Modules

Deployment

Connect External Sources

Integrating with external systems like CRM, ERP, and business intelligence tools enhances the AI’s analytical capabilities. By accessing structured and unstructured data from multiple sources, the AI can provide real-time business insights, customer behavior predictions, and operational efficiency reports, making it a valuable decision-support tool.

Support Analysis Correction

Errors in AI-driven analysis can impact decision-making. The system must support analysis correction, allowing users or automated mechanisms to adjust and refine incorrect interpretations. By learning from corrections, the AI improves its accuracy over time, ensuring more reliable insights and predictions.

Dedicated Domain Library

To deliver precise and relevant analysis, the AI core includes a dedicated domain library that contains specialized knowledge for industries such as finance, healthcare, manufacturing, and retail. This allows the system to generate more context-aware insights, reducing errors caused by generic language models.

Self-Train NLP Library

Continuously improve its understanding of language and context. A self-training NLP library allows the AI to refine its language processing capabilities based on new data, user interactions, and evolving industry trends. This ensures higher accuracy in text comprehension, sentiment analysis, and predictive modeling without frequent manual updates.

Support Different File Formats

Support analysis with multiple file formats, including PDF, Excel, CSV, JSON, and XML, ensuring compatibility with various business tools. This flexibility allows users to easily share, process, and analyze data across different platforms.

Allow API Connection

For seamless integration with enterprise systems, the AI analysis core must support API connections. This allows businesses to embed AI-driven insights directly into their dashboards, automation workflows, and third-party applications, enabling real-time decision-making and process optimization.

Modules

Deployments

Provide Alerts and Suggestions

To support proactive decision-making, the AI core must provide alerts and actionable suggestions based on real-time analysis. It can detect anomalies, predict trends, and send alerts about critical business events, such as potential fraud, operational risks, or market changes, helping organizations respond promptly.