Nano Interactive CTV data tool uses AI to fix programmatic fragmentation

The launch of Nano Screen Graph addresses the chronic lack of standardization in CTV metadata, which has historically forced advertisers to accept high rates of wasted spend and repetitive ad delivery. By using AI to bridge gaps between different publisher data sets, Nano Interactive provides a way for planners to achieve high-precision targeting without the privacy risks or technical limitations of legacy identifiers. This move signals a shift toward signal-based intelligence as the industry moves away from cookies and device IDs in fragmented environments. Watch for whether this metadata unification improves fill rates for smaller publishers who currently struggle to provide the granular data required by premium programmatic buyers.

Nano Interactive has been building toward the Screen Graph launch for several years, positioning itself as a privacy-first alternative to identifier-dependent targeting. The company processes 62 billion impressions across 100 markets daily, according to chief revenue officer Niall Moody, who has argued that short-lived intent signals often outperform long-term audience profiles, particularly during high-attention events like major sporting tournaments (thedrum.com). The broader strategic context is the industry's forced migration away from cookies and device IDs. In a January 2026 interview with ExchangeWire, Moody outlined Nano's philosophy that ID-free supply should be treated as a distinct, high-value channel rather than a fallback. He noted that many DSPs quietly down-weight bid requests when no user identifier is present, creating a structural undervaluation of inventory where consented IDs are scarce (exchangewire.com). Nano's recommendation is to run parallel line items — one optimized for ID-present traffic, one for ID-free — to preserve reach and clean measurement. The underlying technology relies on vectorisation, which converts content into mathematical representations of meaning so that systems can match ideas rather than keywords. In an August 2026 ExchangeWire post, Michaela Rairata, Nano's Client Growth Director, explained that the company analyzes approximately 4.9 billion signals daily across the open web and its screen graph, covering CTV titles, genres, synopses, and age ratings, all vectorized using the same model so campaign briefs and content are directly comparable (exchangewire.com). Independent data cited in that piece showed average uplifts of 50% on click-through rate, 80% on brand awareness, and 176% on ROI compared with cookie-based targeting. The Screen Graph launch also reflects a competitive dynamic in CTV ad tech. As logic moves to the sell side, crucial targeting decisions now happen in the auction's initial 10-millisecond window, before bid requests are sent, close to the impression and its richest signals. Nano's bet is that proximity to content metadata — rather than reliance on third-party identity graphs — surfaces more context and reduces waste, rewarding publishers who structure their supply properly, especially as continues to challenge the ecosystem.