# AiOO and TeknaLab.ai launch first AI agent platform for programmatic DOOH and in-store retail media buying

*Physical-world media just became machine-buyable, opening automated placement decisions for shelf-edge screens and retail endcaps.*

By **Jenny Huang Goodman MPA MSc MHSA, Principal** — The Stash Edge, Hako Shikin LLC.
Published 2026-06-27.

Canonical: https://www.pops4.com/stash/articles/aioo-and-teknalabai-2026-06-27t00-7
Subject: AiOO and TeknaLab.ai
Tags: retail media, dooh, programmatic, ai agents, in-store advertising, physical product

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AiOO and TeknaLab.ai announced in June 2026 the first platform where autonomous AI agents can execute purchases of digital out-of-home (DOOH) and in-store retail media without human intervention, according to a press release issued from Cannes. The system allows software agents to buy screen time on shelf-edge displays, endcap monitors, and in-aisle digital fixtures the same way programmatic systems already buy banner ads online.

The platform connects retail media inventory — screens inside grocery stores, convenience shops, and big-box chains — to AI decision engines that evaluate placement, timing, and audience fit in real time. An agent receives a media brief, queries available inventory across participating retail networks, evaluates cost per impression against performance benchmarks, and completes the transaction autonomously. The entire cycle, from brief to booked screen time, can occur in seconds.

This works because the platform standardizes what has historically been a fragmented, relationship-driven market. Retail media buying has required direct negotiations with individual chains, each with proprietary systems and rate cards. AiOO's infrastructure translates that complexity into machine-readable endpoints. An AI agent sees a unified inventory feed, standard pricing models, and APIs built for programmatic execution. The agent optimizes the same way it would for digital display — but the output is a **15-second loop** on a cooler door at a Walmart in Tulsa or a checkout screen in a Portland Whole Foods.

The mechanism matters for physical-product brands because it collapses decision latency. A brand launching a new energy drink can now deploy an agent that monitors local weather APIs, identifies zip codes experiencing heat spikes, and buys in-store screen time in those markets within the same hour. The agent reallocates budget from underperforming placements to high-traffic stores without waiting for a human media planner to log in. Speed and granularity previously available only to e-commerce display buyers now apply to the physical retail aisle.

A small brand runs this play by starting with a narrow test: one metro, one retail chain, one week. Write a creative brief — product, audience, desired outcome — and feed it to an AI agent built on an orchestration layer like LangChain or a no-code agent builder. The agent connects to AiOO's API, queries inventory for stores matching your geographic and foot-traffic criteria, and buys screen time in **50 to 200 locations** for a few hundred dollars. You supply a **15-second video asset** (shot on an iPhone, edited in CapCut, exported at broadcast resolution). The agent uploads the creative, schedules the run, and reports back impressions and cost per screen. Budget cap the test at **$500**. Measure against a control metro where you run no screens. If attributed lift justifies the spend, expand by adding more agents, more metros, or more retail chains.

The broader shift is that physical-world media is no longer a phone call and a rate card. It's an API. Brands that learn to brief agents instead of agencies will move faster, test cheaper, and iterate on creative and placement in hours instead of quarters. The next unlock will be dynamic creative — agents that swap the video asset based on real-time triggers like inventory levels or competitor promotions detected via shelf-monitoring cameras. That layer is already being built.

## The takeaway

AI agents can now buy in-store screens programmatically, giving small brands the speed and targeting granularity previously reserved for digital display.

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## Publisher

**Hako Shikin LLC** — Virginia Beach, Virginia. Founded 1997. ASI 217876 · DUNS 18-204-6339.
Principal and author: **Jenny Huang Goodman MPA MSc MHSA**.

- Author: https://www.huanggoodman.com/about
- LLM context: https://www.pops4.com/stash/llms.txt
- MCP endpoint, for AI agents: https://mcp.pops4.com/mcp
- Client dashboard: https://dashboard.pops4.com/
- Catalogue: 70,000+ products, 200+ brands