PALO ALTO, CALIF. -- Retail media has become the fastest-growing profit line in grocery, yet the billions of dollars CPG advertisers invest in it every year flow through a system where media buyers and merchants never see the same data. Merchants plan assortments, negotiate trade spend, and execute resets with no visibility into which CPG media investments are driving category velocity, while CPG advertisers renew or walk based on incrementality proof that most retailers cannot provide. To solve for this, SymphonyAI, a global leader in Vertical AI, today announced the general availability of CINDE Retail Media Intelligence (RMI), an AI platform that connects merchandising, media, and shopper intelligence into a single closed-loop system, giving retailers and CPG partners shared visibility into how every media dollar moves category turns, trade spend ROI, and gross margin across every reset cycle, joint business planning negotiation, and campaign flight.

CINDE RMI is not a retail media network platform. It is the intelligence layer that makes every RMN platform smarter. It plugs into existing retail media stacks rather than replacing them, and integrates with leading third-party measurement partners for CPG-credible incrementality validation. For mid-to-large grocers with existing or nascent retail media programs, this means accessing AI-driven incrementality intelligence, precision audience segmentation, and media-to-shelf attribution without the cost and complexity of a full platform migration. For CPG advertisers, it means finally seeing proof that their media investment drives in-store category performance, which is the single most cited barrier to growing retail media spend.

Six Capabilities

CINDE RMI delivers six integrated capabilities, each built on SymphonyAI's existing CINDE retail AI infrastructure:

·Audience Intelligence for Retail Media: First-party scan data and shopper behavior converted into precision audience segments, giving CPG partners the targeting intelligence they need to drive category velocity and basket attachment, and giving merchants visibility into which shopper segments are responding to media investment.
·Retail Media Campaign Measurement: Closed-loop campaign measurement using causal inference and adstock modeling to produce iROAS, ROAS, new-to-brand, new-to-category, and lifetime value. For merchants, this converts trade spend negotiations from assumptions about promotional lift into verified, auditable category performance data.
·CPG Investment Advisor: Portfolio-level intelligence that identifies CPG spend gaps across the category portfolio, surfaces upsell opportunities aligned to the reset calendar, and converts category planning data into incremental advertiser investment, giving merchants a clear view of which vendor partnerships are underfunding categories and what the trade spend opportunity is.
·In-Store Attribution — Computer Vision: Computer vision deployed at store level verifies that in-store media placements ran as planned, closing the promotional compliance gap between campaign booking and physical shelf execution, and feeding verified execution data back into the next promotional window and JBP review.
·Retail Media Agentic Campaign Engine: AI agents that monitor campaigns continuously, auto-remediate underperforming placements and audience segments, and prepare JBP briefings autonomously, reducing manual campaign management work for both media and category teams.
·Merchandising and Media Closed Loop: A shared data model connecting joint business planning and category management directly to retail media campaign planning and performance. Assortment decisions, planogram resets, and trade spend negotiations are made with full visibility into what CPG media investment is doing to category turns and gross margin, within the same cycle rather than the next one.

Market Context

Retail media has grown into one of the highest-margin revenue streams available to grocers, yet most retailers manage it in isolation from category management. Merchants planning resets and negotiating trade spend have no visibility into which CPG media investments are driving category velocity, comp store sales, or gross margin per foot. CPG advertisers increasingly demand proof of incrementality, not just impressions, and the inability to connect media spend to in-store category performance is the single most cited barrier to growing retail media investment.

“Retail media is the fastest-growing revenue line for grocers, but most retailers are managing it blind. There is no connection between what the merchant knows about the category and what the media buyer is selling to CPG partners,” said Manish Choudhary, President of Retail, SymphonyAI. “CINDE RMI closes that loop. When a CPG advertiser can see exactly how their media investment connects to in-store category performance, verified by computer vision and measured by causal incrementality, the conversation shifts from spend justification to investment growth. That is the unlock we are bringing to market.”

To request a demonstration or connect with the SymphonyAI team at NRF APAC, visit booth 1514. SymphonyAI will also be participating in two sessions at the show:

BIG Ideas Session — Wednesday, June 3, 2:20 - 2:50pm, Level 1, EBI Stage 1: Surachai Hirannitichai, Group Chief Digital Technology Officer, Big C Supercenter, joins Paul Howe, Managing Director, ReadyMS Thailand, and Manish Choudhary, President of Retail, SymphonyAI, to discuss the retailer pain points driving technology transformation at Big C — a live case study in how one of Asia-Pacific's largest grocery operators is rethinking its digital infrastructure.

Expo Tour — Engaging Customers with Generative AI: Retailers will review the technology road map of generative AI to provide insights on generating value including higher revenue, streamlined efficiencies. Retailers attending NRF APAC can add this guided expo tour to their registration package.