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Learn how we have helped organizations go from reactive to proactive

Recent Projects

AI Transformation

A leading private equity firm, recognizing the untapped potential within their portfolio's jewelry store chain, partnered with Le Marais Advisory to drive a comprehensive AI transformation. The initiative aimed to enhance customer experience, optimize inventory management, and boost sales. Utilizing advanced AI and machine learning models, the project implemented personalized recommendation systems that tailored product suggestions based on customer preferences and purchase history.

AI Strategy

A prominent software education company sought to revolutionize their learning platform by integrating conversational AI (Convo AI) and generative AI (Gen AI) technologies. Partnering with Le Marais Advisory, the company embarked on an AI strategy to enhance student engagement, personalize learning experiences, and streamline knowledge sharing.

Predictive analytics COE

A major public sector organization partnered with Le Marais Advisory to establish a Center of Excellence (CoE) for predictive analytics, aiming to enhance decision-making processes and improve service delivery. The CoE implemented advanced predictive analytics models to analyze vast amounts of data, identifying patterns and trends that informed strategic initiatives.

Contact center modernization

We developed a state-of-the-art contact center solution that leverages AI to enhance customer service efficiency and satisfaction. By integrating advanced speech recognition and natural language processing technologies, we enabled the system to understand and respond to customer queries with higher accuracy and speed.

Fraud, Waste & Abuse

Implemented a comprehensive fraud detection system for our public sector client aimed at identifying and mitigating instances of fraud, waste, and abuse. Utilizing machine learning algorithms, the system analyzes patterns and anomalies in claims data to flag potentially fraudulent transactions.

Generative AI Intent Tagging

Generative AI is revolutionizing the way businesses handle customer interactions by automating the tagging of call intents with high precision. By deploying this technology, companies can analyze audio from customer service calls in real-time, using natural language processing to detect and categorize caller intent. This allows for immediate and accurate response strategies, routing calls to the appropriate departments, and providing personalized customer service.

Churn and LTV Models

For a casino's marketing department, implementing a predictive model to calculate customer lifetime value (LTV) and predict churn proved transformative. Utilizing advanced analytics, we developed a robust model that integrates historical data on customer behavior, gaming preferences, and transaction histories to accurately forecast LTV. This model allows the casino to identify high-value customers and tailor personalized marketing strategies to enhance retention.

Generative AI Knowledge Search

For a software education company looking to enhance its resource accessibility and learning efficiency, implementing a Generative AI (GenAI) for knowledge search can be a game-changer. This AI-driven tool is designed to streamline the way students and educators access and utilize educational content. By integrating GenAI with the company's existing database of tutorials, documentation, and learning modules, the system can understand and process natural language queries from users, providing precise and contextually relevant information in real-time.

ML and AI Strategy

A regional insurance company leveraged AI and ML to revolutionize its operations, enhancing efficiency and customer satisfaction across the board. By implementing AI-driven predictive analytics, the company improved its risk assessment models, enabling more accurate premium settings and loss predictions. Machine learning algorithms were utilized to automate claims processing, dramatically reducing processing times and minimizing human error.

Email automation

We partnered with a leading educational service provider tasked with managing a high volume of service requests from universities. The client faced challenges in responding promptly and appropriately to diverse inquiries, which ranged from program details to partnership opportunities. To address this, we designed and implemented an AI-powered email automation system that not only categorized incoming requests based on their content and urgency but also tailored responses to fit the specific needs of each university.

Neural Network to predict health outcomes

Convolutional Neural Networks (CNNs) are being effectively employed to predict osteoarthritis by analyzing data collected from gyroscopes, accelerometers, and magnetometers embedded in wearable devices. These sensors track and record the subtle movements and orientations of the body that might indicate early signs of joint stress and degradation. By feeding this multidimensional sensor data into CNNs, the algorithms can identify intricate patterns and deviations from normal biomechanics that typically precede the onset of osteoarthritis.

Markov Models

In a project designed to optimize the management of student loans, we employed Markov models to predict borrower repayment behaviors and assess the risk of default. By categorizing borrowers based on their repayment history and demographic data, we developed a state transition model that could predict the likelihood of moving from one repayment state to another (such as on-time payments, delinquency, or default).

ML, AI, Visualization and RPA Center of Excellence

Predictive Analytics Center of Excellence

We advised our public sector client on establishing a Shared Services Center of Excellence (CoE) to centralize and optimize its operations, harnessing the capabilities of ML, AI, Visualization, and RPA technologies. This CoE is designed to streamline administrative processes, enhance decision-making, and improve service delivery across various government functions. This integrated approach not only increases operational efficiency but also significantly boosts the quality of public services, demonstrating a forward-thinking application of technology in government.

Featured Client Success Story

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Strategy | Gen AI | Conversational AI | Email Automation

Transforming a worldwide organization with a modernized contact center.

LMA designed a modern contact center leveraging Self Service, Conversational AI, Email Automation and Generative AI for our education software client. Our client was a global company had over 10 million+ contacts a year and annual run rate of over $185m. The team also created 3 proof of values for the client leveraging Generative AI for contact intent, email automation in SalesForce, and Conversational AI.


in run rate savings.

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AI Center of Execellence

Building a AI Center of Excellence for our Public Sector Health Partner

An AI Center of Excellence (CoE) designed for a healthcare client, particularly one associated with military medical services, focuses on ensuring the readiness and effectiveness of their staff through advanced AI integration. This CoE acts as a central hub for innovation, best practices, and expertise in artificial intelligence, aiming to harness AI's potential to improve healthcare delivery and outcomes.


increase in efficiency

Get started quickly with an AI strategy briefing, Discover where AI can make the biggest impact and how LMA can elevate your AI investments.


Your partner for all things AWS

Reducing time to value with built-in SageMaker features.

Create, Store and Share Features

The machine learning development process often begins with extracting data signals, also known as features. Feature stores serve as the single source of truth to store, retrieve, remove, track, share, discover, and control access to features.

While creating models for both LTV and Churn, our team develop a feature store to reducing repetitive data processing and curation work required to convert raw data into features for training an ML algorithm.

Where we've made an impact


Using Gen AI to tag the intent of uncategorized call and email contacts.

The process began by parsing email and phone contacts text, splitting them into chunks containing several lines of text, transforming the chunks into embeddings, then finally storing those embeddings in the vector store. Then we used an LLAMA2 to summarize the chunk where we believed the intent lived and then applied Gen AI for the intent.

Real business challenges

Take the next step

Get started quickly with an AI strategy briefing, Discover where generative AI can make the biggest impact and how LMA can elevate your AI investments.

Unlock AI’s full potential with a strategy session

Attend an AI strategy session to take the first step towards unlocking the full potential of generative AI at scale. Collaborating with our experts, you’ll learn:


  • How to adopt and scale AI safely yet efficiently across your enterprise 

  • How organizations like yours are gaining business value from generative AI in a priority use case

  • How to progress quickly from strategy to pilot to scale

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