ResultsThatSpeakForThemselves

Investment research was slow, fragmented, and repetitive—investors spent hours manually researching startups across scattered sources, often duplicating efforts and missing key insights.

Velais developed an AI Startup Screening Agent that automates research across multiple data sources, enables investors to interact with the data via natural language, and stores insights intelligently to prevent redundancy.

• 75% reduction in research time per startup
• 2X faster deal flow pipeline
• 40% increase in relevant deal discoveries
• 70% fewer repetitive research tasks
• Higher confidence in investment decisions

Escalating AWS cloud costs—exceeding $36,000/month—were threatening the sustainability of the AdTech department due to inefficient architecture, lack of cost visibility, and over-provisioned resources.

Velais applied a 'CTO as a Service' model to redesign the infrastructure with a CFO mindset: we built a cost-aligned cash flow model, mapped inefficiencies, and led a full migration to Microsoft Azure with a refactored, cost-optimized architecture.

• 83% reduction in cloud costs (from $36K to $6K/month)
• Transformed a cost center into a profitable unit
• Deployed a scalable, leaner architecture on Azure
• Aligned cloud infrastructure with financial sustainability
• Upskilled internal engineering on cost-aware cloud practices

The client's keyword-based search system was rigid, slow, and unable to deliver relevant results due to its reliance on exact matches and lack of semantic understanding.

Velais implemented a GenAI-powered semantic search system using enriched embeddings, a custom AI model, and Vector Search to enable intuitive, intent-driven company discovery.

• 5X improvement in search accuracy
• 60% faster search experience
• 90% of searches returned relevant results on first attempt
• 20% more companies discovered through semantic matching
• Fully automated company data enrichment pipeline