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Emerging Surface

Advertising inside conversational AI answers.

The newest paid channel on the roadmap — emerging within conversational AI interfaces. We are building the measurement, placement, and coordination frameworks for it now, not after it matures.

80+
Awards
14
Markets
16+
Years
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Conversational Ad Engine

Ads inside the conversation.

gpt-monitor — ad placement tracker
tracking
$ omnicliq gpt --monitor
[prompt] Queries analyzed ✓ 500 tracked
[brand] Mentions detected ✓ 78% share
[rank] Visibility scored ✓ top 3
✓ Pipeline complete
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Engagement vs Display

First-mover discipline, not first-mover hype.

Paid placements inside conversational AI interfaces — product recommendations, sponsored answer integrations, and commerce flows within the conversational surface — are emerging. The surface is early enough that the measurement is incomplete, the placement formats are still evolving, and most agencies are either sitting this one out or over-promising based on pitch-deck scenarios.

Our position: early channels reward the advertisers that build the measurement before the spend scales. We monitor how product and service queries surface commercial content in the conversational answer layer for your category. We track the prompt patterns that generate branded recommendations — the AI-era equivalent of commercial-intent keyword research on traditional search. Where paid placements become available, we test with incrementality discipline.

Much of the work today is preparation. LLM visibility optimisation — the organic side — is where most of the brand exposure lives right now, and we coordinate paid and organic as one practice. When paid placements mature, the accounts already measuring and monitoring the surface are the ones that will compound on it.

What makes the difference.

01

LLM Citation Monitoring

Tracking how your brand and competitors appear in conversational AI responses across commercial query patterns. The brand exposure layer that exists today, regardless of whether paid placements are live in your category.

02

Prompt-Pattern Analysis

Understanding which prompt patterns trigger commercial recommendations and where paid opportunities will sit. The AI-era equivalent of classic commercial-intent keyword research — done with tooling we built for it.

03

Paid-Organic Coordination

Brand visibility in conversational AI answers is an organic SEO/GEO outcome today. We coordinate the organic work (content, schema, brand mentions across authoritative sources) with the paid surface as it emerges.

04

Incrementality From Day One

Measurement discipline that separates AI-surface impact from baseline brand search lift. Early-channel spend is easy to attribute incorrectly — we build the attribution correctly from the start.

05

Internal LLM Expertise

Our internal AI agent work gives us deep understanding of how conversational interfaces route user intent into commercial recommendations — knowledge we bring directly into the paid-placement strategy.

06

Iteration at LLM Pace

The surface evolves faster than any paid channel we have run. Our framework is built to match — weekly monitoring, rapid test cycles, and no quarterly strategy reviews that age out before they ship.

Building the approach.

01

Observe

Map how conversational AI currently answers commercial queries in your category. Track citation frequency, recommendation patterns, and the prompt contexts that generate branded mentions.

02

Optimise

Coordinate organic GEO work — content, schema, brand entity mentions — to strengthen your visibility in the LLM answer layer. Preparation for paid placements starts with organic presence.

03

Activate

Test paid placements as they become available in your market and category. Incrementality measurement built in. Creative and placement format adapted to the conversational interface.

04

Compound

Winning patterns replicated. Paid-organic coordination tightened. The LLM answer layer turned into a durable brand and performance advantage before competitors notice the channel exists.

Politikos Shop — flagship fashion department store

Politikos Shop.

+231%
Revenue
+225%
Transactions
+230%
Ad Spend
2
New Markets
Read full case study

Common questions.

Partially and evolving. Product recommendations and sponsored integrations have rolled out in specific categories and markets, with broader availability expected through 2026-2027. For most advertisers it is still emerging, but the LLM answer layer as a brand visibility surface is very real today — and that is where the work starts.
Traditional SEO optimises for classic search engine results — blue links, featured snippets, knowledge panels. LLM visibility (also called Generative Engine Optimisation, or GEO) optimises for how large language models summarise and cite brands in their responses. The tactics overlap but the evaluation criteria differ significantly.
Not if your category shows meaningful LLM-surface brand exposure today — which most consumer and B2B categories do. The organic visibility work (GEO) pays off now. The paid surface is additive on top of that foundation when it matures. Waiting until everything is live means starting from zero when competitors have compounded.
Some — structured data, entity clarity, and citation-worthy content formats tend to need adjustment. The changes overlap significantly with traditional technical SEO, so the work often fits into existing SEO roadmaps rather than becoming a separate project.
No — the LLM answer layer includes multiple engines across the industry. Our GEO practice covers all of them as one strategy, since the content and schema work that improves visibility in one LLM usually improves visibility across the others as well.

Ready to own the answer?

Let's talk about visibility across the LLM answer layer — as conversational AI becomes a primary discovery surface.

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