Free
$0Free plan available.
Sesame Labs offers Community Hub, an AI-powered platform that automates community marketing through gamification. It rewards community members for their activity on social media, YouTube, and Discord, aiming to improve marketing KPIs, boost community engagement, and save time. They are also building MadMen AI, which creates and manages high-performing ad campaigns by identifying characteristics of top-performing ads and producing ad creatives for top-quartile performance.
Use Community Hub to reward community members for their online activity. Use MadMen AI to create and manage high-performing ad campaigns.
Community Hub is an AI-powered platform that automates community marketing through gamification, rewarding members for their activity on social media, YouTube, and Discord.
MadMen AI creates and manages high-performing ad campaigns by identifying the characteristics of top-performing ads and producing ad creatives designed for top-quartile performance.
MadMen AI supports Instagram, Facebook, Google, and TikTok.
Free plan available.
Use these comparison pages to understand the trade-offs between the models most relevant to Sesame Labs.
Compare Gemini 1.0 Pro Deprecated and Gemini 1.5 Flash Vision Deprecated across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus general-purpose AI workloads.
Compare Gemini 1.5 Pro Vision Deprecated and Gemini 1.0 Pro Deprecated across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for general-purpose AI workloads versus long-context workloads.
Compare Gemini 1.0 Pro Vision Deprecated and Gemini 1.5 Flash Vision Deprecated across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for general-purpose AI workloads versus general-purpose AI workloads.
Compare Gemini 1.5 Pro Vision Deprecated and Gemini 1.0 Pro Vision Deprecated across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for general-purpose AI workloads versus general-purpose AI workloads.
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