Pencil

Pencil is an AI ad-generation platform that creates on-brand ads at scale and predicts their performance before they run.

Overview

Pencil combines generative creative with performance prediction. Brands upload their assets, guidelines, and past campaign data, and Pencil generates ad variations — video and static — matched to brand identity and platform conventions. What separates it from generic image generators is the prediction layer: models trained on ad performance data estimate which creatives will outperform before budget is spent, and results feed back to sharpen future generation. The platform supports the major social and display channels, and its workflows suit both agencies producing at volume and in-house teams iterating quickly. For performance marketers tired of the creative-testing bottleneck, Pencil turns ad production into a systematic, measurable pipeline. Because generated creatives are grounded in the brand’s own successful past ads, output quality tracks the brand’s real aesthetic rather than a model’s generic interpretation of instructions. Brand governance controls keep generated output consistent with guidelines across large creative volumes, and collaboration features let marketing teams review, annotate, and approve variants inside their existing campaign workflows.

Key Features

• On-brand video and static ad generation at scale
• Performance prediction for creatives before media spend
• Learning loops that improve generation from campaign results
• Multi-channel output for major social and display platforms
• Brand grounding from past successful campaign assets
• Feedback loops connecting realized performance back into generation quality

Pricing

Pencil offers a free trial for initial creative generation. Paid plans scale by generation volume and workspace features, with enterprise agreements covering brand governance, integrations, and dedicated support.

Who Is It For

Performance marketing teams and agencies producing high volumes of ad creative who want to test more variants with less production effort and pre-spend prediction. It fits brands where creative volume is the binding constraint on testing velocity and campaign learning speed.