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Name: TXI Digital
Price range: $

Unique insights. Stronger predictions. Better decisions.

For today's businesses, the ability to collect, analyze, and interpret data is not optional.

TXI builds digital products that propel data-driven organizations to the top of their industries.

With a finger on the pulse of data and analytics, organizations can tell powerful stories, ask better questions, and obtain faster, clearer insights to create products and services that customers need and love. That's where we come in. Our experienced consultants work closely with our clients and data teams to create custom software solutions that translate raw data into meaningful business intelligence.

By leveraging cutting-edge technology (including machine learning and artificial intelligence), we help our clients make faster and better decisions that improve their business performance.

Data strategy
Infrastructure & platforms
Data engineering
Analysis & visualization
Analyze case studies
FAQs

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Data strategy

Data Strategy isn’t just about choosing the right data warehouse or data lake; done right, data strategy starts with deeply understanding the questions and use cases that the data product intends to address. That understanding starts with users and consumers of data.

At TXI, we apply design thinking, lean product development, and human-centered design principles to our data product development process. By doing so, we’re able to create innovative solutions that not only meet our clients' business needs but also provide an exceptional user experience.

By starting with “why” and discovering user needs and desires, we can create data products that deliver real value to our clients and their customers.

5 barriers to healthcare innovation

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Infrastructure & platforms

TXI brings engineering expertise to build cutting-edge data infrastructure and platforms. We work closely with our clients and partners who specialize in data science and analytics to develop custom solutions that meet the needs of users and customers. We leverage the latest tools and technologies to design and develop platforms that are scalable, secure, and optimized for performance.

Our data platforms are designed to provide faster and clearer insights to our clients. To do that, we make sure they integrate seamlessly with machine learning algorithms, AI tools, and data analytics and visualization software. Graph databases like Neo4j let us manage and analyze complex data structures in a highly scalable and efficient manner.

Our approach to building data infrastructure and data platforms is driven by a passion for innovation and a commitment to delivering outsized value. We recognize that our clients bring unique domain expertise and insights to their data, so we collaborate closely to integrate their expertise into our engineering solutions. From data democratization to data storytelling, our platforms are designed to help our clients unlock the full potential of their data.

Tools and technologies we employ include:

Amazon Web Services (AWS)
Google Cloud Platform (GCP)
Databricks
Snowflake
DBT
Redshift
Airflow
Cloudera
Fivetran
Airbyte
Neo4j

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Data engineering

TXI is proficient in the latest data engineering tools and technologies, and follows modern software engineering principles such as Agile engineering, DevOps practices, and Continuous Integration and Continuous Deployment (CI / CD) to ensure that our solutions are of the highest quality. Our engineers are experts in the “ETL” process: Extracting raw data, Transforming and curating it, and Loading it into a database. We design systems that enable data scientists and analysts to access and interpret data to move client organizations forward.

To keep client data safe, we follow the latest security best practices to ensure that our data platforms are secure and compliant with industry regulations. We leverage modern security technologies such as identity and access management (IAM), encryption, and monitoring to provide a secure data platform that protects data from unauthorized access or data breaches.

TXI takes a design-thinking approach, working directly with users and consumers to identify good sources of data, to curate the data so that it’s useful and intuitive, and to apply appropriate constraints and controls to protect sensitive data.

To complement the best-in-class data infrastructure we rely on, we take a modern approach to data engineering, leveraging the latest software engineering and security best practices. TXI data engineers drive innovation with data and are key members of any cross-functional data product team. They are skilled in:

Data Modeling
Data Pipelines
Data Quality
Data Accessibility
Data Observability
Performance Improvement
Data Security & Governance

Case Studies

Converging data and digital to accelerate the development of life-changing therapies for patients

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Analysis & visualization

The end result of clean, organized, available data? Dynamic dashboards and other visualizations that can be used to make fast decisions and excellent predictions. We take a human-centered, design-led approach to support the people who provide context to data, and who use it to tell stories and make predictions. Raw data by itself has minimal value, but the right visualization, in the right hands, can transform it into knowledge, enabling business insights and decisive actions.

TXI has extensive experience working with top data visualization tools to deliver visually appealing, user friendly, and informative data visualizations:

Tableau
D3.js
PowerBI
Spotfire
Superset
Microstrategy
QlikSense
Sisense
Looker

A good data visualization framework provides a user-friendly interface, supports a broad range of data sources, and offers advanced analytics features like predictive modeling and machine learning. Tools like these can reveal insights that are hidden deep in data lakes or warehouses. And through visualizations, data teams can also support “human in the loop” automation, in which human interaction complements and supports a learning AI system.

Our clients come to us looking for ways to make sense of their data, rising above individual components to develop knowledge that can lead to new breakthroughs and discoveries. TXI can help accelerate this process by bringing our product innovation and data engineering expertise together with our clients' deep understanding of their domains. We complement data-aware clients with capabilities to create integrated teams that can envision and deliver data-powered products.

The result: products and platforms that transform business opportunities, enabling data-driven decision making to quickly respond to user and customer needs.

What we are building together is empowering scientists to answer scientific questions in minutes instead of weeks.

VP, R&D at Fortune 100 BioPharma

Case studies

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Digital Health

Converging data and digital to accelerate the development of life-changing therapies for patients

Comms & media

Automating high-stakes business analysis to empower faster decision-making

Case Study

Training doctors with a flexible, CME-crediting mobile app

FAQ

FAQs

What is a custom software solution for business intelligence?

A custom software solution for business intelligence is a software application designed to translate raw data into meaningful insights for decision-making purposes. It extracts, transforms, and loads data from various sources and presents it in ways that allow decision-makers to derive insights quickly and accurately.

Why do businesses need custom software solutions for business intelligence?

Businesses need custom software solutions for business intelligence to make informed decisions based on data-driven insights. By extracting and analyzing data from various sources, businesses can identify patterns, trends, and insights that would not be apparent otherwise.

What are the benefits of a custom software solution for business intelligence?

The benefits of a custom software solution for business intelligence include faster and more accurate decision-making, increased productivity and efficiency, improved resource allocation, better risk management, and increased profitability.
What types of data can be analyzed using a custom software solution for business intelligence?

A custom software solution for business intelligence can analyze various types of data, including sales data, customer data, financial data, website traffic data, social media data, and more.

What are the steps involved in creating a custom software solution for business intelligence?

The steps involved in creating a custom software solution for business intelligence include data extraction, data transformation, data loading, data analysis, and data visualization.

What programming languages are used to create custom software solutions for business intelligence?

Some popular programming languages TXI uses to create custom software solutions for business intelligence include Python and Java.

What is the difference between ETL and ELT?

ETL (extract, transform, load) refers to a process of extracting data from various sources, transforming it into a standard format, and loading it into a data warehouse or database. ELT (extract, load, transform) is a similar process, but it loads data into a database before transforming it.
What is a data warehouse?

A data warehouse is a large repository of data that is used for business intelligence purposes. It is designed to store and manage data from various sources, and to support complex queries and data analysis.
What is data visualization?

Data visualization is the process of presenting data in a graphical or visual format, such as charts, graphs, or maps. It is used to make data easier to understand and to identify patterns and trends.
What are some popular data visualization tools?

Some popular data visualization tools include Tableau, Power BI, QlikView, and D3.js.
What is machine learning?

Machine learning is a type of artificial intelligence that allows computer systems to learn and

improve from experience, without being explicitly programmed.
How can machine learning be used for business intelligence?

Machine learning can be used for business intelligence by analyzing large amounts of data to identify patterns and insights, and by using those insights to make more accurate predictions and decisions.
What is natural language processing (NLP)?

Natural language processing (NLP) is a type of artificial intelligence that allows computer systems to understand and interpret human language.
How can natural language processing be used for business intelligence?

Natural language processing can be used for business intelligence by analyzing unstructured data, such as customer feedback, social media posts, and emails, to identify patterns and insights.
What is predictive analytics?

Predictive analytics is a type of data analysis that uses statistical and machine learning algorithms to make predictions about future events or trends.
How can predictive analytics be used for business intelligence?

Predictive analytics can be used for business intelligence by analyzing past data to make predictions about future trends and events, and by using those predictions to make more informed decisions.
What is big data?

Big data refers to large and complex datasets that are difficult to process and analyze using traditional data processing methods. Big data typically involves large volumes of data with high velocity, variety, and veracity. This data can come from various sources such as social media, sensors, web logs, and more. To extract insights from big data, businesses typically use specialized tools and technologies, such as Hadoop, Spark, and NoSQL databases.
How is AI used to gather business intelligence in custom software?
Artificial Intelligence (AI) can be used in gathering business intelligence in custom software by enabling systems to process large volumes of data and identify patterns, trends, and insights that might not be apparent otherwise. Some of the ways AI can be used for business intelligence include:
1. Natural Language Processing (NLP): AI-powered NLP tools can analyze unstructured data such as customer feedback, social media posts, and emails to identify patterns and insights.
2. Machine Learning (ML): AI-powered ML algorithms can be used to analyze large datasets and identify patterns and insights that can be used for decision-making.
3. Predictive Analytics: AI-powered predictive analytics tools can be used to analyze past data to make predictions about future trends and events.
4. Image and Video Analysis: AI-powered image and video analysis tools can be used to extract insights from visual data, such as identifying patterns in customer behavior or detecting defects in manufacturing processes.
By using AI to gather business intelligence, custom software can provide more accurate and actionable insights, which can lead to better decision-making and improved business performance.

Analyze

Unique insights. Stronger predictions. Better decisions.

Data strategy

Infrastructure & platforms

Data engineering

Converging data and digital to accelerate the development of life-changing therapies for patients

Analysis & visualization

Analyze case studies

FAQs

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