Dyvo.ai

Launch Fast in a Booming AI Market

When Dyvo.ai started, AI avatar apps were appearing almost daily. Delays could mean early demand and visibility loss. The team needed to validate the idea quickly and release a polished product before the market became overcrowded.

Solution

We used a lean product approach with no-code tools, a focused scope, and fast decision-making. This helped the team move from idea to launch in less than a month while keeping quality high on both iOS and Android.

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Deliver AI Results Users Would Actually Share

Generating avatars was not enough. Images needed to look attractive, recognizable, and worth posting online. Poor likeness, visual artifacts, or weak styles could reduce trust and hurt retention after the first use.

Solution

We ran multiple experiments with models, prompts, and generation settings to improve output quality. This helped produce avatars that looked closer to users, reduced common AI issues, and created stronger reasons to return.

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Control GPU Costs While Scaling Demand

Avatar generation depends on GPU power, and user growth can quickly increase infrastructure costs. Buying hardware early was expensive and risky, especially for a new product still testing demand and conversion potential.

Solution

Instead of purchasing GPUs, we used on-demand cloud infrastructure through Runpod.io. This allowed the team to scale processing capacity when needed, reduce idle costs, and keep the business model more efficient.

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Build Trust Around Personal Photo Uploads

Users had to upload multiple selfies before receiving results. That creates hesitation, especially with AI products using personal images. Without trust, many users would leave before completing onboarding or making purchases.

Solution

We designed a clean onboarding flow and positioned privacy as a core product value. Clear UX, smooth upload steps, and a privacy-focused experience helped reduce friction and improve confidence in the product.