SLM vs LLM: When 2B parameters beat 1T
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The assumption that bigger models are always better isintuitive but wrong.
AI-first applications
AI-first applications go beyond traditional ERP, CRM, and SaaS by learning, adapting, and making decisions autonomously. Instead of relying on manual inputs and rigid workflows, they analyze data, optimize processes, and solve problems in real time, making businesses more efficient and future-ready.
Traditional business applications are becoming obsolete. As Satya Nadella recently pointed out, AI is shifting business logic from static databases to intelligent agents, enabling applications to analyze, decide, and act in real time.
💰 Lower Costs – Automates workflows, reducing admin overhead and IT maintenance.
📈 Greater Efficiency – AI handles complex processes, freeing teams for strategic work.
🎯 Better Customer Experiences – Personalizes interactions and adapts in real time.
⚡ Increased Agility – AI-first apps evolve dynamically as business conditions change.
Companies that embrace AI-first applications today will gain a competitive advantage, while those clinging to static systems risk falling behind. The future of business isn’t software—it’s intelligence.
Why to change the thinking about apps now
78%
of organizations have integrated AI into at least one business function
54%
cheaper maintenance of apps, which core is based on AI tech stack
77%
of mobile devices are using integrated AI features, users expect the same elsewhere
48%
shorter time-to-market for changes in AI-first applications
Read more on related topics
What is SLM and why size matters
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A clear explanation of SLMs: purpose-built AI models that deliver faster, more accurate results while keeping your data on-premise.
The AI Automation Field Guide: From Pilot to Production in 90 Days
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A pragmatic 90-day roadmap to take AI automation from pilot to secure production.
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