Mirrors now uses a coordinated multi-agent AI framework to automate the full contextual campaign lifecycle. One agent converts brand briefs into cross-platform media plans ready for activation, while another enforces brand safety and contextual relevance. A real-time optimisation agent adjusts targeting and placements to boost engagement, viewability, and conversions. A continuous-analysis agent mines performance data to produce deeper insights and actionable recommendations. The agents communicate and reallocate investment toward high-performing contextual signals across YouTube, CTV, TikTok, Meta, and programmatic channels, guided by a client-first approach that prioritizes measurable advertiser impact.
One AI agent manages automated campaign setup, turning a brand's brief into a contextual media plan ready to activate across platforms like YouTube, CTV, TikTok, Meta, and programmatic channels. A second agent ensures ads are delivered in brand-safe and contextually relevant environments. A third agent actively optimises campaigns in real time, adjusting targeting and placements to improve metrics such as engagement, viewability, and conversions. A fourth continuously analyses performance data to generate deeper insights and actionable recommendations.
These agents don't operate in silos: the agents communicate and learn from one another. For example, if the system identifies that a certain contextual signal (such as a specific podcast, influencer, tutorial, or video category) is performing exceptionally well, the AI agents will automatically shift more investment to the winning context across all active platforms. This innovation is founded on Silverpush's client-first AI philosophy, which focuses not only on improving internal efficiency, but about delivering real, measurable impact for advertisers.
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