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  "documentTitle": "Eximius Ventures Just an Agent Away An AI Thesis",
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      "text": "Agentic startups approach pricing through an outcome-based lens. Customer support incumbents like Zendesk follow a traditional seat-based approach. In contrast, Decagon calculates how many support tickets can be processed with its solution and charges a percentage of the resultant savings. This appeals to customers who see clear, quantifiable benefits, while incumbents struggle to pivot to such a radically different structure. An established player cannot easily shift to outcome-based pricing without unsettling existing customers, contracts and internal revenue and profit projections.",
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      "text": "Pricing and business model constraints also undermine incumbents' attempts at deeper AI integration. While the cost of AI inference keeps dropping, it still remains substantial. Many AI-native startups adopt usage-based pricing: if an inference costs ten cents, the startup charges up to a dollar, pocketing the difference. Traditional software giants, however, have historically relied on seat-based pricing, and find this transition problematic. Customers accustomed to a per-seat model are reluctant to pay more for each AI interaction. However, bundling unlimited AI features into a seat license risks skyrocketing inference costs and eroding provider margins. This tension makes it incredibly difficult for large players to scale powerful AI capabilities without facing either customer dissatisfaction or severe profitability concerns.",
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      "text": "Corporate bureaucracy further impedes innovation, as organisational inertia and internal incentives favour predictable revenue from existing products over disruptive changes.",
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      "text": "Importantly, startups do not need to supplant incumbents outright to succeed. The market's scale enables new players to establish profitable niches. During the SaaS era, Slack thrived alongside Microsoft and Atlassian. Asana approached billion-dollar revenue despite competing with major software suites, while Box built a billion-dollar run rate in commodity",
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      "text": "AI applications often deliver services at lower costs with reduced human involvement. This efficiency threatens the traditional 80-85% margins that incumbents have historically enjoyed and seek to protect.",
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      "text": "Cannibalisation is another deterrent for established players. Google, for instance, could feasibly integrate advanced generative features into search—yet it proceeds cautiously given that undercutting its core advertising revenues would be detrimental. Perplexity faces none of that tension and can move faster in building innovative features.",
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