Intryc August Releases

Customer support has changed more in the last twelve months than it has in the previous decade. AI is no longer a tool teams experiment with but it’s becoming part of how support organizations operate every day.

But while AI has accelerated, QA workflows haven’t. Even though AI has automated most of the surface level scoring, most teams are still manually pulling reports, assigning reviews, calibrating scorecards, and chasing follow-ups in spreadsheets. A large portion of tickets or calls still require heavy human involvement in their evaluation and there is still lack of trust on AI to audit the most complex, process-driven cases. And for autonomous agents to converse with real customers and collect real customer data, they must strictly adhere to all compliance and monitoring requirements that humans did until now.

There is a clear, big gap in the AI for QA landscape today with its risk surface only increasing by orders of magnitude at an accelerating pace.

So rather than adding AI to existing workflows, we asked a different question: what would QA look like if it were designed from the ground up today?

That thinking led us to rebuild key parts of the platform, introduce new AI-powered workflows, and lay the foundation for autonomous AI Agents that can take on repetitive operational work while keeping humans in control and hold both human and AI agents to the highest standards of performance and conduct.

These releases were shaped by conversations with QA and customer support leaders. Again and again, we heard the same thing: teams don’t need AI for the sake of AI. They need AI that actually removes repetitive work without disrupting the workflows they already rely on.

Today, we’re excited to share the first step in that vision: a refreshed brand and website, three major product releases, and a preview of what’s coming next.

We have a simple goal with these releases: to eliminate the repetitive work that slows QA teams down without taking humans out of the loop. It's a hard trade-off, one that the industry has been failing to meet for years for the simple reason that it was driven by the wrong incentives. Focusing on deflection rates and cost cuts only to get more call-backs and re-hire people to fix what was promised but couldn't be automated. The right incentives are outcome-based. Truly completed and closed cases. Faster rep onboarding. Reliability, scalability, and predictability of chatbot performance.

Maintaining consistent evaluations across reviewers has always required constant manual calibration. As support volumes grow, that quickly becomes unsustainable.

Intryc's Auto QA Optimization continuously calibrates your AI evaluations in the background, helping teams maintain consistent scoring without manually reviewing every evaluation.

Finding the right data often means digging through tickets, filtering conversations, or building reports before you can answer even a simple question.

QA Assistant lets you ask questions in plain English and retrieve the insights you need in seconds, making it easier to investigate issues, identify trends, and make decisions faster.

Following up on QA shouldn't require spreadsheets, emails, or manual handoffs.

Action Center brings reviews, coaching, disputes, and follow-up tasks into one place, making it easy to assign work, track progress, and ensure nothing falls through the cracks.

Together, these features reduce the operational overhead of QA so teams can spend less time managing workflows and more time improving customer experience.

While today's releases make QA workflows faster, they're only the beginning. The next step is making them autonomous.

Over the past few months, we've been building Intryc AI Agents: autonomous AI that can execute entire QA workflows in the background, allowing teams to spend less time managing operations and more time improving customer experience.

Instead of manually pulling reports, assigning reviews, monitoring compliance, or following up on coaching, AI Agents execute these workflows end-to-end. From Auto QA to dispute pre-screening, coaching follow-ups, weekly QA digests, and evaluation coverage, Agents handle the repetitive operational work while your team focuses on improving customer experience.

Just as importantly, AI Agents don't replace your team's judgment. You decide what great support looks like through your scorecards, policies, and evaluation criteria. Agents simply execute the workflows consistently, at scale, and around the clock.

We're currently rolling out AI Agents in a limited closed beta and look forward to working closely with early customers as we shape the next generation of QA automation.

The features we've launched today and the AI Agents we're building toward reflect our broader vision about how AI should be used in enterprise software.

For us, success is measured by whether we help teams spend less time on operational overhead and more time improving the customer experience. Every product we build has the same goal: eliminate repetitive work, surface better insights, and give QA teams more time for the decisions that matter.

That philosophy extends beyond how we build products to how we build Intryc itself. We've consistently heard that customers want more visibility into where the platform is headed. Rather than treating product development as a series of isolated launches, we believe in building in public, sharing both what we've shipped and what's coming next.

It keeps us accountable, gives customers confidence in the direction we're taking, and yes, gives our competitors something to catch up on.

We're opening a limited number of AI Agent beta spots over the coming weeks.

If you're interested in early access and helping shape the future of QA, visit intryc.com or get in touch with our team.