Predictive media plan
The media plan gives you a transversal view of your media plan before the launch of your campaign. You'll find performance predictions associated with spend estimates, with an ultra-granular level of detail that can be viewed by using interactive filters.
Making the right media choices
Automated
Once you've chosen your objectives and your parameters, the collection and representation of the media plan are generated automatically.
Accurate
Estimate the potential of your next media plan with performance predictions generated from Machine Learning.
Aggregated
Your entire device is displayed with several Ad Platforms at a time.
Forecast performance indicators
Find the indicators you want, whatever your campaign objectives.
Dynamic filtering
Our media plans feature a wide range of views, enabling isolated analyses of your plan's predictions.
Want help?
You can get assisted with Generative AI for Media Planning
Moving from "Bidding Blindly" to "Designing Winning Strategies"
The Big Idea: We are introducing ASGAR, the first Generative AI engine capable of designing complex, multi-feature advertising strategies before a single dollar is spent.
The Multi-Billion Dollar Problem
• The "Black Box" of Pre-Launch: Current AdTech optimizes after the campaign starts bidding. There is almost zero optimization in the planning phase.
• Combinatorial Explosion: A typical ad campaign has over 678 million possible combinations of settings (Device *\times* Geo *\times* Browser *\times* Time, etc.).
• Human Limitations: No human media trader can calculate the synergy between 10+ variables simultaneously.
• Existing AI Fails: Standard Recommenders (Matrix Factorization) can't handle the complexity. Standard Generative AI (LLMs) hallucinates invalid configurations and are suboptimal / not data driven.
The Solution – ASGAR
A "Strategy-First" Generative Engine. Unlike traditional systems that just rank existing lists, our engine builds optimal strategies from scratch.
• Bundle-Centric: It understands that an ad strategy is a "bundle" of interacting features. It knows that Mobile works differently with Video than it does with Banner Ads.
• Oracle-Guided: The system is trained against a "Performance Estimator" (a frozen Oracle) ensuring every generated strategy is mathematically predicted to perform.
• Zero-Spend Optimization: We optimize the plan virtually, reducing the "learning phase" budget waste that plagues the industry.
The Technological Moat (Why We Win)
Robust, Flexible, & Proprietary Architecture
• Deep Interaction Awareness: Unlike Multi-Armed Bandits (which treat features separately), our attention mechanisms map the hidden synergies between all campaign variables..
• The "Aligner" Safety Net: A proprietary neural component that detects "sensitivity." It prevents the model from making small, subtle changes that would crash campaign performance—solving the "near-miss" problem standard AI suffers from.
• Vector Quantization (VQ): Solves the "echo chamber" problem. While other AIs repeat the same safe answers, VQ forces our system to remain creative and diverse, uncovering hidden pockets of inventory.
Business Flexibility & User Control
AI as a Co-Pilot, Not a Black Box.
• "Token-Driven" Suggestion: We invented a mechanism where clients can input soft preferences (e.g., "Try to favor iOS users"). The AI listens but retains the autonomy to override if the data proves it’s a bad idea.
• Risk Toggle: One-click switching between Conservative Mode (proven, steady ROI) and Exploratory Mode (high-risk, high-reward discovery) without retraining the model.
Future-Proof & Scalable
Ready for the LLM Era
• LLM-Native Architecture: Built on Transformers (just like GPT-4). We can plug standard LLMs into our front end to let clients "chat" with their media plans, while our engine handles the mathematical heavy lifting..
• Infinite Extensibility: The architecture is agnostic to input types. We can instantly integrate Real-Time Trends, Seasonality, or competitor data as new context features without rebuilding the core engine.
The Technological Moat
Why Legacy Methods Fail at Scale. Existing solutions break under the complexity of modern advertising. ASGAR thrives on it.
