Research
AI market research & insights
Original research from a team building and scaling AI products across 3 markets. We publish what we learn — market data, technical architectures, and business strategies backed by first-party evidence.
Get research reports as they publish
Early access to all reports, data sets, and technical deep-dives.
The State of Consumer AI Applications (2026)
Market sizing, revenue models, and growth vectors for consumer AI apps across iOS, Android, and web. Based on public data and our first-party metrics from 7 live products.
AI Agent Architectures: From Single-Turn to Persistent Memory
A technical comparison of agent architectures — stateless, session-based, and persistent memory agents. How we implement cross-product learning at Virtual Minds.
Building AI Products with Claude: Lessons from 7 Shipping Apps
Practical guide to using Claude in production — prompt engineering, tool use, caching strategies, and cost optimization from real-world deployment.
AI App Revenue Models: Subscription vs. Usage vs. Hybrid
Analysis of monetization strategies across 100+ consumer AI apps, with a deep-dive into what works for creative tools, productivity apps, and AI assistants.
The Multi-Product AI Company Playbook
Why the next wave of AI companies will look like app publishers, not SaaS companies. Portfolio strategy, shared intelligence, and the economics of multi-product AI.
Our research methodology
All Virtual Minds research combines public market data (App Store analytics, Sensor Tower, data.ai) with first-party evidence from operating 7 AI apps across 3 market verticals. We cite sources, disclose methodology, and distinguish between observation and opinion. Research is reviewed by our founding team before publication.