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Assistance in marketing and sales content

Customer support chatbot

Image generator for Advertising

Sales support and Insights

Extraction of HIPAA identifiers from documents

Retail

AI-Powered Campaign Content Generation for a Fashion Brand

We collaborated with a fashion brand to develop an application capable of generating campaign emails and Instagram content based on specific inputs such as pictures and prompts. By harnessing the potent computer vision technologies of the Florence project, we could draw out descriptions and color profiles from the provided images, aiding us in crafting captivating campaign narratives. Moreover, we tapped into the potential of OpenAI chat models and the DALL-E service to recommend suitable images enhanced with AI-generated artistic backgrounds in several variations. This comprehensive process led to the production of impactful and visually delightful campaign emails tailored for the fashion brand.

Retail

Elevating Fashion Campaigns through AI-Driven Creativity

60%

Efficiency Boost:

60% reduction in time spent on campaign content creation.

$1.5 M

Cost Savings:

Annual savings of $1.5 million.

20%

Personalized Visuals:

20% increase in engagement metrics with AI-generated artistic backgrounds tailored to campaigns.

15%

Customer Satisfaction:

15% increase in customer satisfaction ratings.

Annual Revenue:

$6.2 billion

Market Capital:

~ $9.8 billion

No. of Employees:

~ 24,000

Retail

This project has the potential to revolutionize the fashion brand’s campaign content generation by leveraging AI technologies. The application’s capabilities in extracting image descriptions, color profiles, and generating personalized visuals have resulted in impactful campaign narratives and visually appealing content.

Completed and implemented.

Finance

AI Chatbot for Customer Support : Transforming Financial Inquiry Handling with Azure and OpenAI

Learn how we are working with a leading financial organization to streamline its client support process, delivering precise and timely information while minimizing manual effort with an unmatched support experience from an AI chatbot. By leveraging Azure and OpenAI, we are able to analyze dynamically scraped content from various client sources, extracting valuable insights that revolutionize the way financial inquiries are addressed.

Finance

Transforming Financial Planning with Intelligent Insights

4000+

No. of webpages scraped:

A significant amount of data will be collected from the client’s website through web scraping. This process will involve scraping over 4000 webpages from various sources on the website, including FAQs and articles.

6 weeks

Deployment Timeline:

Includes performing various tasks such as data pre-processing and cleaning, efficient data indexing, development of a model for answering financial questions, creation of a user-friendly prompt-based interface, optimization for accurate responses and user testing.

Rapid response:

The model ensures quick responses within minutes, eliminating the need for clients to spend excessive time searching for documents. It streamlines the process, enabling efficient access to relevant information.

Annual Revenue:

$5M

No. of Employees:

Finance

The project revolutionizes financial planning by leveraging advanced AI technology. It streamlines information delivery, empowering clients with accurate answers to financial questions and prompt-based interactions. This positions the company at the forefront of AI adoption, delivering efficient, personalized services, and staying competitive in the financial industry. Additionally, by analyzing dynamically scraped content from various client sources, the project extracts valuable insights that revolutionize the way financial inquiries are addressed. This real-time intelligence empowers the company to provide personalized and efficient support, enabling clients to make informed decisions and achieve impactful outcomes.

Project in progress as of May 2023*

Automotive

AI-Powered Personalized Ad Generator for Automotive Company

Our project entails the development of an ad generator specifically tailored for an automotive company, leveraging computer vision capabilities from the Microsoft Florence computer vision project and OpenAI chat models. By utilizing Florence to fetch image descriptions and incorporating the power of OpenAI chat models, we have created an innovative solution that automates the generation of personalized advertisements. This technology enhances efficiency, enabling the automotive company to deliver highly engaging customer experiences in the automotive industry.

Automotive

Revolutionizing Automotive Advertising Through AI-Driven Personalization

50%

Efficiency Boost:

50% reduction in ad creation time and $2.5M annual cost savings.

30%

Increased Engagement:

30% higher click-through rates and conversion rates.

20%

Enhanced Relevance:

20% improvement in ad relevance scores and 15% increase in customer satisfaction ratings.

50%

Social Media Reach:

50% increase in social media impressions and 40% rise in social media engagement.

Annual Revenue

$122.5 B

Market Capitalization:

$85.5 B

No. of Employees:

~155,000

Insurance

Streamlining Client Support: Azure and OpenAI Transforming the Insurance Industry

Discover how we partnered with a prominent insurance company to enhance its client support process through an innovative app. Leveraging Azure OpenAI Service and Azure Cognitive Search, we created a comprehensive knowledge base by indexing the company’s data. By combining this knowledge base with OpenAI’s advanced language model, we empowered users to ask questions and receive accurate answers in real-time. This streamlined approach revolutionizes customer query handling, empowering informed decisions and remarkable outcomes, setting a new standard in client assistance.

Insurance

Cutting-edge solutions that set a new standard in client assistance

20,000

No. of company documents:

The project involved indexing a substantial number of company documents, totaling 20,000. This includes a wide variety of documents, such as policies, procedures, product manuals, and customer support articles.

1 minute

Time to find answers:

The model guarantees prompt responses within minutes, eliminating the necessity for clients to invest hours in document searches. By streamlining the process, it enables efficient access to relevant information, saving valuable time.

Improved operational efficiency:

The project’s focus on enhancing the client support process through automation and real-time information access has resulted in improved operational efficiency. By reducing manual efforts and providing quick responses, the insurance company can handle a larger volume of client inquiries with the same or fewer resources, driving cost savings and improving overall operational efficiency.

Annual Revenue

$3.3B

No. of Employees

3,500

Insurance

The impact of this streamlined approach is remarkable, empowering clients to make informed decisions and achieve exceptional outcomes. With our solution in place, the time previously spent on manual document searches has been significantly reduced, resulting in quick responses and saving hours of valuable time for both clients and support teams. This project sets a new standard in client assistance, redefining the way queries are handled and elevating the overall customer experience.

Project in progress as of April 2023*

Healthcare

Automate HIPAA Identifier extraction to optimize patient lookup for a medical equipment company.

Learn how Data Science Dojo is helping a leading medical equipment company in enhancing their document processing and patient lookup by automating the extraction of HIPAA Identifiers from the referral documents.

Healthcare

Revolutionizing Patient Data Processing with Automated HIPAA Identification

200000+

No. of document:

The project involved automating the extraction of HIPAA identifiers from a dataset of around 200,000 referral documents.

500+

No. of different formats observed:

The document set provided by the client had 500+ different formats with no proper labeling. We started by meticulously reviewing and categorizing the documents to build a document corpus with representative documents.

90%

Accuracy on referral documents:

90% accuracy on referral documents On a representative test set of 929 referral documents, the system was able to extract the desired fields accurately around 90% of the time.

75%

Accuracy on other documents:

The system’s performance was not limited to referral documents alone. It also demonstrated good accuracy on 425 other documents, which were entirely new. The system was able to achieve an overall accuracy of 75% on this new and unseen data, indicating its ability to generalize well.

Annual Revenue:

$2.97B+

Market Capital:

$1.64B+

Home deliveries each day:

36,000

Locations:

746 in 47 states

Insurance contracts:

2,686

Lives changed last year:

3.9 M

Employees

11000+

Healthcare

The client manually processes over 100,000 requests to extract patient information and enter it into the system before engaging the consulting team. By creating an automated HIPAA identifier extraction system, the team helped the client in improving efficiency and reducing errors caused by manual processing. The automated extraction system has reduced the processing time significantly and improved the patient’s look up in the system by providing a combined accuracy of 90% on desired fields. Overall, our achievement of automating extraction of HIPAA identifiers from documents is a remarkable feat that will significantly enhance client’s operations.

Completed and implemented.