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Distyl
AI Native Workflows for Mission Critical Enterprise Operations

What is Distyl?

Distyl is an enterprise-grade AI platform that specializes in building and deploying production-ready AI systems for Fortune 500 companies. At its core is Distillery, their proprietary platform that transforms organizational knowledge into dynamic, auditable processes that scale with business needs.

The platform employs an AI-native methodology that integrates artificial intelligence into every aspect of operations, enabling rapid generation, refinement, and deployment of scalable solutions. With a focus on transparency and explainability, Distyl's systems are tailored to specific business contexts and subject matter expertise, ensuring reliable automation of core business processes.

Features

  • AI-Driven Workflow Generation: Automatically creates AI-native routines from organizational assets
  • SME Collaboration System: Enables iteration and evolution of workflows with version control
  • Audit Trail: Detailed logging and tracing of all LLM calls, tool calls, and reasoning steps
  • Forward Deployment: Dedicated engineering team ownership of implementation outcomes
  • Rapid Implementation: Accelerates time-to-value from months to days

Use Cases

  • Enterprise process automation
  • Business workflow optimization
  • Organizational knowledge transformation
  • Core operations automation
  • System deployment and scaling

FAQs

  • How does Distyl ensure transparency in its AI systems?
    Distyl ensures transparency through detailed logging and tracing of each LLM call, tool call, reasoning step, and guardrail, making all actions taken by Routines fully auditable.
  • What is Distillery?
    Distillery is Distyl's proprietary platform designed to quickly generate, refine, and deploy AI Native workflows called Routines, transforming organizational knowledge into dynamic, auditable processes.
  • How does the SME collaboration process work?
    Subject Matter Experts (SMEs) can iterate on and evolve the Routines, with all changes being versioned, reviewable, and end-to-end deployment tested to ensure system reliability.

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