For security teams weighing build vs buy for their AI SOC, the prototype is the easy part. Running it reliably in production, across every alert type with different context, takes far longer.
In this fireside chat, Ahmed Achchak, CEO and Co-founder and Corentin Le Reun, VP and GM Americas at Qevlar AI, share what they are hearing in the field from enterprises and MSSPs that chose to build. The same obstacles come up in conversation after conversation: getting analysts to trust AI verdicts enough to move from validation into production, closing alerts that need context the system does not have, depending on one or two engineers to keep the build running, absorbing model changes and upkeep that never ends, and scaling past a handful of use cases.
Drawing on those conversations across Europe and the US, they talk through where and why in-house builds stall, what each obstacle costs in time, people and budget, and what teams decided to do once they hit those limits.
