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The Reality of AI Adoption in SaaS companies
Strategic Summary for SaaS Leaders: While consumer AI usage is high, enterprise AI adoption remains low. Most SaaS organizations are currently in the "Messy Middle"—the transition from AI experiments to scaled operational integration. Success in 2026 is defined not by "isolated AI features," but by redesigning internal workflows, hardening data infrastructure, and treating AI as a horizontal system capability rather than a vertical product add-on. There is a nagging feeling

Anna Perelyhina
Mar 227 min read


How to Architect Your Data for Scalable AI in SaaS (2026 Guide)
In 2026, the gap between a successful AI feature and a failed one isn't the model you choose (GPT-5, Claude 4, or Llama 4). The gap is your Data Supply Chain. If your data is fragmented, delayed, or unstructured: Your AI will hallucinate. Your AI will generate irrelevant outputs. Your AI will burn tokens without generating revenue. Your AI will fail in enterprise environments. If your data is messy, your AI will be hallucinatory at best and a liability at worst. To scale, you

Anna Perelyhina
Mar 14 min read


How B2B SaaS Founders Fix Churn at $100K MRR
Why Churn Becomes a Serious Growth Problem at $100K MRR In my decade of consulting for B2B SaaS companies, I’ve seen a consistent inflection point appear around $100K MRR . At this stage, founders have achieved product-market fit. They are past the $5K–$50K MRR phase where growth depended on founder hustle, manual support, and direct customer conversations. But this is also where the growth math starts to break. The retention tactics that worked early no longer scale. Founder

Anna Perelyhina
Jan 25 min read
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