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Why Us

Data is moving way too fast

By the year 2025, there will be 175 zettabytes of data accessible, which is triple what we analyze today.

How was this problem trying to get solved before?

Extracting relevant and accurate insights by examining and analyzing diverse data sources has become more challenging. Current tools to leverage data insights are expensive, inefficient, insecure, unreliable, and require manual intervention.

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Understanding internal and external data is time-consuming.

Analyzing company data takes about 4-5 hours, and staying up to date with relevant trends takes about 6-7 hours. Teams does not have enough time to fully analyze both company and external data at the necessary times. 

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Pinpointing quality external data is difficult.

The difficulty in collecting high-quality data is one of the major obstacles for big data analysis. Unstructured information does not lend itself easily to being transformed into structured types and then processed further, so it takes much longer than other forms would take when processing this type or format .

Creating strategic plans from data is time-consuming.

Maya’s ability to read and analyze external data is a huge advantage for the company because it allows them to access insights from both sides – workers’ perspectives as well as that of the overall business goals.

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If we continue with this current process

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Inaccurate planning

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Missed Opportunities

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Unknown Data Placement

You have to meet Maya AI

A generative AI robot that provides actionable insights from internal and new data in real time.

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Easy integrations –
Easy communication

Maya AI offers easy integration and communication capabilities, allowing businesses to seamlessly incorporate the technology into their existing systems and communicate insights to relevant stakeholders.
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Correlate new and historical data to create predictions and recommendations.

By analyzing large amounts of data from various sources, Maya is able to identify patterns and trends that can be used to provide recommendations for businesses to optimize their operations and decision-making processes.

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Actionable insights on what/ where to implement the strategies

Maya AI provides businesses with actionable insights and recommendations on where and how to implement effective strategies based on its analysis of data patterns and trends.

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With Maya AI we are replacing these tools and tasks

Support tickets like Jira for data requests

Data Transformation

ETL jobs for Ad Hoc requests

BI Tools

It costs over $3M to have a small data science team, it cost less than $250K with Maya to do the same job, and more.

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Use Cases

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Maya is revolutionizing healthcare by improving patient outcomes, reducing costs, and associating appropriate treatments towards patients.

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Transforming the pharma industry by accelerating drug discovery, improving clinical trials, and optimizing manufacturing processes.

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Reshaping the retail industry by improving customer experiences, increasing operational efficiency, and enabling recommendations.

How does Maya do it?

Stay ahead of the market while it’s happening

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Use Cases

Meet Maya AI Healthcare Asset Learning

Asset Learning

Read and identify answers from various medical assets to understand specific details.

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Sentiment Analysis

Analyze patient feedback, social data, and other sources to understand patient attitudes and experiences.

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Policy Changes

Data-driven insights on how policy changes could impact healthcare operations and patient care.

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Conditional Correlation

Identifying complex relationships and patterns in patient data, enabling more accurate diagnosis and treatment recommendations.

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Patient Trends

Understand what type of trends could affect patient care and how you can use them.

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Locational Analysis

Analyzing patient data, hospital locations, and geographic information to identify areas of care and reasoning.

Use Cases

Maya AI for Pharma Drug Discovery

Drug Discovery

Identify patterns and relationships between various factors, such as drug efficacy and patient profiles, to support the development of more effective and personalized treatments.

Maya AI Symptoms Analysis for Pharmaceutical Companies

Symptoms Analysis

Analyze vast amounts of medical data and identify patterns and relationships between symptoms and specific drugs, leading to improved patient outcomes through personalized treatment and care plans.

Maya AI Drug Repurposing

Drug Repurposing

Analyze vast amounts of medical data, identifying new uses for existing drugs and optimizing their efficacy for specific patient needs.

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Locational Analysis

Maya can support location-based symptom analysis by using advanced machine learning algorithms to identify patterns and correlations between specific symptoms and geographic regions.

Maya AI for Pharma Policy Changes/ Regulation

Policy Changes/ Regulation

Providing insights on the impact and consequences of proposed changes, aiding in informed decision-making for stakeholders.

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Drug Distribution

Analyzing data such as market trends, supply chain logistics, and consumer behavior, using machine learning algorithms to identify opportunities for improving efficiency and reducing waste.

Use Cases

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Market Trends

Understand what trends could affect your business and how you can use them.

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Price Optimization

Analyze how customers will respond to different prices for your products/ services through various elements.

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Policy Changes

Find out how policy changes could impact your business and what you need to do to prepare.

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Brand Reputation Analysis

Analyze how your company is being rated through, social media, publications, reviews, etc.

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Competitive Market Analysis

You need to look at your competitors and see how they are affecting the market.

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User Sentiment Analysis

Understanding what customers are thinking, feeling, and how they are reacting to the company’s products and services.