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Certinia Unveils Veda: AI Agents for End-to-End Professional Services Workflows

AI Agents Professional Services Workflow Automation Enterprise AI Knowledge Graphs Intelligent Automation
November 04, 2026

This summary and analysis were generated by AI from the original article at AI – SiliconANGLE and may contain errors (how Viqus works). Read the source for full details.

Viqus Verdict Logo Viqus Verdict Logo 7
Context-Aware Enterprise AI Blueprint
Media Hype 4/10
Real Impact 7/10

Article Summary

Certinia announced significant advancements in its platform by introducing Veda, an enterprise-grade intelligent operations engine, and integrating the Moonnox AI-native services delivery platform. This combination aims to automate complex, context-dependent tasks across the entire professional services lifecycle. Veda provides rules-bound, autonomous workflows, while Moonnox adds crucial context via knowledge graphs, connecting unstructured data like emails and chats with structured records like timecards. The company further expanded its offering with a System of Action, increasing its agent library to guide clients through complex, measurable business outcomes, positioning its platform as a blueprint for enterprise AI adoption.

Key Points

  • Certinia launched Veda, an intelligent operations engine, to automate complex, context-aware workflows within professional services.
  • The acquisition of Moonnox enhances Veda by integrating unstructured data (emails, chats) into a context graph alongside structured project data.
  • The expanded System of Action provides numerous persona-based agents designed to guide clients through measurable business outcomes in project delivery.

Why It Matters

This is a notable demonstration of enterprise AI moving beyond simple automation to tackle the complexity of knowledge work. By grounding its agents in deep operational context—combining structured ERP data with unstructured communication—Certinia is attempting to solve the 'last mile' problem of AI adoption in high-touch service industries. If successful, this architecture could become a blueprint for how AI agents manage consequential, multi-stage business processes, shifting the focus from mere capability to verifiable, governed outcomes.


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