> ## Content Index
> Fetch the complete content index at: https://www.aiacceleratorinstitute.com/llms.txt
> Use this file to discover other available public pages before exploring further.

# Can you trust your workflow in production?
- URL: https://www.aiacceleratorinstitute.com/how-to-validate-monitor-govern-agentic-ai/
- Published: 2026-10-06T14:45:45.000Z
- Updated: 2026-10-06T14:45:45.000Z
- Description: How do you validate an AI or agentic workflow well enough to confidently move it into production - and keep it reliable once it is there?
- Author: AIAI
- Tags: AIAI, Live session, Agentic AI

Moving an agentic workflow out of the pilot stage is where many enterprise AI programs stall.

A workflow can look impressive in a demo and still fall short in production, and prompt-level testing alone rarely tells you whether a workflow is truly ready.

Agents that answer customer queries, flag suspicious transactions or process claims need to be safe, evidence-based, policy-compliant and appropriately constrained.

Join us and **Innodata** for a practical, conversational look at how to validate AI and agentic workflows before deployment, and how to keep them reliable once they're live & begin to scale.

---

**Why attend?**

- **Production readiness is harder to define than it looks.** Many teams test outputs but miss the failure modes that matter most to the business.
- **The same principles apply across very different workflows.** From customer support and AML in financial services to claims processing in insurance, see how validation requirements shift with each workflow and its business objective.
- **There's a clear path from pilot to production.** Follow a framework that takes you from experimentation to validation, deployment and continuous monitoring.

---

**What you'll learn**

- What you actually need to validate before an AI workflow is production-ready
- How to connect technical evaluation metrics to the business KPIs your leadership cares about
- Where automation is sufficient and where human judgment is still required
- How to use the same framework to monitor reliability long after deployment

---

**Speaker**

**Jyotsna Jha** Vice President of Product, AI/LLM Practice, Innodata

Jyotsna leads product strategy and execution for Innodata's agentic evaluation, observability and feedback systems - helping enterprises build, govern and continuously improve AI agents operating in real-world workflows. She has built and scaled AI products across real-time intelligence, intelligent document processing and data platforms.