IgniteTech Brings AI That Fixes, Tests and Ships Around the Clock to Enterprise Software

Not an AI assistant. AI that takes the bug report, fixes it, tests it, ships it and tells the customer it is done, inside guardrails built on decades of software experience.

LONDON, Nov. 4, 2026 — IgniteTech, the AI-first enterprise software company, today detailed how it is bringing AI-run software development to enterprise customers, changing the relationship people have with their software. AI does not just assist developers. Working around the clock, it takes a customer's bug report, finds and fixes the cause, tests the fix, deploys the update and tells the customer it is done, all automatically and within guardrails the company has spent years building. CEO Eric Vaughan will present it today at the Financial Times Future of AI Summit in London.

"When software breaks, you wait," said Vaughan, who also leads Khoros and GFI Software. "You report the problem, and you are told it is in the backlog, the line of fixes waiting their turn. Backlog is a word this industry invented as a defense. This is the new age of software. If you report something broken today, it should be fixed by tomorrow morning."

Khoros will bring this approach to its Aurora AI and Iris® AI platforms first, so community and social media customers can report a problem or ask for a feature and see it built into the shared product.

Every step is checked. Before writing a fix, the system interviews the person who reported the problem until it understands it, then reproduces the problem itself. A fix goes live only after passing automated tests, and the system then repeats the customer's original steps on the live product to confirm it works before notifying them that the issue has been resolved. Feature requests follow the same path.

Two internal IgniteTech systems, used daily by dozens of employees, already fix and improve themselves this way: KnowledgeWell, an internal knowledge base, and Anvil, an account management system for one of the company's largest product programs.

Vaughan, a software developer by background, wrote both systems himself in under two months, on purpose. "You cannot hand a change this size to an organization as a slide deck," he said. "I needed to set the table: prove it in real production software, then build the harness that makes it repeatable. It is not my project anymore. It is how we build."

In early September, Vaughan spent four days on a Texas jury with his phone off. While he was out, Anvil kept fixing and improving itself, shipping four releases and seventeen changes requested by five colleagues.

That harness is what IgniteTech is taking across its portfolio. The obvious question is what keeps software that builds itself from drifting away from what it was meant to do. IgniteTech's answer is guardrails. Every product has a clear blueprint of its purpose and where it is headed, and every request is checked against that blueprint before anything is built. Requests that fit become features for every customer, and those that don't fit go to a person to decide. Each product stays one product for every customer, with no custom versions to maintain. People still control logins and access, payments, deleting data and anything sent outside the company.

"The guardrails are the product," said Vaughan. "Anyone can let AI write code. The hard part is the harness that decides what gets built, proves it works and keeps the product true to what it is for. We spent nearly four years building it on top of decades of building enterprise software the hard way."

"People have experienced software the same way for decades: roadmaps measured in quarters and bugs that age in a backlog," said Vaughan. "Anthropic and OpenAI have shown that AI can write most of their own code. We are bringing that to enterprise software, where customers feel it: software that works around the clock, fixes the reason a bug happened and not just the bug, and builds what you ask for. Five years from now, maybe sooner, people will expect all software to behave this way. We are at the front of it."

IgniteTech says the approach is still in the early phase. It does not always build a feature the way the requester intended, and it makes mistakes. "So do people," said Vaughan. "The difference is that this gets better every week."

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