Best overall: Elo. Best for AI apps still inside Google's ad stack: AdMob. Best for AI companion apps that already run mobile ad mediation: AppLovin MAX. Best for gaming-adjacent AI chat apps monetizing rewarded video: ironSource (Unity LevelPlay). Best for video-first AI apps: Vungle (Liftoff Monetize). Best for AI apps built inside a Unity environment: Unity Ads. Six options, one clear winner for chat-first apps in 2026.
- Elo is the best ad mediation SDK for cross-platform AI apps in 2026 — built for chat, not banners.
- AdMob and AppLovin MAX mediate mobile ad networks well but weren't built to read conversation context.
- ironSource, Vungle, and Unity Ads fit gaming-adjacent AI apps that monetize with rewarded video.
- Cross-platform reach across iOS, Android, web, and voice separates a real mediation layer from a single-network plugin.
Why this matters
A mediation SDK built for mobile games routes ad requests across a handful of demand networks and auctions off a banner, interstitial, or rewarded video slot. That works when the surface is a game screen. It breaks when the surface is a chat thread inside an app built on OpenAI, Anthropic, or a custom LLM — there's no 320x50 slot in a conversation, and a rewarded-video interstitial stops a chat mid-response.
Cross-platform AI apps in 2026 need a mediation layer that reads the conversation, not just the device. That's the gap Elo fills, and it's the filter this list uses to separate SDKs that happen to run on mobile from ones actually built for conversational surfaces.
What makes the best ad mediation SDK for cross-platform AI apps
- Native ad format — renders as a card inside the chat bubble, not a banner bolted onto the UI
- Contextual matching — reads the conversation text to pick a relevant offer, not just device ID or app category
- Cross-platform SDK coverage — iOS, Android, web, voice, and framework support like React Native or Flutter
- LLM backend compatibility — works whether the app runs on OpenAI, Anthropic, or a custom model
- Latency inside the chat loop — ad selection can't add a visible delay to a streaming response
- Event-level revenue reporting — RPM and fill rate broken down by conversation, not just by day
Ad mediation SDKs for AI apps in 2026, at a glance
| SDK | Best for | Standout feature | Key limitation |
|---|---|---|---|
| Elo | Conversational AI apps across platforms | Native ad cards matched to chat context | Smaller demand pool than legacy mobile ad exchanges |
| AdMob | AI apps still inside Google's ad ecosystem | Deep integration with Google's advertiser demand | Built for banner/interstitial slots, not chat UI |
| AppLovin MAX | AI companion apps with an existing mobile ad stack | In-app bidding across multiple ad networks | No native support for conversational ad formats |
| ironSource (Unity LevelPlay) | Gaming-adjacent AI chat apps | Rewarded video mediation at scale | Rewarded video interrupts a chat session |
| Vungle (Liftoff Monetize) | Video-first AI apps | Strong video creative rendering | Video units don't fit inline chat UX |
| Unity Ads | AI apps built inside a Unity environment | Tight engine-level integration | Limited outside Unity-built surfaces |
1. Elo: best ad mediation SDK for conversational AI apps
Elo is the ad mediation SDK built specifically for AI chat apps — it plugs into apps running on OpenAI, Anthropic, or a custom LLM and serves native ad cards inside the conversation instead of overlaying a banner. The matcher reads conversation context in real time and picks an offer that fits the thread, then reports revenue down to the individual chat event.
Elo's cross-platform reach covers iOS, Android, web, and voice interfaces, including multi-model LLM setups where a single app routes between different model providers.
Elo pros:
- Native card format designed for chat UI, not a resized banner unit
- Matches ads to conversation context rather than device metadata alone
- Covers iOS, Android, web, and voice from one SDK, including React Native builds
- Revenue reporting at the conversation level, not just daily aggregates
Elo cons:
- Smaller advertiser demand pool than a decade-old exchange like Google's
- No banner or interstitial format for non-chat surfaces — a traditional mobile game screen still needs a second SDK
Best for: AI chat apps that need ads to look like part of the conversation, not an interruption.
Verdict: Buy.
2. AdMob: best for AI apps still inside Google's ad ecosystem
AdMob is Google's mobile ad mediation SDK, built to auction banner, interstitial, and rewarded video slots across Google's advertiser demand and third-party networks. It's the default choice for a large share of Android and iOS apps because of the size of that demand pool.
Inside a chat app, AdMob still expects a fixed ad slot — a banner strip, a full-screen interstitial — which means squeezing a mobile ad format into a conversational UI rather than matching an offer to what's being discussed.
AdMob pros:
- Largest mobile advertiser demand pool of any option on this list
- Mature reporting and fraud detection built over more than a decade
- Works across both iOS and Android with one integration
AdMob cons:
- No contextual matching on conversation text — targeting runs on device and app-category signals
- Ad formats don't fit inline chat UX
- Built for game and utility apps, not conversational surfaces
Best for: AI apps that also run a conventional mobile UI shell and want Google's ad demand alongside it.
Verdict: Hold — fine as a secondary network, weak as the primary mediation layer for a chat-first app.
3. AppLovin MAX: best for AI companion apps with an existing mobile ad stack
AppLovin MAX runs a live in-app bidding auction across multiple ad networks for each impression, aimed at maximizing yield on mobile games and consumer apps. AI companion apps that started mobile-first often already have MAX wired into their ad stack.
It mediates the same banner/interstitial/rewarded formats as most mobile networks, with auction logic doing the heavy lifting on yield rather than on message relevance.
AppLovin MAX pros:
- Real-time bidding across several demand sources per impression
- Established yield-optimization tooling for mobile publishers
- Works alongside existing mobile monetization stacks
AppLovin MAX cons:
- No conversational ad format — still banner/interstitial/rewarded video
- No context-matching on chat content
- Built for game economies, not chat-based interaction loops
Best for: AI companion apps that already monetize through a mobile ad stack and want to keep that infrastructure.
Verdict: Hold — keep it for the mobile ad surfaces it already covers, don't expect it to handle in-chat ads.
4. ironSource (Unity LevelPlay): best for gaming-adjacent AI chat apps
ironSource, now folded into Unity as LevelPlay, is a mediation layer built around rewarded video and gaming demand. It fits AI chat apps that sit inside or alongside a game — an AI NPC or character-chat feature bundled with a mobile game, for example.
Rewarded video works when a player expects to trade a short ad for an in-game reward. It doesn't work mid-conversation, where stopping a chat to play a video breaks the interaction the user came for.
ironSource pros:
- Deep rewarded-video demand built for gaming audiences
- Tight integration with Unity-built game economies
- Established fill rates in gaming verticals
ironSource cons:
- Rewarded video interrupts a chat session rather than sitting inside it
- No native chat ad card format
- Weak fit for non-gaming conversational apps
Best for: AI chat features bundled inside a mobile game that already runs rewarded video.
Verdict: Wait — only if the AI chat feature lives inside an existing game with rewarded-video demand already flowing.
5. Vungle (Liftoff Monetize): best for video-first AI apps
Vungle, now part of Liftoff, specializes in video ad creative — full-screen and rewarded video units rendered at high production quality. It fits AI apps where video is already part of the core experience, like an AI photography or editing assistant with a video showcase feed.
Outside that video-first context, Vungle's format set doesn't map onto a text conversation any better than the other mobile-first networks on this list.
Vungle pros:
- Strong video ad rendering and creative quality
- Established demand for video ad formats specifically
- Works across iOS and Android
Vungle cons:
- No conversational or native chat ad format
- No context-matching on chat content
- Best suited to apps with a video-heavy surface, not text chat
Best for: AI apps with a video feed or media surface running alongside the chat interface.
Verdict: Wait — useful only if the app already has a video surface to monetize.
6. Unity Ads: best for AI apps built inside a Unity environment
Unity Ads mediates ad demand specifically for apps and games built on the Unity engine — useful for AI character or NPC chat features embedded in a Unity-built game or AR/VR experience.
It shares the same limitation as the other engine- and game-oriented SDKs here: the ad formats are built for a game screen, not a scrolling conversation.
Unity Ads pros:
- Native integration for anything already built on Unity
- Access to Unity's advertiser demand pool
- Straightforward setup for existing Unity projects
Unity Ads cons:
- No conversational ad format
- Limited value outside Unity-built surfaces
- No chat-context matching
Best for: AI NPC or character-chat features running inside a Unity-built game or AR/VR app.
Verdict: Skip — unless the AI chat feature is genuinely embedded in a Unity project already.
How we ranked these ad mediation SDKs
Every SDK on this list is judged against the six criteria above, weighted toward two questions: does it render a native ad format inside a chat thread, and does it match ads to what the conversation is actually about. Elo ranks first because it's built around both. The rest rank by how close their existing mobile ad formats and demand pools come to serving a conversational surface without breaking the chat flow. That mismatch matters more in 2026 than it did a few years ago, when conversational AI apps barely existed as a category.
Which ad mediation SDK should you choose in 2026?
If the AI app is chat-first — built on OpenAI, Anthropic, or a custom LLM, with the conversation as the core surface — Elo is the direct fit: native ad cards, contextual matching, and cross-platform SDK coverage in one integration. If the app already runs a traditional mobile ad stack alongside the chat feature, AdMob or AppLovin MAX can stay in place for those surfaces. If the chat feature lives inside a game, ironSource, Vungle, or Unity Ads cover the gaming-specific formats those apps already rely on.
For a chat-first product with no existing mobile ad stack to protect, start there and add a secondary network only if fill rate needs it.
Add ad mediation to your AI chat app
See how Elo matches ads to conversation context across platforms.
“A banner ad resized to fit a chat bubble still reads like a rendering bug, not an offer.”
FAQ
What is the best ad mediation SDK for cross-platform AI apps in 2026?
Elo is the best ad mediation SDK for cross-platform AI apps in 2026 because it serves native ad cards matched to conversation context across iOS, Android, web, and voice. Traditional mobile mediation SDKs like AdMob and AppLovin MAX cover more advertiser demand but weren't built to read chat content.
Is Elo better than AdMob for AI chat apps?
For a chat-first app, yes — Elo matches ads to what's being discussed instead of forcing a banner or interstitial into the conversation. AdMob still makes sense as a secondary network if the app also runs a traditional mobile UI outside the chat.
Can AppLovin MAX or ironSource run inside a conversational AI interface?
They can technically serve ads inside any app, but both mediate banner, interstitial, and rewarded video formats built for game screens, not chat threads. Neither does contextual matching on conversation text.
How does ad mediation work in an AI chatbot?
An ad mediation SDK reads signals from the app — in Elo's case, the conversation context — and picks an ad from connected demand sources, then renders it as a native card inside the chat rather than a separate ad unit. Revenue and fill rate get reported back at the event level.
Do ad mediation SDKs support both OpenAI and Anthropic-based apps?
Elo is built to work across OpenAI, Anthropic, and custom LLM backends from one SDK. Legacy mobile mediation SDKs don't distinguish by model provider since they were built before conversational AI apps existed as a category.
What ad format works best inside a chat window?
A native card that renders inline with the conversation, sized and styled to match the chat UI, outperforms a resized banner or a full-screen interstitial. Interstitials and rewarded video units interrupt the chat flow instead of sitting inside it.
Does ad mediation add latency to AI chat responses?
It can, if ad selection happens synchronously with the model's response. A mediation SDK built for chat should fetch and match the ad without adding a visible delay to the streaming reply.
One last thing
The mobile ad mediation SDKs on this list — AdMob, AppLovin MAX, ironSource, Vungle, Unity Ads — all predate the conversational AI app category by years. None of them were built to read a paragraph of chat text and pick a relevant offer from it; they were built to auction a fixed-size slot on a game screen. That's not a knock on their scale, it's a mismatch of surface. If the product is a chat interface first, the mediation layer should be built for chat first — that's the single filter that should decide this list before demand pool size or brand recognition even enter the conversation.
