process was costing a significant amount of money and was sometimes error-prone resulting in further penalties.

Our team stepped in to resolve this problem through process automation where we used the techniques of text mining, sentiment analysis and machine learning algorithms. With this new automated system, our client was able to eliminate the cost of a 40-member outsourced team and significantly improve the chances of meeting SLAs through more accurate prediction of the department that can address the issue based on the text of the complaint.

Long Term Medicaid Services Process Optimization:

 As part of Medicaid program, our client provides long term care services to Medicaid patients. As part of the program our client employs a number of care coaches and third-party service providers to attend to the needs of Medicaid patients. But there were inefficiencies in the system of care coach assignment and need-evaluation of the patients, which was resulting in revenue loss and fraud.

Our team developed an application to recommend the assignment of care coaches to patients with the goal of minimizing the distance they travel and maximizing the time they spent with the patients, with a near-uniform distribution of workload among care coaches. This resulted in multi-million-dollar travel-related savings, better results for patients, and work-life balance to care coaches.

We also used Machine Learning techniques to better evaluate the individual needs of every patient. We took the patient’s medication history and predicted services they would benefit from. Care coaches started using those recommendations while offering services to the patients. This resulted in cost savings, happy patients, and reduced the scope for fraud that could be involved in offering services.

We collaborated with a leading insurance provider to develop an advanced data analytics platform. This platform was intended to save costs by detecting fraudulent claims and managing health insurances in an efficient and hassle-free manner.

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We collaborated with a leading insurance provider to develop an advanced data analytics platform. This platform was intended to save costs by detecting fraudulent claims and managing health insurances in an efficient and hassle free manner.

Health Insurance Claim Management and Fraud Detection Analysis

INSURANCE

We created a flexible, interactive and dynamic case management system.

Our client, who was a premier technology solution provider based in the U.S., approached us to develop a framework that could be used to assist community managers and support workers to properly attend to individual requirements of homeless youth, especially pregnant ones, from a region. They sought a platform that would not just connect case managers to their patients, but also help streamline the file management process.

The client needed an on-demand case management platform that made the existing process more efficient, allowed for care managers to connect with their patients and offer space for sharing data, building reports and monitoring progress.

We came up with a highly scalable cloud-native solution that allowed the case managers to connect screen-to-screen with their program participants and to monitor and manage their assigned cases in a more comprehensive way.

The client can now help their customers scale-up their activities across various counties in the US, with the help of the more streamlined system. The case managers have also reported better results in a shorter TAT, thanks to the screen-to-screen interaction feature.

: We proposed a cloud-native solution, leveraging the Microsoft Azure platform to embrace rapid change, large scale, and resilience as a service.

: The solution provided for browser-based video calls were implemented using WEBRTC. We built a powerful real-time video communication module, by using the built-in camera and microphone for the video calling, which also follows PCI and HIPAA standards. The other side of this framework is real-time browser notifications between the users.

: We proposed a custom case management module where the program participant could sign-up and make requests depending on their needs. The key highlight of this module is that case managers can search program participants, associate cases, track various cases, update various statuses, create appointments, and schedule meetings. All the notes, appointment history, status relevant to a case is tied to the program participant’s profile, which served as the single source for all the information.

: We developed a custom Forms Management Module, to address all their dynamic in-take form creation and publishing requirements. We built a flexible framework using Angular as frontend, which turns query the questions and control types from the form to render dynamically.

Dynamic Appointment Scheduling and Booking Module

: The solution included a custom module, which took care of appointment booking on behalf of the case manager/program participant. Based on the many appointment types, case managers could set the availability and the dynamic time slot logic would automatically suggest the next available slot to schedule an appointment in the system.

: A dynamic content creation and publishing module was developed in the system, using which case managers could create various resources, and publish it to targeted user groups. This Custom Content Publishing Module was used to make announcements, share resource information, emergency contact information pertaining to various counties etc.

: A custom-built reporting module was implemented to cater to various reporting needs. The case managers could generate and export various reports to Microsoft Excel format in the application.

: The framework had a localization component, that gave high flexibility to the application, and where the client could customize the labels and messages based on their needs.

We partnered with a US based technology solution provider to create a flexible, interactive and dynamic case management system for seamless functional management.  

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Community Care Case Management System

HEALTHCARE

We developed a comprehensive set of solutions that helped our client to scale from a regional player to a national market

As a top-rated radiology group owned by a private equity firm, our client was in the process of expanding their business through acquisitions and mergers that also helped them stay ahead of the competitive winds in the radiology industry. Although their revenue and market share were growing, so were their expenses and technical/operational costs. With the demand for radiology services at an all-time high, the client felt it was time to upheave the existing operational processes and set in its place a more efficient and digitally adaptive process. They were on the lookout for a technologically strong strategic growth partner when they approached our team at Expeed.

The client needed process improvements that would increase both employee productivity and satisfaction, which in turn would lead to improved customer experience and retention. They also needed a system that was easier to integrate disparate data sources, giving them faster access to more accurate information, improved analysis, and accelerated decision-making.

Through our Rapid Digital Transformation Assessment™, we enabled the client to identify opportunities for, and the quantified benefits of, automating manual processes and producing and integrating the systems required to deliver predictability to their organic and inorganic (M&A) growth strategy. These systems would address key technical and operational challenges, reduce operating costs, and streamline the acquisition and integration of smaller and larger companies.

With our enhanced processes in place, the client reported accurate QA numbers for the first time with overall consensus. Adherence to QA contracts rises from 30% to a near 100% mark. Moreover, the client now reports a 97% work-billing match as compared to the 70% work-billing match that existed.

Our solutions resulted in more accurate tracking and accounting for radiologists’ work units (services) and a more effortless association with external billing companies, leading to better planning and revenue prediction.

The solutions we provided the client were derived from our Rapid Digital Transformation Assessment which identified the following touch-points of opportunities/threats to the company’s existing processes.

Story-Telling Data Dashboards: We exposed the relevant data and created a unified dashboard that could translate the information into decision-making performance narratives. This helped to uncover underlying problems and allowed them to be subsequently fixed. Our efforts included exposing previously incorrect metrics that concealed existing issues, bringing the actual needs of the company to the forefront to be addressed.

Technologically Efficient Workflow: By understanding the processes of the users, team Expeed was able to redesign workflows that increased efficiencies and addressed technological gaps in their systems. We were able to reconcile internal disagreements within the company. Not only were their teams gathering and looking at incorrect numbers but were also not doing calculations correctly. We brought their stakeholders together to understand their requirements more intricately and then to design a system that agreed upon and met everyone’s needs.

With the problem areas clearly defined, our team was able to recommend a solution that would address the identified challenges, mitigate execution risk, and overdeliver on their anticipated ROI expectations.

: We exposed the relevant data and created a unified dashboard that could translate the information into decision-making performance narratives. This helped to uncover underlying problems and allowed them to be subsequently fixed. Our efforts included exposing previously incorrect metrics that concealed existing issues, bringing the actual needs of the company to the forefront to be addressed.

: By understanding the processes of the users, team Expeed was able to redesign workflows that increased efficiencies and addressed technological gaps in their systems. We were able to reconcile internal disagreements within the company. Not only were their teams gathering and looking at incorrect numbers but were also not doing calculations correctly. We brought their stakeholders together to understand their requirements more intricately and then to design a system that agreed upon and met everyone’s needs.

 Once the larger process was streamlined to work more effectively and adapt to their digital touchpoints, we delivered strategic and tactical solutions to overcome their specific operational inefficiencies. Here are a few of them:

We helped a top-rated radiology group scale from a regional player to a national leader by digitally transforming their processes to improve efficiency and reduce costs amid rapid expansion.
 

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 Process Enhancements for Digital Transformation and Scale

We developed an Automated Case Review Assignment System that enhanced Quality Assurance process efficiencies.

Our client was in dire need of an efficient system that would help them choose cases to be reviewed for QA purposes. As one of the leading radiology groups in the US, they had a huge volume of un-reviewed cases that needed a proper QA analysis – a task that was manually laboring and inefficient. Radiologists had to choose which exams to review, and the QA team would have to manually assign cases to fill in any paucity in coverage. Service level agreements with different medical groups dictated levels of coverage, in terms of modality, interpreter, and site, which became a logistical morass for the team. The system also led to an imbalance in workloads

The methodology that was being followed by the company for assigning peer reviews of cases for the QA team was not scalable. The company itself was growing with dozens of sites and thousands of exams per day.

Our team at Expeed conceived and built a rule-based system that allowed for automated selection of cases to be reviewed, thereby ensuring the sample covered all types of cases and with almost no resource hours lost in the selection process.

With our automated review assignment system in place, the client’s QA team was able to keep up with the ever-expanding growth of the parent company and allowed them to reliably deliver contracted reviews to medical providers with whom they had service level agreements.

Our client was especially happy that the intrinsic work related to each review was accounted for instead of treating every review as equal work.

: We conceived and built a rule-based system that enabled automated assignment of exam reviews. These rules could be applied at different levels. For instance, a rule could be applied as broad as an entire practice or as narrowly as an individual radiologist. Specific categories also included sites and types of employees, for instance, new hires. The categories were dynamically linked to the companies database so that as options changed, for example, a new radiologist is hired, options automatically update. In addition to a selection of radiologists to which a rule applied an amount could be indicated, in either percentage or absolute numbers.

: The set rules were then cumulatively applied to exams in a rolling window. For instance, if 2% of exams were to be reviewed, 2% of the exams for the previous 30 days would be randomly selected for review. The process was set to repeat every day and the exams previously selected would already be accounted for.

This simple concept was applied throughout the system and on all rules using hierarchical layering. This helped minimize the number of exams selected while satisfying all rules that had been created.

: Our process ensured that the exams that were selected for review were relatively recent and evenly distributed in time. The size of the window was adjustable so that stochasticity in the sample could be managed.

Resource Management: Finally, each exam was assigned to a radiologist that was credentialled to review the exam. This process included accounting for any specialities that might be applicable, i.e., MSK, Neurology, etc. Workloads were balanced among all radiologists using the Relative Value Unit (RVU) assigned to each procedure. As new exams were selected for review, it was balanced to perform across all viable peers. Thus, no member of the radiology team felt encumbered because they were assigned more complex exams to review.

The Automated Case Review Assignment System for Healthcare leverages advanced algorithms and Artificial Intelligence to streamline the case review process in healthcare settings.

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Automated Case Review Assignment System

We created a real-time natural language processing (NLP) algorithm to analyze and accurately determine medical codes in order to make our client’s medical billing process more time and cost efficient.

Medical billing is an important component of practices and is key to ensuring the smooth operation of the revenue cycle for our client. Proper medical billing codes, along with supporting information, are necessary to accurately charge health insurance providers and ensure accurate reimbursements. For example, each billing must include the code and reasons for suggesting the particular procedure with diagnostic evidence in order for the insurance provider to make a maximum claim payment.

As one of the leading radiology groups in the market, our client needed to set in place a more error-free and timely computing method for processing medical bills to relevant insurance companies. In order to optimize claims, the existent process required each medical code to be validated and supported by information provided by the physicians about each case. With over 300,000 dictations to be processed each month, this was time-consuming and was prone to manual errors of omissions or misinterpretations.

Data submitted by physicians were often insufficient to narrow down the exact medical code. Hence, there was a lot of time spent on submitting Requests for Information (RFI) and validation. Improper assignment of codes also led to reduced claims, leading to an increase in the overall cost for the company.

We built an NLP algorithm that identified key information required by medical coders relevant to the procedures described in the reports. Automated prompts were set up to retrieve missing information from the concerned physician.

Our billing solution was able to quickly learn the various parameters that defined the complete billing information required and could assess and categorize over 30,000 dictations as “complete” or “incomplete with physician’s input needed” in fewer than 10 minutes.

Proper medical billing codes, along with supporting information, are necessary to accurately charge health insurance providers and ensure accurate reimbursements.

: While ensuring the protection of PHI and HIPAA compliance, our Director of Data Science lead the team that built a real-time NLP algorithm to ingest and analyze dictated reports. This analysis identified key information required by medical coders relevant to the procedures described. If key details were omitted, based on for instance the exam modality (i.e., X-ray, MRI), the physician was prompted to add specific details before sending off the report.

We developed an advanced natural language processing (NLP) solution to lower medical costs and improve accuracy for a leading radiology team.

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Natural Language Processing Model for Accurate Medical Billing Coding System

We helped our client transform digitally by creating a uniquely designed Shopify website with POS integration that allowed them to expand their reach while streamlining their online and brick-and-mortar operations.

Our client, a for-profit subsidiary of World Bicycle Relief, was looking for a transformative solution that allowed it to be more accessible to communities across the world while streamlining its operations in brick-and-mortar locations. Driven by the need to expand their reach and optimize their processes, the company reached out to us for an e-commerce solution based on Shopify.

Having relied primarily on brick-and-mortar stores for sales, the client felt restricted and particularly challenged when they wanted to expand their mission globally. They realized that establishing an online store was the only way to overcome this. However, while doing so, the client wanted to make sure that the online platform was designed uniquely to communicate their core mission and values and not appear too sales-y. Moreover, it had to offer a comprehensive solution for streamlining and centralizing purchase and inventory data management.

Our team at Expeed implemented a two-part solution to meet the client’s requirements:

Our solutions have introduced a new level of efficiency into the company’s daily operations, especially when it comes to inventory management. The real-time data synchronization between their stores and the online platform enables them to make informed decisions regarding stock levels and purchasing strategies. The platform also offers enhanced accessibility and improved user-friendliness. The design revamp allows visitors to navigate and engage with ease, promising improved customer retention and higher conversion rates.

Understanding the Required Features and Functionalities:

Just as with any other project, we began by analyzing the client’s existing website and understanding the features and functionalities or the lack of it. We also worked closely with their larger team to understand their internal processes and how well-placed they were for a digital shift. This helped us understand their expectations better and also gave us insights into their ideal customer behaviors.

Some of the important takeaways from our research were:

Since the client had specifically requested to use Shopify for the new website, our team’s next activity was theme identification. Here our UX team stepped in to recommend the best Shopify themes available that could be customized freely and that also matched the company’s branding styles. The chosen theme provided a framework for the project’s design and development teams to work cohesively, ensuring a unified and visually appealing final product.

This phase involved the actual implementation of the website’s custom features and functionalities. While the Shopify theme already supported most of the basic shopping features like product catalogs, carts, checkouts, etc, our team customized these features to improve the functionality, accessibility, speed, and security of the website. For instance, we added additional layers of security while integrating the payment gateways and payment methods to ensure the highest compliance standards.

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Another pivotal component of this project was the enabling of a Point of Sale (POS) channel in Shopify for mobile and tablet devices. This integration allowed the brick-and-mortar store managers to track and manage their inventory better with improved product categorization, warehouse-specific product data access, and real-time stock updates. The app pulled inventory and sales data from all the physical and virtual stores, unifying their sales data channels, easily accessible by the company’s backend offices.

The integration of the online platform with the client’s Sage Evolution ERP was the next critical step. To achieve this our team leveraged the adapter integration service that facilitated the recording of all Shopify transactions into the client’s ERP system, ensuring accuracy and efficiency in financial data management. Real-time data synchronization between the two systems streamlined the flow of information, reducing manual data entry and minimizing errors.

While our development team worked on perfecting a customized technology that would help the client streamline their global operations and centralize data collection, our UX team was developing a whole new brand shopping experience for the site visitors and B2B stakeholders. This included in-depth research and analysis of ideal user journeys, defining user personas, developing design guidelines, and creating a roadmap to increase app and site user retention.

Here’s a snapshot of some of the notable UX improvements that the team brought to life:

We have built a customized Shopify eCommerce platform with POS integration, enabling seamless online and offline collaboration for the global bicycle retailer while reflecting its mission-driven brand identity.

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Shopify Website with POS Integration for Bicycle Retailer

E-COMMERCE

We offered a versatile payment gateway integration solution designed for subscription businesses.

Our team at Expeed recently implemented a transformative payment integration project with saaslogic, a subscription management platform, and billing automation software. Keeping in mind, the demands of a rapidly growing subscription economy and booming SaaS businesses, we put together a robust integration solution with multiple payment gateways and payment methods that offered businesses the flexibility to sell products and services through subscription models.

saaslogic needed seamless integration of multiple payment gateways so that it could serve a broad spectrum of B2B and B2C businesses. Our team made sure that the integrated payment solutions allowed saaslogic merchants to sell their products all across the US as well as internationally. This also meant handling varying transaction charges across different payment methods, card types, and regions while keeping transaction costs reasonable for both saaslogic merchants and their customers. 

From providing connected account solutions for pre-existing Stripe account merchants to offering saaslogicpay accounts with some of the lowest transaction charges to new merchants, our team carried out multiple payment integrations that allowed flexibility, ease of access, and scalability to subscription businesses.

: Integration with all the major payment gateways and methods were the first and the most important task we took up for saaslogic. Stripe being a popular payment gateway in the US, a basic Stripe integration was the primary ask for the platform. Our team set it up so that merchants could seamlessly link their existing Stripe accounts for processing payments from customers. Alternatively, we also created provisions to create new Stripe accounts exclusively for saaslogic. All payments initiated through the saaslogic platform were channeled through this dedicated Stripe account, ensuring efficiency and ease of use. Our team also integrated Authorize.net as an alternative payment gateway for the platform.

: Since saaslogic had already established markets in India and Africa, the platform needed to have other payment gateways integrated apart from Stripe and Authorize.net. For instance, we chose to integrate the platform with Razorpay for its Indian customers. This provided a location-specific payment gateway based on the business addresses. Configurations were set up to enable the platform to auto-select the payment gateway to be used based on the nearest selling address of the merchant (or process with default address in case of other locations). This allowed the end customer access to all the payment methods offered by the selected payment gateway. 

It also allowed merchants to scale their businesses globally without having to deal with the complexities involved in setting up payment collection methods specific to different regions around the world. Similar configurations were made on mPesa integration for saaslogic’s African merchants.

: For merchants who had no prior payment gateway accounts, we set up provisions to offer a saaslogicpay account – a built-in payment gateway solution by saaslogic. This way, not only did the merchants benefit from some of the lowest transaction fees, but they were also able to provide their users with a continued user experience and transaction efficiency.

Surcharge Flexibility and Different Transaction Fees

: One of the key features of saaslogic as a payment platform was the ability to offer surcharge flexibility. The team set up configurations that allowed merchants to easily pass the entire transaction fee directly to the customer or share a percentage of that cost. This included the ability to add surcharges, either as fixed amounts or as a percentage of the transaction. This is an especially important feature for merchants who want to allow multiple invoice settlements in single transactions. 

Another key integration challenge was enabling merchants to choose the transaction fees for different payment methods. For example, businesses often have to pay different charges for transactions conducted via ACH bank transfers, debit cards, corporate cards, personal credit cards, etc. Our development team made sure that saaslogic customers were able to easily select the transaction charges that applied to their businesses in different regions based on the payment method selected.

Multiple Payment Gateways for Diverse Operations

: Another use case we had to keep in mind while working on the payment integrations was businesses maintaining separate accounting books for different service lines or locations. In such cases, we created provisions to allow multiple payment gateway integrations for the same merchant but with different bank accounts. This feature enables businesses to keep their books clean and easy to track.

Payment Options for Recurring Customers & Data Compliance

: One of the most common challenges associated with payment data collection and processing is being compliant with PCI DSS. With saaslogic, we took all precautions to ensure that it complied with these regulations, irrespective of the payment methods.

With data compliance rules and regulations constantly changing across the globe, saaslogic also needed to offer compliant solutions to its recurring customers who preferred not to store card or bank details and desired diverse payment methods for each transaction. Along with disabling auto-pay options, we made sure that merchants could extend multiple payment methods every time an invoice was generated against a subscription and payment reminder emails were sent to the customer. 

We developed a robust payment integration system for Saaslogic, enabling seamless multi-gateway support and advanced payment flexibility tailored for subscription-based businesses.

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Payment Integration Solution for saaslogic

We designed an NLP model that could quickly identify and assign treatments to patients based on the seriousness of their medical conditions.

As one of the leading healthcare solutions and treatment providers in the country, our client and their employed doctors and care administrators were finding themselves time-stricken to evaluate the ever-increasing number of patient files in order to assign treatment based on urgency. All the extra resource hours being spent on the review of patient files was adding to the lack of healthcare support staff which was becoming a growing problem in light of the COVID-19 situation.

The client was facing issues with its healthcare staff being overworked and unable to adequately focus attention on patients in urgent need of care. There needed to be a system that would help identify critical care patients and assign them immediate attention.

Our team employed natural language processing techniques on a sample of ~5,000 medical dictations to build a classification model, determining how urgently a patient needed treatment.

The artificial intelligence solution we created advised the healthcare practitioners and helped them to identify urgent care requirements, with over 95% accuracy. The model ensured that the client’s healthcare staff was not over-burdened with the task of identifying the most critical patient case files.

The model performs with greater than 90% accuracy, automatically identifying urgent cases in the vast majority of instances and augmenting our client’s ability to rapidly and accurately perform triage.

 We used Azure Machine Learning services to quickly train the model using a sample size of over 5,000 medical dictations. Through this exercise that was monitored closely for 100% accuracy in diagnosis, our model was able to scale quickly and expand effectively to review and identify critical cases on a much broader sample in a very short period of time. In order to reduce risks and situations where patient cases get identified wrongly as non-critical, the model was trained to be very conservative while drawing conclusions.

The model also allowed for quick deployment into a production environment.

 The fully developed model now works with greater than 95% accuracy and uses our Artificial Intelligence solution to advise healthcare practitioners about the urgency associated with each case. Our solution has eliminated the need for additional time being spent by the already overburdened healthcare staff.

The NLP-based model improves healthcare efficiency, underlining and prioritizing urgent cases among patients with over 90% accuracy. Powered by Azure Machine Learning, this system analyzes medical dictations to make automatic treatment appointments.

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The NLP-based model improves healthcare efficiency, underlining and prioritizing urgent cases among patients with over 95% accuracy. Powered by Azure Machine Learning, this system analyzes medical dictations to make automatic treatment appointments'

NLP-Based Treatment Urgency Identifier

AI-BASED APPLICATION

Our client’s existing system was unable to meet the SLAs that were required in order to respond to customer complaints, resulting in penalties. To overcome this problem, our client outsourced the activity of manually reviewing each of the complaints and assigning them to the appropriate department. This manual process was costing a significant amount of money and was sometimes error-prone resulting in further penalties.

Long Term Medicaid Services Process Optimization: 

As part of Medicaid program, our client provides long term care services to Medicaid patients. As part of the program our client employs a number of care coaches and third-party service providers to attend to the needs of Medicaid patients. But there were inefficiencies in the system of care coach assignment and need-evaluation of the patients, which was resulting in revenue loss and fraud.

The system uses advanced data analytics and machine learning to prevent fraudulent insurance claims. The system automates complaint responses and data analysis of claims, minimizing computational errors and enhancing efficiency to reduce operational costs. 

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Fraud Detection and Claims Optimization System

This project addresses the overwhelming requirement for automation in the key fields of the recruitment process by developing AI agents to handle various tasks. This intelligent tool efficiently manages the entire job recruitment process, which previously required the HR team's direct involvement. 

The ultimate objective of the project was to develop specialized AI agents to handle various steps involved in candidate recruitment, thereby making the entire process flawless and easier. 

Upload resumes to the software to avoid the hassles of managing them manually. 

 We use a powerful AI agent to evaluate resumes and extract candidate information to accelerate candidate matching. 

Expeed’s AI-driven recruitment platform revolutionizes hiring processes by automating tasks such as resume screening, candidate scoring, and interview evaluation. Built on CrewAI’s agent-based framework, the tool simplifies recruitment workflows, ensuring scalability, precision, and efficiency.

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Health Insurance Claim Management and Fraud Detection Analysis