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At AI Field Day 7, Parvathi Letha, Head of Product Management at Articul8, and Dr. Arun Subramaniyan, Founder and CEO of Articul8, presented the Articul8 platform, a secure, domain-specific generative AI solution tailored for high-value enterprise use cases. Parvathi detailed the architecture, beginning with its autonomous data perception functionality, which ingests and semantically connects structured and unstructured data—including PDFs, tables, images, and CAD drawings—into a living, schema-aware knowledge graph. This knowledge graph serves as the core institutional memory, continually evolving through user interactions, and supports auditability and traceability by tracking updates and allowing for corrective feedback, ensuring personalized and adaptive intelligence for each enterprise and user.
A cornerstone of Articul8’s approach is its agentic reasoning engine, which utilizes hundreds of domain- and task-specific agents. When a complex enterprise mission is received, the reasoning engine breaks it down into sub-missions and autonomously selects the most appropriate agent for each segment. This collaborative, context-aware architecture emulates expert teams, vastly accelerating tasks such as root cause analysis, compliance checks, and network troubleshooting, and supporting outcomes with fine-grained traceability. Articul8’s hyper-personalization goes further with adaptive user interfaces and the capability to create digital twins, allowing outputs and insights to reflect individual user decision styles and enterprise workflows. Domain-specific models span industries like semiconductor, aerospace, manufacturing, supply chain, and telco, with bespoke agents such as a highly specialized Verilog model for chip design and general-task agents for time series, table, and chart understanding.
For enterprise consumption, Articul8 supports multiple models: companies can subscribe to the full suite as a traditional enterprise software platform or deploy select agents a la carte via the AWS Marketplace, paying per API call for agents like LLM IQ, which benchmarks LLMs for specific use cases, or the Network Topology Agent, which digests network logs and diagrams to support troubleshooting. The platform’s industry-specific models are co-developed with partners such as the Electric Power Research Institute and leading aerospace firms, ensuring both robust data integration and expert validation. Articul8’s agent-of-agent architecture has been in production for more than two years and is already driving measurable ROI in semiconductor root cause analysis and CAD validation, reducing processing times from days to hours and delivering over 93 percent detection accuracy—while maintaining data control and auditability entirely within customer security perimeters.
Personnel: Arun Subramaniyan, Parvi Letha
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