100K+ Followers, 15M+ Views, and 100K+ Users in Under 6 Months

Solvearn needed rapid distribution and user growth, but consistent content output was a bottleneck. Manually finding viral formats, extracting patterns, and turning them into scripts was too slow to post at the volume required to win attention. They also needed smarter user-to-user matching so the product experience actually retained the audience they were driving in.

Deep Loom built multiple integrated systems that worked together:

• Multi-dimensional vector search engine across 6 profile dimensions, scaling to 100K+ users
• Conversational voice AI onboarding agent integrating speech recognition and voice synthesis, increasing profile completion by 30% and reducing sign-up drop-off by 22%
• Agentic AI landing page generation pipeline as the company's first revenue-generating feature, managing 35+ dynamic component combinations while maintaining brand voice consistency
• Short-form content research + scripting engine that continuously identified viral Instagram reels, extracted winning patterns, and generated ready-to-record scripts
• Recommendation pipeline using vector search to improve AI matching inside the platform

The systems transformed Solvearn's growth trajectory, scaling to 100K+ users in under 6 months and reaching €600K valuation. The multi-dimensional vector search engine across 6 profile dimensions enabled seamless user matching at scale. The conversational voice AI onboarding agent increased profile completion by 30% and reduced sign-up drop-off by 22%, significantly improving user acquisition. The agentic AI landing page generation became the company's first revenue-generating feature, managing 35+ dynamic component combinations. By automating content research and script generation, they could post at the volume needed to capture attention, driving 100K+ followers and 15M+ views while the intelligent matching systems improved retention and engagement.