Pre-built AI models for users at all levels
Our CGI TextAI platform empowers both non-technical and technical users to develop custom solutions with little or no prior AI technical knowledge. This low-code, adaptable platform uses AI and machine learning (ML) automation to analyze structured and unstructured data at scale—providing enhanced data analytics and a better user experience, while also reducing operational costs.
Customizable for your specific needs
CGI TextAI can be customized for unique datasets, infrastructure requirements and content needs across industries. Application examples include chatbot systems leveraging large language models (LLM), customer feedback analysis, fake news detection, ticket processing automation, summarizing information, customer complaint classification, speech tagging, content writing, and more.
Additionally, you can use your domain-specific experiences to quickly classify and analyze data, and easily build models to make predictions. CGI TextAI also offers flexible and seamless integration with existing tools and infrastructure to help you incorporate AI into your analytics processes faster.
- Reduce complexity by solving business problems without prior in-depth AI experience
- Implement agile and custom service solutions by scaling servers up or down, depending on the load—making it easier to track workloads and progress
- Rapidly develop and deploy AI with pre-built AI models, ML pipelines, project templates and ready-made datasets
- Ease-of-use for users at all levels via low-code, ready-made AI/ML models
- Cross-industry applications including banking, insurance, consumer services, life sciences, automotive, and more
- Customizable to meet unique organizational needs
- Flexible deployment for on-site, off-site, or cloud environments
- Optical character recognition (OCR)
- Speech to text
- Text generation using LLMs
- Natural language understanding
- Text clustering
- Text classification
- Topic and keyword extraction
- Text summarization
- Name entity recognition
- Part-of-speech tagging
- Semantic analysis
- Data anonymization
- Serverless data infrastructure
Cases in point
- Accelerating regulatory content creation
For organizations looking to help users draft and manage regulatory content, where generative AI and LLMs do the heavy lifting, CGI TextAI includes an AI accelerator that serves as a generative AI natural language document assistant. The accelerator’s efficiency and speed are ideal for creating initial drafts of regulatory content much faster than traditional approaches. This tool is designed for stable content generation and integration with intelligent authoring tools.
- Natural language interactions with customer data
Leveraging LLMs to make databases conversational creates exciting possibilities for natural language interactions with multiple data sources. By integrating LLMs into database systems, customers can query and manipulate data using conversational language, enhancing accessibility and the user experience. CGI TextAI simplifies data exploration and analysis, making each more intuitive and efficient for both technical and non-technical users.
- Free-text intelligence
Enterprises dealing with free-text field data encounter numerous challenges due to its unstructured format, making analysis complex and prone to inaccuracies. Privacy concerns further emphasize the need for advanced natural language processing (NLP) techniques for efficient extraction and handling. Addressing these issues, CGI TextAI adopts a custom-generated analytics and insights approach, leveraging ensembled NLP techniques. This powerful tool finds applications in ticketing systems and survey feedback analysis—drastically reducing processing time from weeks to mere minutes.
- Invoice archive digitization
A European forestry association had archives containing hundreds of thousands of invoices. A lack of meta data or a clear knowledge of what the invoices contained made them difficult to digitize. CGI TextAI, using AI-supported information extraction, structuring and deep learning algorithms, performed data cleaning and post processing to extract the required information from the invoices. The solution reduced employee workloads and allowed for further and more substantial data analysis.