In a recent discussion at VentureBeat’s Transform 2024, Elastic CEO Ash Kulkarni and DocuSign CPO Dmitri Krakovsky shed light on the transformational power of generative AI in enterprise search and contract management. The conversation emphasized the increasing relevance of AI-driven search capabilities for organizations grappling with extensive data repositories and intricate contractual relationships. Elastic’s enterprise search strategy has undergone a significant evolution with the integration of generative AI. The introduction of the Elasticsearch Relevance Engine (ESRE) in May 2023 marked a pivotal moment for the company, signaling a strategic shift in search technology. ESRE blends traditional keyword-based search methods with advanced vector search functionalities, enabling a deeper comprehension of context and semantics within vast data sets. This hybrid approach equips Elastic to offer its clients more sophisticated means of retrieving pertinent documents from their Elasticsearch databases, whether through vector search, text search utilizing BM25, or a blend of techniques.
Kulkarni elaborated on Elastic’s progress by incorporating retrieval augmented generation (RAG) into its vector database technology. He emphasized, “We’re possibly one of the most extensively used vector databases out there, and we’ve integrated it.” By integrating these features into its database functionality, Elastic leverages the accumulated expertise from years of work on Elasticsearch. With enhanced capabilities such as permissions, faceted search, hybrid search, and the flexibility to employ multiple search techniques like BM25 basic search alongside vector search, Elastic is positioned to cater to diverse enterprise search needs. Kulkarni underscored the company’s commitment to flexibility and developer empowerment, stating, “It’s crucial to provide developers with a plethora of choices and functionalities, allowing them the freedom to select models that best suit their requirements. This ethos is ingrained in our DNA.”
On the other hand, DocuSign leverages AI to revolutionize contract management processes. Krakovsky outlined their vision of utilizing agents powered by AI to assist in negotiating contracts. The Intelligent Agreement Management (IAM) platform is designed to convert static contract data into actionable insights. Core components like Maestro, Navigator, and App Center collaborate to analyze contracts systematically. This platform addresses a significant void in enterprise digitization, as contracts often exist as static PDFs lacking the functionality for comprehensive reasoning, querying, or scaling.
IAM facilitates the transformation of static PDFs into structured, analyzable data. Krakovsky illustrated this with an impactful example where a customer identified inconsistencies and optimization opportunities across 70 contracts with a system integrator, consequently saving over $100 million. What used to necessitate manual review of hundreds of contracts can now be largely automated, demonstrating IAM’s potential to elevate contract management into a strategic business function. Both Kulkarni and Krakovsky highlighted the significance of responsible AI adoption and emphasized the need for transparency, caution, and end-to-end solutions to enhance operational efficiency and customer experience.
Cost optimization emerges as a critical factor in AI implementation, with emphasis on resource utilization to maximize value and efficiency. Kulkarni predicted a downward trend in inference costs due to hardware and technology advancements, alongside increased competition in the large language models (LLMs) domain. As AI’s capabilities continue to expand, particularly in areas like multimodal models and insights extraction in contract management, enterprises are poised to leverage AI-driven tools for more informed decision-making and enhanced customer interactions.
Real-world applications of AI in enterprise settings, such as using Elastic’s technology to automate internal processes at Cisco or transforming wealth management client interactions at a Fortune 100 bank, underscore the broad-reaching impact of AI-powered solutions. From intelligent search capabilities to automated contract analysis, the potential benefits are vast. However, success in harnessing this potential hinges on navigating technical, ethical, and operational challenges effectively. Issues surrounding data privacy, model transparency, and cost-effective scaling demand careful consideration to ensure sustainable and ethical AI adoption in enterprise environments.
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