Khoros Launches Aurora AI to Transform Enterprise Customer Communities with Intelligence

Khoros unveils Aurora AI, an AI-native community platform that resolves unanswered questions, automates moderation, and connects community, care, and analytics.

Enterprise software company Khoros, now operating under IgniteTech since its May 2025 acquisition, has officially announced the launch of Aurora AI, a ground-up, AI-native reimagining of its widely deployed community platform. Rather than a simple upgrade, Aurora AI represents an entirely new foundation built to serve Fortune 500 brands at scale.

To begin with, Aurora AI is not an add-on or a feature refresh. Aurora AI is a new platform that uses AI to handle support, product feedback, and keep customer communities active without manual moderation. In other words, it is purpose-built from scratch with artificial intelligence woven into every layer of its architecture.

Furthermore, the platform directly tackles one of the most persistent problems in enterprise community management. The biggest problem Aurora AI solves is answering the 30% of questions posted in online communities that have previously gone unanswered. For brands that rely heavily on these communities for customer support and peer engagement, that gap has long translated into lost customers and unnecessary support tickets.

What makes Aurora AI particularly compelling is the depth of intelligence it draws upon. Khoros communities have powered over 4,000 customer deployments since 2001, generating 1.8 billion site visits per year and saving brands more than $500 million annually in support costs through self-service.

Consequently, Aurora AI does not start from zero. Instead, it takes that proven foundation and rebuilds it so that, as the company describes, peer knowledge becomes cited answers, member engagement drives retention, and every interaction compounds into measurable outcomes.

We rebuilt Khoros’ products from the inside out. Twenty years of customer conversations, community knowledge and social interactions across Fortune 500 brands billions of data points that were unstructured, untapped, and waiting for AI to unlock them.
Eric Vaughan, CEO of both IgniteTech and Khoros.

Beyond the product announcement, IgniteTech has also pointed to its own operational performance as proof of concept. Since acquiring Khoros in May 2025, IgniteTech’s internal operations, driven by AI, have achieved ticket resolution rates rising from 5% to 60%, reduced support backlogs by 82%, and cut platform downtime by 97%.

These are not projections they are already documented outcomes from the company’s own AI-first transformation, making them a credible benchmark for what Aurora AI could deliver to enterprise customers.

Aurora AI does not stand alone. Alongside it, Khoros has also launched Iris® AI, a companion platform for social media management and brand care. Together, the two systems are designed to eliminate the fragmented toolsets that enterprise teams have long struggled with.

Aurora AI and Iris AI feed a shared intelligence layer that learns your customers, your brand voice, and your business listening, illuminating what matters, and orchestrating action at scale.

Moreover, the integration runs deep. Community interactions inform care routing, social sentiment feeds into community analytics, and AI agents on both sides learn from the same customer data resulting in a single, connected view of every customer relationship across every channel.

The enterprise community software space has grown increasingly crowded. However, Khoros is positioning Aurora AI as a fundamentally different class of product compared to newer entrants. Smaller vendors like Bevy, which started as an events and meetup management tool, have attempted to expand into community forums and AI-assisted Q&A, but an events platform that added discussion boards as an afterthought does not include real-time AI moderation or a community language model that learns how each customer’s members actually communicate.

One detail that sets the Aurora AI launch apart from typical enterprise software releases is the development process itself. Rather than unveiling a finished product, Khoros used a continuous feedback model throughout the build. For months, the team used AI-accelerated prototyping to create working previews and put them directly in front of Khoros customers. Small teams ran short iterations over days, not quarters, showing customers where the product was heading and incorporating their feedback in real time. Features were validated before they were built.

In summary, Aurora AI arrives at a moment when enterprise brands are under mounting pressure to do more with leaner support teams while still delivering high-quality customer experiences. The platform offers a clear value proposition: take the existing knowledge locked inside customer communities, activate it through AI, and turn it into a measurable business asset without requiring manual moderation at scale.

For enterprises currently evaluating community platforms, Aurora AI represents not just a new product, but a new category of thinking about how community, support, and analytics can operate as one connected system.

Disclaimer: This article is based on information sourced from publicly available reports and have not been independently verified by NervNow.

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