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BUSINESSNEXT Enhances GenAI Debugging and NLG Capabilities

BUSINESSNEXT has reaffirmed its commitment to AI-driven transformation with capabilities in Generative AI (GenAI) debugging and natural language generation (NLG). 

Ensuring reliability and performance in AI-driven workflows, BUSINESSNEXT's SFA platform offers advanced debugging for GenAI and LLMs with comprehensive debugging and tracing capabilities for GenAI models and large language models (LLMs). The platform integrates OpenTelemetry (Otel), an AI audit pipeline, and a feedback-driven improvement pipeline to track and analyze AI interactions in real-time.

Through these mechanisms, BUSINESSNEXT enables users to trace user queries, generated responses, invoked tools, actions taken, and knowledge references used in retrieval-augmented generation (RAG) workflows. This granular visibility ensures that errors can be swiftly identified and rectified, optimizing LLM performance and enhancing AI-driven decision-making. These capabilities distinguish BUSINESSNEXT from market competitors, providing enterprises with AI solutions that are transparent, accountable, and continuously improving.

BUSINESSNEXT's AI-powered analytics platform brings next-generation natural language generation (NLG) capabilities to the enterprises, enabling dynamic and context-aware textual responses.

The system autonomously generates narratives for individual visualizations through charts, dashboards, and data models, offering AI-driven insights into trends, anomalies, and patterns. Users can tailor these narratives through BUSINESSNEXT's Prompt Studio, selecting tone (formal, analytical, conversational, or concise) and verbosity levels for greater personalization.

BUSINESSNEXT's AI-driven analytics processes entire dashboards to generate insightful summaries and trend analyses. With a 95% AI-generated response rate, the system provides comprehensive, context-rich explanations that empower business users to interpret complex data with ease. Templatization options ensure consistency, while language customization supports regional and business-specific requirements.

By analyzing entire data models, BUSINESSNEXT generates detailed narratives that uncover correlations, anomalies, and trends. Users can further refine outputs with customizable tone and verbosity settings, ensuring alignment with organizational goals and audience preferences.

With a strong emphasis on AI-driven automation, BUSINESSNEXT's NLG capabilities ensure that AI powered enterprises can leverage data-driven insights for strategic decision-making while maintaining control over customization and business alignment.

"Our continued investment in AI-driven automation ensures that enterprises can trust our solutions to provide both transparency and accuracy in GenAI workflows," said Sushil Tyagi, Executive Director at BUSINESSNEXT. "By embedding deep debugging capabilities and intelligent NLG within our SFA and analytics platforms, we are enabling institutions to enhance customer engagement, optimize operations, and drive strategic growth."

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BUSINESSNEXT Enhances GenAI Debugging and NLG Capabilities

BUSINESSNEXT has reaffirmed its commitment to AI-driven transformation with capabilities in Generative AI (GenAI) debugging and natural language generation (NLG). 

Ensuring reliability and performance in AI-driven workflows, BUSINESSNEXT's SFA platform offers advanced debugging for GenAI and LLMs with comprehensive debugging and tracing capabilities for GenAI models and large language models (LLMs). The platform integrates OpenTelemetry (Otel), an AI audit pipeline, and a feedback-driven improvement pipeline to track and analyze AI interactions in real-time.

Through these mechanisms, BUSINESSNEXT enables users to trace user queries, generated responses, invoked tools, actions taken, and knowledge references used in retrieval-augmented generation (RAG) workflows. This granular visibility ensures that errors can be swiftly identified and rectified, optimizing LLM performance and enhancing AI-driven decision-making. These capabilities distinguish BUSINESSNEXT from market competitors, providing enterprises with AI solutions that are transparent, accountable, and continuously improving.

BUSINESSNEXT's AI-powered analytics platform brings next-generation natural language generation (NLG) capabilities to the enterprises, enabling dynamic and context-aware textual responses.

The system autonomously generates narratives for individual visualizations through charts, dashboards, and data models, offering AI-driven insights into trends, anomalies, and patterns. Users can tailor these narratives through BUSINESSNEXT's Prompt Studio, selecting tone (formal, analytical, conversational, or concise) and verbosity levels for greater personalization.

BUSINESSNEXT's AI-driven analytics processes entire dashboards to generate insightful summaries and trend analyses. With a 95% AI-generated response rate, the system provides comprehensive, context-rich explanations that empower business users to interpret complex data with ease. Templatization options ensure consistency, while language customization supports regional and business-specific requirements.

By analyzing entire data models, BUSINESSNEXT generates detailed narratives that uncover correlations, anomalies, and trends. Users can further refine outputs with customizable tone and verbosity settings, ensuring alignment with organizational goals and audience preferences.

With a strong emphasis on AI-driven automation, BUSINESSNEXT's NLG capabilities ensure that AI powered enterprises can leverage data-driven insights for strategic decision-making while maintaining control over customization and business alignment.

"Our continued investment in AI-driven automation ensures that enterprises can trust our solutions to provide both transparency and accuracy in GenAI workflows," said Sushil Tyagi, Executive Director at BUSINESSNEXT. "By embedding deep debugging capabilities and intelligent NLG within our SFA and analytics platforms, we are enabling institutions to enhance customer engagement, optimize operations, and drive strategic growth."

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There's an image problem with mobile app security. While it's critical for highly regulated industries like financial services, it is often overlooked in others. This usually comes down to development priorities, which typically fall into three categories: user experience, app performance, and app security. When dealing with finite resources such as time, shifting priorities, and team skill sets, engineering teams often have to prioritize one over the others. Usually, security is the odd man out ...

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IT outages, caused by poor-quality software updates, are no longer rare incidents but rather frequent occurrences, directly impacting over half of US consumers. According to the 2024 Software Failure Sentiment Report from Harness, many now equate these failures to critical public health crises ...

In just a few months, Google will again head to Washington DC and meet with the government for a two-week remedy trial to cement the fate of what happens to Chrome and its search business in the face of ongoing antitrust court case(s). Or, Google may proactively decide to make changes, putting the power in its hands to outline a suitable remedy. Regardless of the outcome, one thing is sure: there will be far more implications for AI than just a shift in Google's Search business ... 

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Service disruptions remain a critical concern for IT and business executives, with 88% of respondents saying they believe another major incident will occur in the next 12 months, according to a study from PagerDuty ...

IT infrastructure (on-premises, cloud, or hybrid) is becoming larger and more complex. IT management tools need data to drive better decision making and more process automation to complement manual intervention by IT staff. That is why smart organizations invest in the systems and strategies needed to make their IT infrastructure more resilient in the event of disruption, and why many are turning to application performance monitoring (APM) in conjunction with high availability (HA) clusters ...

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With the 2027 deadline for SAP S/4HANA migrations fast approaching, organizations are accelerating their transition plans ... For organizations that intend to remain on SAP ECC in the near-term, the focus has shifted to improving operational efficiencies and meeting demands for faster cycle times ...

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