Software, Cloud & Artificial Intelligence
AI, cloud computing, and next-generation software platforms are reshaping the global IT architecture and broader economy — accelerating productivity, transforming industries, and unlocking one of the most compelling investment opportunities of the century.
Investment Thesis
| AI adoption is accelerating across every industry, driving exponential demand for data, compute, cloud platforms, and AI-native applications. |
| Software remains the highest-quality business model (scalable, recurring revenue, global market reach, strong margins). |
| Cloud infrastructure is expanding to meet AI’s compute intensity, creating new opportunities in storage, orchestration, and distributed systems. |
| Vertical AI applications (healthcare, manufacturing, legal, finance, robotics) are emerging faster than in previous tech cycles. |
| Enterprise software continues to replace legacy workflows, accelerating digital transformation globally. |
| AI lowers barriers to innovation, enabling leaner teams to create disruptive solutions in shorter cycles. |
| Data, cybersecurity, and digital infrastructure are becoming strategic assets and national priorities, supporting sustained investment. |
Key Subsectors & Value Chain
| AI & Machine Intelligence · Foundation models & generative AI · Vertical AI platforms (healthcare, legal, manufacturing, finance etc.) · Model training tools & infrastructure · AI chips, inference systems & model-serving platforms · Autonomous decision systems |
| Cloud Computing & Data Infrastructure · Cloud platforms (IaaS, PaaS) · Hybrid and multi-cloud orchestration · High-performance computing (HPC) for AI · Databases, data lakes, and vector databases · Observability, monitoring, and DevOps tooling |
| Enterprise & Application Software · SaaS platforms for enterprise productivity · Process automation (RPA, workflow, ERP modernization) · Cybersecurity platforms · Industry-specific systems (vertical SaaS) · Developer tools & API infrastructure |
What CAND Looks For
· Clear and defensible differentiation (technology, model performance, data advantage)
· Strong product-market fit with scalable enterprise adoption
· Compelling unit economics and recurring-revenue business models
· Sustainable competitive moats — data, distribution, integration lock-in, or ecosystem advantage
· Founder excellence and deep technical expertise
· Security, compliance, and governance readiness for enterprise-class solutions
· Credible scaling pathways with capital-efficient growth
Risks & Considerations
· Rapid technology evolution may compress competitive advantage
· High compute costs for AI model training and inference
· Regulatory uncertainty around AI usage, privacy, and data governance
· Market saturation in some horizontal AI categories
· Dependence on cloud platform ecosystems and hyperscalers
· Security threats and model vulnerability risks
How CAND Helps Investors Navigate This Sector
CAND combines deep technical literacy, strong founder networks, and AI-driven diligence tools to identify high-quality opportunities early. Our work integrates:
· evaluation of model performance and architecture
· assessment of data strategy and defensibility
· benchmarking against global competitors
· analysis of cloud and compute economics
· validation of enterprise adoption pathways
With access to emerging founders, researchers, and early-stage platforms, CAND helps qualified investors participate in this transformative sector with clarity, confidence, and high conviction.
