How to Ensure AI Chatbots Stay Accurate, Compliant and Secure

AI chatbots are reshaping customer interactions, but they also introduce new risks. In this episode of Full Tech Ahead, host Amanda Razani sits down with Andre Scott, Developer Advocate at Coralogix, to discuss how businesses can protect themselves from chatbot failures, misinformation, and data leaks.

Coralogix provides a full-stack observability and monitoring platform that includes logs, metrics, traces, APM, and AI observability. Scott explains how organizations can instrument their AI systems for transparency using open telemetry and evaluation tools, ensuring chatbots remain compliant, secure, and reliable as regulations tighten across industries.

Summary

Andre Scott shares insights into the current challenges of managing AI chatbots in enterprise environments. Unlike traditional deterministic systems, chatbots are non-deterministic—meaning even successful responses can fail catastrophically. Scott emphasizes that businesses must move beyond static monitoring to adopt AI evaluation engines that assess correctness, detect prompt injection, and ensure chatbots stay on topic.

He outlines a roadmap for companies:

• Instrument chatbots with open telemetry and trace kits.
• Integrate evaluation layers to analyze model behavior in real time.
• Comply with evolving regulations around data protection and AI accountability.

Failure to do so can lead to reputational and regulatory damage, as seen in incidents like Air Canada, DPD, and Chevrolet’s chatbot misfires. Scott also highlights the benefits of chatbots for customer support and productivity when they’re properly evaluated and monitored. Looking ahead, he predicts a future of voice-enabled and multimodal AI agents, which will bring both innovation and new oversight challenges.

Quotes

• “Evaluation is the crown jewels when it comes to these agentic AI workflows.”
• “Traditional monitoring shows a 200 OK, but with AI, that doesn’t mean success — it could still be failing catastrophically.”
• “Do you really own your code? You need open-source instrumentation to truly understand what’s happening inside your models.”

Takeaways

• AI chatbots require evaluation, not just monitoring. Traditional success metrics don’t capture AI logic failures.
• Open-source instrumentation such as LM Trace Kit and OpenTelemetry enables visibility into chatbot behavior.
• Compliance and privacy risks including GDPR, HIPAA, and data leakage demand proactive observability.

Timestamps

[00:00] Introduction — Andre Scott and Coralogix

[01:00] AI chatbot failures: Air Canada, NYC, and Chevrolet

[01:30] Why chatbots still fail and the problem of non-determinism

[03:00] How evaluation engines detect errors and hallucinations

[03:40] Integrating evaluators and open telemetry

[05:00] Repercussions of poor chatbot oversight

[06:20] Compliance and regulation readiness

[07:30] Business benefits of responsible AI chatbot use

[08:20] Future trends including speech-to-speech and multimodal chatbots

[08:57] Key takeaway: own your code, monitor everything, and evaluate always

Links / Resources

Website: Coralogix - https://coralogix.com/

LinkedIn: Andre Scott - https://www.linkedin.com/in/andre-scott/

Podcast: Full Tech Ahead — Hosted by Amanda Razani

Find Amanda Razani on LinkedIn. https://www.linkedin.com/in/amanda-razani-990a7233/