PH Deck

Users previously relied on traditional image editing software which is slow with high latency and often complex to use for achieving professional results

Users face challenges in achieving character consistency, multi-image fusion, and precise editing with natural language in image generation, leading to fragmented outputs and inefficient workflows.

Users struggle with complex and time-consuming photo editing tools that require technical expertise, leading to inefficient workflows and limited creative flexibility when transforming images.

Users need to create and edit images using multiple tools, which can be time-consuming and inefficient. Traditional methods often lack integration of advanced features like photo editing and image fusion in one platform, requiring separate apps or manual adjustments.

Users previously relied on older versions of Google's AI models (e.g., Gemini Lite) with higher latency and lower quality for handling large-context AI tasks, limiting efficiency and scalability.

Users relying on previous AI models face slow processing speeds and high operational costs, limiting scalability and real-time application potential.

Users previously relied on traditional or basic AI image editors with slow processing speeds and limited precision in localized adjustments, leading to inefficient workflows and compromised creative control.

Users rely on traditional image editing software requiring technical skills leading to a high learning curve and inefficiency

Users struggle to create high-quality, consistent AI-generated images efficiently, facing time-consuming manual adjustments and limited character consistency across multiple images with traditional tools.

Users need to manually edit images using traditional software like Photoshop or other tools to create variations, which is time-consuming and requires technical expertise.