Top AI Optimization Tools for Programmatic Advertising

1) Scalable (Vibe Marketing + Ad Spend Optimization)

Overview:
Scalable is the only platform that operationalizes vibe marketing for programmatic advertising. You describe how the brand should feel and what you want to happen. Scalable compiles that brief into creative tests, placements, and budget moves, and it keeps learning from results. This prompt-driven workflow helps teams pivot quickly to market changes while staying aligned with search intent and sales outcomes.

Key Features:

• Vibe Brief: Write what you want the brand to project, and include examples you like or dislike.

• Vibe Compiler: Translates your brief into channel-specific experiments for your approval, including creative, copy, and audiences.

• Adaptive Budget Orchestration: Reallocates spend toward combinations of vibe, audience, and creative that drive your KPI, within ROAS or CPA guardrails.

• Search-intent alignment: Ensures messaging and positioning track with evolving queries and demand patterns.

Pros:
Plain-English control, fast iteration, strong spend efficiency from intent alignment, and brand guardrails so output stays on message.

Cons:
Best for teams that want a prompt-driven workflow. It is not intended to replace every highly bespoke feature in an enterprise DSP tech stack.

Pricing:
Simple onboarding and guided pilots. Contact Scalable for current plans.

2) Google Display & Video 360 (DV360)

Overview:
Enterprise DSP within Google Marketing Platform, well suited for teams that want tight integration with Google measurement and media.

Key Features:
Automated bid strategies that adapt to auction signals, plus Custom Bidding where you can upload Python-based scripts to value impressions using your own KPIs. API support allows script upload, verification, and assignment. 

Pros:
Deep integrations with Google data and formats, mature auto-bidding options.

Cons:
Advanced features can require specialist expertise and developer time for custom logic. The scripting model generally expects Python familiarity. 

Pricing:
Contracted through Google or certified partners; pricing is not publicly listed.

3) The Trade Desk (Kokai with Koa AI)

Overview:
Independent, omnichannel DSP used by many agencies and large brands, notable for identity and CTV strength.

Key Features:
Koa AI supports optimization and recommendations, and Kokai provides a modern interface and workflows intended to speed up decision-making. 

Pros:
Powerful AI-assisted recommendations, broad open-internet reach, strong partner ecosystem.

Cons:
Enterprise-grade depth can require expertise to unlock all value.

Pricing:
Custom, typically via direct contract or approved partners.

4) Amazon DSP

Overview:
A strong choice when Amazon’s retail and streaming signals matter, including ecommerce, CPG, and entertainment.

Key Features:
Performance+ uses Amazon first-party signals and machine learning to automate setup, audience creation, and goal-based optimization. Independent coverage notes its performance-oriented design for non-endemic advertisers.

Pros:
Unique commerce and media data, strong CTV and retail media options.

Cons:
Walled-garden constraints, and suitability depends on whether your audience engages within Amazon surfaces.

Pricing:
Custom, often with spend minimums via Amazon or approved partners.

5) StackAdapt

Overview:
Self-serve DSP with user-friendly workflows, popular with lean teams that want strong contextual controls.

Key Features:
Page Context AI maps phrases and keywords to page-level context for precise placement and cookieless reach. Third-party walkthroughs describe practical setup and use cases.

Pros:
Clean UI, quick deployment of contextual strategies, good education resources.

Cons:
A contextual focus may limit access to commerce or identity-rich datasets compared with larger ecosystems.

Pricing:
Custom, typically through StackAdapt direct.

6) Quantcast Platform

Overview:
Open-internet platform driven by its Ara machine learning engine and a large, real-time behavioral dataset.

Key Features:
Ara delivers audience insights and activation that update as behavior changes, providing analytics and planning alongside buying. Recent docs emphasize real-time insights at scale. 

Pros:
Helpful for discovery and mid-funnel growth on the open web; fast insights.

Cons:
Performance can vary by vertical and data availability, so testing and tuning are important.

Pricing:
Custom, via Quantcast or partners.

7) Adobe Advertising DSP

Overview:
Best for organizations already using Adobe Experience Cloud and seeking unified data and activation.

Key Features:
Optimization is powered by Adobe Sensei, with documentation explaining how the engine optimizes packages and pacing. The product site highlights centralized buying and analytics across channels. 

Pros:
Deep integrations with Adobe data and analytics, cross-channel orchestration.

Cons:
Enterprise complexity and cost, typically better for larger teams with established Adobe stacks.

Pricing:
Custom, usually part of broader Adobe contracts.

8) Yahoo DSP

Overview:
Omnichannel DSP with identity and privacy-forward targeting options.

Key Features:
Yahoo ConnectID and Next-Gen Solutions enable authenticated and ID-less targeting. In 2025, Yahoo added Comscore AI-powered ID-free audiences into its DSP. 

Pros:
Useful in cookieless environments, solid CTV access, expanding identity partnerships.

Cons:
Ecosystem breadth can be smaller than Google or The Trade Desk in some regions; features vary by market.

Pricing:Custom, through Yahoo or reseller partners.