Insights

Charting the Course: Conversations with Navigate Ventures’ Portfolio Companies Bringing AI to complex contact center environments, with Peter Iansek, Co-founder and CEO of Operative Intelligence

Charting the Course: Conversations with Navigate Ventures’ Portfolio Companies 

Bringing AI to complex contact center environments, with Peter Iansek, Co-founder and CEO of Operative Intelligence

Insightful Discussion with Peter Iansek, Co-founder of Operative Intelligence

By Ivan Nikkhoo, Managing Partner, Navigate Ventures

At Navigate Ventures, we support the founders of high-potential SaaS startups as they look to bridge the growth capital funding gap.
Recently, we invested in Operative Intelligence, a leading AI-enabled enterprise platform for contact/call center management. This platform aims to help organizations unlock the potential of every human interaction by radically improving customer experiences, faster, and at scale.
Conversation with Peter Iansek
Good to see you Peter. Why does AI represent a breakthrough for contact centers and the world of customer experience?
Over the last decade, we’ve seen an explosion of new technology in this space, driven by cloud migration and a focus on customer experience as a revenue booster. Despite significant investment, contact center volumes have increased, and customer experience has dropped to a decade-low. AI can address this by identifying customer needs in real-time through automated data analysis.
So Operative Intelligence can analyze all the data and give contact centers a better understanding of customer needs?
Exactly. Our AI answers the foundational question, “What do customers really want?” By analyzing unstructured data in real time, we reveal specific, actionable issues that drive customer interactions.
Which industries or verticals are particularly suited to this technology?
It’s more about the contact center’s scale rather than a specific industry. We work with industries with large customer bases, like banks, airlines, insurance companies, and retailers, where our technology helps make sense of vast customer data.
You’ve been selling AI to enterprises since 2020. What are the secrets of your success?
Initially, terms like LLMs and ML weren’t widely understood. We focused on solving a specific problem we knew from experience. Prioritizing security and creating proof points helped us gain trust, and our success is rooted in directly addressing real-world challenges.
Are there any other common barriers you encounter when speaking to large organizations?
A common challenge is skepticism. Companies often hesitate to deploy AI without understanding the problem it solves. Our custom-trained models provide reassurance and align with each client’s unique needs.
How have your enterprise relationships helped to shape your product roadmap?
Insights from contact centers are valuable across the entire business. Product teams use them to improve self-service options, while marketing teams learn what drives inquiries. Addressing these broader needs has shaped our product roadmap significantly.
How do advancements in large language models affect your business model?
Unlike general models, our custom models provide context, unlocking deeper insights and enabling advanced chatbots that handle complex queries without human intervention. This model is central to our future vision for automation.
What’s your view on where the AI market is headed, especially looking toward 2025?
Benchmarking shows that 39% of customer contacts could be automated in the next five years. This is a massive opportunity as enterprises get more comfortable with AI. Infrastructure and GPU availability are challenges, but as they improve, the potential for AI-driven transformation will only grow.
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