Democratize your data analysis. Expero’s Jetpack AI Assisted Analytics Module is an innovative solution designed to elevate the approach to data analysis through the integration of advanced artificial intelligence. At its core, the module employs a sophisticated combination of Large Language Models (LLM) with Retrieval Augmented Generation (RAG) technology. This innovative blend enables the creation of a digital guide that excels in providing insightful, conversational navigation through complex data sets, providing novel insights and analysis.
Leveraging Expero CONNECTED's proprietary semantic view models, the Jetpack module facilitates seamless discourse with a broad spectrum of heterogeneous data sources, including knowledge graphs, time series, geospatial and large relational databases. This feature allows users to engage with the Jetpack digital agent in natural language, democratizing data analysis and making it accessible to individuals regardless of their technical background. Through intuitive dialogues, users can easily query, explore, and understand their data, transforming raw information into actionable insights.
A standout feature of the Jetpack module is its capability to support users in progressively building and refining hypotheses. Jetpack extends beyond synthesizing natural language into queries, it interprets the user’s intents and guides them through data analysis, specialized to their specific domains. By interacting with the module, users can pose questions, to which Jetpack responds by retrieving and analyzing relevant data, subsequently cataloging the findings in natural language and illustrating them in compelling data visualizations . This iterative process not only enhances the depth and breadth of data exploration but also fosters a deeper understanding of the underlying patterns and trends.
Importantly, the Jetpack module prioritizes the security and privacy of the data it handles. Utilizing closed-circuit LLM technology, it ensures that the entire data analysis process remains confined within a secure environment, thereby eliminating the risk of data leakage. This focus on data security makes Jetpack an ideal solution for organizations that hold data privacy and protection in high regard.
Jetpack empowers firms to swiftly establish a secure, Large Language Model (LLM) driven AI analytics concierge meticulously tailored for data analytics. This specialized tool stands out for its ability to facilitate gaining insights from complex data, transforming how businesses interact with their information landscape. Jetpack’s multi-agent architecture allows rapid deployment and specialization without needing to build a complex system from the ground up, ensuring high security and that the solution is deeply integrated into the user's specific data analytics needs and challenges.
Simplified Data Interaction: Jetpack's agent-driven UI navigation means that the experts who understand their data can still use the tools that embody their expertise: domain-specific visualizations and workflows.
Track Your Analysis Journey: Jetpack maintains a comprehensive record of user inquiries, ensuring that users can track their analytical processes, revisit previous analyses, and build upon their insights over time.
Jetpack is distinguished from simplified LLM wrappers or query generating sidekicks by its modular multi-agent and multi-domain data architecture. Jetpack works with user context and as an agent with deliberate intent.
The smartest AI in the world can’t function if it’s kept in the dark. Jetpack is configured with an understanding of the user and the work they are trying to do.
Persona Context: Jetpack is configured to understand the user’s job and typical tasks so that a conversation can use domain-specific language and ideas. Where possible, the appropriate LLMs can even be specialized with proprietary material to further augment its usefulness. The intent is not for an LLM to memorize this data, which they are not good at, but instead to use appropriate vernacular and be aware of ideas which are not available in the publicly trained LLMs.
Data Context: Jetpack contains a curated set of agent workflows including specialized LLMs which can converse with data across multiple domains, including knowledge graphs, time series, and relational data. A “speed layer” can ingest key data for rapid analysis. The CONNECTED semantic layer can characterize available data in terms of well-known domain contexts.
A user’s conversation with JetPack is not simply a conversation with an LLM; Jetpack works with multiple models and tools in a deliberate agent workflow to assist the user. The results can be new visualizations, natural language summaries, suggestions for future direction, and even rearrangement of or actions in an existing user interface.
The process begins with an Intent Identification stage, where the system determines the nature of a user's inquiry by comparing it with a database of available intent handlers. This step involves analyzing the user's context and the range of recognized intents, with the aid of a sophisticated language model to pinpoint the relevant intents tied to the user's query. This phase wraps up by preparing the necessary intent modules for the next steps.
In the subsequent phase, Intent Handling, the request is subjected to a detailed analysis tailored to the specific intent. A customized request is formulated for the language model, integrating both the user's context and intent-specific parameters. This leads to a collection of outcomes, each prepared for use in the final phase. The system is designed to be modular, allowing for the seamless addition of new intent handlers, such as:
The last phase, Applying Results, involves updating the system based on the insights gained from the Intent Handling phase. Outcomes are aligned with a range of result handlers tasked with implementing these updates, covering areas such as:
Like the earlier phases, this stage allows for the integration of new result handlers, promoting the system's flexibility and growth potential. Altogether, these components constitute a versatile framework designed to understand and process user inquiries effectively, thereby enhancing user engagement and analytical efficiency.
Expero's Quickstart PoC is an end-to-end service designed to quickly demonstrate the practical value and viability of Jetpack within approximately eight weeks. This PoC is not just about showcasing Jetpack's potential to revolutionize data analysis; it's also a strategic exploration into how this technology can be seamlessly integrated and scaled within your organization's existing value streams.
Our engagement goes beyond the technical implementation of Jetpack; we place a significant emphasis on understanding precisely how and where Jetpack's technology can be applied within your value stream for maximum impact. This approach ensures that the PoC is not only a demonstration of Jetpack's capabilities but also a practical guide on embedding this technology in ways that directly contribute to your strategic objectives and operational efficiency.
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