Case Study: Designing AI-Augmented Enterprise Investigation Systems
Enterprise investigations slow down when evidence is scattered across systems. The challenge is bringing retrieval, agent workflow, and human oversight together without burying investigators in more noise. In "Case Study: Designing AI-Augmented Enterprise Investigation Systems", Santosh Vasudevan and John Selvaraj Arulappan connect AI agents and RAG to investigation workflows where speed still needs human judgment.
Session details
Organizations today face growing operational complexity, fragmented enterprise data, and increasing pressure to investigate anomalies, incidents, and high-risk events faster than traditional workflows allow. This interactive case study session explores how modern AI architectures can augment enterprise investigation systems by accelerating evidence gathering, cross-system analysis, policy retrieval, and structured decision support while maintaining human accountability and oversight. Using a realistic enterprise investigation scenario, attendees will walk through how a traditional investigation workflow operates, where operational bottlenecks emerge, and how AI-assisted systems can improve speed, consistency, and visibility across complex environments. The session focuses on practical implementation patterns rather than theoretical AI concepts, including: * AI agents for multi-step investigation workflows * Retrieval-Augmented Generation (RAG) for organizational knowledge retrieval * Enterprise tool orchestration and system integration * Explainable AI outputs and structured reasoning * Human-in-the-loop decision support models * Designing AI systems that augment expertise instead of replacing it Attendees will participate in guided workflow redesign exercises and group discussions to evaluate where AI provides meaningful operational leverage and where human judgment remains essential. The session is intentionally industry-agnostic and applicable across operations, cybersecurity, risk management, enterprise support functions, compliance, and other investigation-heavy environments. Attendees will leave with practical frameworks, architectural ideas, and governance considerations they can apply when designing AI-augmented enterprise workflows inside their own organizations.
Primary action
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Agenda facts
- Format
- Interactive Session
- Kind
- Conference Session
- Topic
- Artificial Intelligence and Machine Learning
- Level
- Beginner
- Time
- Oct 30, 2026, 3:45 PM
- Room
- Room E
- Duration
- 60 min
Speakers
Link partners to speaker kits when available, or to the public speaker profile on mitechcon.net.
Santosh Vasudevan
John Selvaraj Arulappan
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LinkedIn
Session LinkedIn Post
Enterprise investigations slow down when evidence is scattered across systems. The challenge is bringing retrieval, agent workflow, and human oversight together without burying investigators in more noise. In "Case Study: Designing AI-Augmented Enterprise Investigation Systems", Santosh Vasudevan and John Selvaraj Arulappan connect AI agents and RAG to investigation workflows where speed still needs human judgment. 📅 October 28–30, 2026 📍 Oakland University, Rochester, MI 🔗 https://www.mitechcon.net/sessions/case-study-designing-ai-augmented-enterprise-investigation-systems/?utm_source=partner-kit&utm_medium=partner&utm_campaign=mitechcon-2026&utm_content=session-case-study-designing-ai-augmented-enterprise-investigation-systems #MITechCon #AIAgents #RAG #EnterpriseAI
Short social
Short Session Post
Enterprise investigations slow down when evidence is scattered across systems. Learn AI architecture patterns that accelerate analysis with human oversight. https://www.mitechcon.net/sessions/case-study-designing-ai-augmented-enterprise-investigation-systems/?utm_source=partner-kit&utm_medium=partner&utm_campaign=mitechcon-2026&utm_content=session-case-study-designing-ai-augmented-enterprise-investigation-systems #MITechCon #AIAgents
Newsletter / email
Newsletter Or Email Blurb
Feature this MITechCon 2026 session in your newsletter or email: "Case Study: Designing AI-Augmented Enterprise Investigation Systems". Enterprise investigations slow down when evidence is scattered across systems. The challenge is bringing retrieval, agent workflow, and human oversight together without burying investigators in more noise. In "Case Study: Designing AI-Augmented Enterprise Investigation Systems", Santosh Vasudevan and John Selvaraj Arulappan connect AI agents and RAG to investigation workflows where speed still needs human judgment. Format: Conference Session. Topic: Artificial Intelligence and Machine Learning. Level: Beginner. Scheduled for Oct 30, 2026, 3:45 PM in Room E. Learn more and share the session: https://www.mitechcon.net/sessions/case-study-designing-ai-augmented-enterprise-investigation-systems/?utm_source=partner-kit&utm_medium=partner&utm_campaign=mitechcon-2026&utm_content=session-case-study-designing-ai-augmented-enterprise-investigation-systems