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AI is becoming standard in CX; execution is becoming the differentiator. The competitive gap is shifting from who has the most AI features to who can connect intelligence across customer context, enterprise systems and workflows to resolve outcomes end to end.

The Twimbit AI-CX Vendor Landscape 2026 therefore evaluates vendors across both AI capability and innovation and market execution and adoption, revealing who can turn AI from impressive technology into scalable enterprise impact.

AI-CX Vendor Landscape 2026

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Digital-only lenders across the Asia Pacific are entering a second wave, moving past the novelty of branchless banking toward more defined business models. Neobanking now spans standalone digital-only banks holding full licenses, digital platforms built by non-bank players, and digital spin-offs launched by incumbent banks to compete with challenger propositions.The shift reflects a broader change in customer mindset and the rise of the experience economy, where speed, personalization, and app-based convenience matter as much as product pricing. Understanding how these three structural categories differ helps explain why some digital banks scale quickly in markets like Singapore, Hong Kong, and Indonesia while others remain niche players tied to a single narrow use case such as remittances or micro-lending.Across the region, regulators are responding to digital banking license applications in different ways, neobanks are using distinct funding and partnership strategies to reach underbanked and mass-affluent segments, and traditional banks are choosing where to build their own digital-only arms rather than cede ground to independent challengers. Customer acquisition costs and deposit-gathering strategies also differ meaningfully between these models, shaping which archetype scales fastest in a given market.<ul><li>Distinct neobank archetypes: standalone digital-only banks, digital platforms, and bank-backed digital spin-offs</li><li>Regional licensing and regulatory context shaping market entry across APAC</li></ul><figure><img src="https://cdn.twimbit.com/uploads/2020/11/09141453/virtual-banking-whitepaper-07-scaled.jpg" alt="5 key characteristics of neobanks"/></figure>

Neo banking 2.0: The new face of banking in the Asia Pacific

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Managed access to Chinese frontier AI models is reshaping enterprise AI strategy. The arrival of Moonshot AI’s Kimi K3 on Amazon Bedrock signals a shift in how large organizations approach AI model selection, procurement, and governance. Enterprises can now leverage advanced, open-weight Chinese AI through familiar AWS APIs, billing, and security frameworks, reducing operational friction and enabling new options for cost management and deployment flexibility.Kimi K3’s integration with Amazon Bedrock introduces prompt caching and supports multi-model architectures, allowing organizations to distribute workloads between open-weight and proprietary models based on cost, complexity, and business needs. This development prompts a re-examination of AI infrastructure, balancing performance, cost efficiency, and governance across diverse use cases.Key considerations for CIOs, CFOs, and CISOs include model provenance, licensing, regulatory compliance, and data residency—especially as regional availability and legal obligations differ across the United States, Europe, and Asia Pacific. The managed environment provides strong infrastructure-level security, but enterprises must still evaluate the governance of Chinese-origin models before adoption.<ul><li>Explores managed deployment options for open-weight AI on AWS</li><li>Assesses security, compliance, and procurement implications</li><li>Compares regional constraints and opportunities for global enterprises</li></ul><blockquote>How will the availability of Chinese frontier AI models like Kimi K3 on Amazon Bedrock change enterprise AI procurement and governance strategies?</blockquote>

The Managed Front Door to Chinese Frontier AI: What Kimi K3 on Amazon Bedrock Means for Enterprise Buyers

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AI compute and chips are undergoing rapid transformation as enterprises shift from a focus on peak training performance to a more nuanced approach that weighs workload requirements, utilisation economics, and infrastructure flexibility. The landscape now extends beyond general-purpose GPUs to include hyperscaler-designed silicon, specialised processors, and regionally controlled architectures. This evolution is driven by growing demand for inference, AI agents, real-time applications, and distributed deployment models, all of which are reshaping how compute is sourced and deployed.Key considerations now include not only processing power, but also cost per workload, energy efficiency, software compatibility, supply resilience, and long-term adaptability. Enterprises must evaluate chip architectures and suppliers across technical, financial, strategic, and operational dimensions, with an increasing emphasis on matching infrastructure to specific application needs rather than standardising on a single chip type.<ul><li>Coverage of general-purpose GPUs, custom cloud silicon, inference specialists, and regional AI chip providers</li><li>Analysis of workload-driven procurement strategies for AI infrastructure</li><li>Examination of supplier risk, software lock-in, and multi-chip strategies</li></ul>For CIOs and technology leaders, the central question is no longer which chip is the fastest, but which combination of compute, software, and supplier ecosystem best supports evolving business and AI workload requirements.<blockquote>How are enterprise AI infrastructure decisions shifting from performance-led to workload-led strategies, and what forces are redefining the AI chip market?</blockquote>

AI Compute & Chips​: Trends and analysis in a fast-evolving market​

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Digital-only lenders across the Asia Pacific are entering a second wave, moving past the novelty of branchless banking toward more defined business models. Neobanking now spans standalone digital-only banks holding full licenses, digital platforms built by non-bank players, and digital spin-offs lau

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Neo banking 2.0: The new face of banking in the Asia Pacific

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