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Kalman Tiboldi - CTO & Founder at GemOne-TVH - Simplify or Die: Why Complexity Is the Real IT Challenge
Germany Sep 25, 2025 Country Members Physical english
Join us for an evening of thought-provoking discussions, real-world use cases, and insights from digital leaders, tech-pioneers and academics as we explore the dynamics of the human-machine relationship.
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Netherlands Sep 25, 2025 Invitation Only Physical dutch
Alleen op uitnodiging. How can organizations proactively ensure business continuity and IT resilience in 2025 amidst increasing disruptions?
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Germany Sep 29, 2025 Country Members Virtual german
Unsere Wissensaustausch-Briefings "AI & Data Knowledge Transfer" zielen darauf ab, CIDOs und Senior Digital Leaders mit praktischen Anwendungen und umsetzbaren Erkenntnissen von Fachexperten zu vermitteln, die den Weg für transformative digitale Reisen ebnen.
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Germany Sep 30, 2025 Country Members Physical german
Von der Theorie in die Praxis: Erst Business, dann Bier.Unstrukturierte Daten sind das verborgene Kapital vieler Unternehmen – und zugleich eine der größten Herausforderungen moderner IT. Gemeinsam mit CIOs, CDOs und CTOs der CIONET-Community sprechen wir zuerst bei WeWork München über Strategien, Technologien und echte Use Cases, um dieses Potenzial zu heben. Danach geht's weiter auf die Wiesn – für den offenen Austausch in bayerischer Atmosphäre.
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UK Sep 30, 2025 Invitation Only Physical english
This exclusive Jefferson dinner, hosted by Mendix and CIONET, brings together a hand-picked group of senior executives and digital leaders from across the UK financial sector.
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Netherlands Sep 30, 2025 Invitation Only Physical dutch
Alleen op uitnodiging. Mastering Digital Sovereignty Control, trust and resilience in an era of geopolitical and regulatory shifts. From the Network to the Data.
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Crypto.com Delivers Accurate Sentiment Analysis in 1 Second with Generative AI on AWS
Crypto.com uses Amazon Bedrock with Amazon SageMaker Studio to run an efficient architecture that delivers nuanced, domain-specific crypto market insights to 100 million global users.
to return results from large language models
to integrate Claude 3 models
Delivers localized multilingual content
Helps engineers continually test new models
Crypto.com is a crypto exchange and comprehensive trading platform serving 100 million users in 90 countries. To improve the service quality of Crypto.com, the firm implemented generative artificial intelligence (AI)-powered sentiment analysis services on AWS to generate market insights.
Crypto.com uses Anthropic Claude 3 large language models on Amazon Bedrock for sentiment analysis and application development, and Amazon SageMaker to fine-tune its custom models. With the top models on AWS, the company can deliver accurate sentiment analysis in less than 1 second, and efficiently train and adjust new models in a rapidly evolving market.
Crypto.com was founded in 2016 with a bold mission: to bring cryptocurrency to every wallet. The company distinguishes itself from other trading platforms through its strong focus on driving user adoption, with a wide network of partners including merchants and payment gateways. Crypto.com currently serves around 100 million users in 90 countries.
With such rapid growth and a diverse customer base—all within an evolving, competitive industry—Crypto.com has embraced generative artificial intelligence (AI) to quickly deliver optimized customer experiences. The company’s AI use cases include conversational assistants for onboarding and customer queries, plus wizards to generate social media marketing campaigns.
In generative AI applications, sentiment analysis and news narrative categorization are becoming increasingly vital; particularly in the cryptocurrency space, investors need timely and accurate market intelligence to make informed decisions. Crypto.com provides a market insight service where users can access the latest news and information from both crypto and traditional news sources to gain insights from the company’s intelligence engines. Each subscription is tailored to the user’s trading level and the coins in their wallet.
Crypto.com employs a range of off-the-shelf machine learning (ML) models alongside its own custom models for sentiment analysis. However, developers encountered challenges with the limitations of open-source models and the high cost of self-hosting large language models (LLMs). They also faced accuracy issues with outputs generated by open-source models, especially when dealing with multilingual news sites. Consequently, Crypto.com sought a more effective solution to integrate and synthesize outputs from multiple ML models—both pre-trained and custom—to provide accurate, reliable, and comprehensive insights into the crypto market.
Generative AI on AWS services like Amazon SageMaker and Amazon Bedrock streamlined our adoption of the latest LLMs and AI technologies. We can now take innovative ideas from POC to full-scale production in weeks.”
Sunny Fok
SVP, Head of AI Innovation Technology at Crypto.com
Crypto.com has run on Amazon Web Services (AWS) since its launch, so when it sought new LLMs for sentiment analysis, Anthropic Claude 3 on Amazon Bedrock was a logical choice. These LLMs are highly scalable and process vast amounts of data in real-time, facilitating comprehensive market research. Initial results showed that LLMs on Amazon Bedrock returned results very quickly, typically within one second.
Integrating Amazon Bedrock eliminated the manual effort, extra cost, and computational constraints of self-hosting LLMs. Within one month, Crypto.com had implemented Anthropic Claude 3 Haiku models on Amazon Bedrock for sentiment analysis, collecting and analyzing crypto news in more than 25 languages. The firm also utilizes Amazon Bedrock for ongoing proofs of concept (POCs) and development. Sunny Fok, head of AI & innovation technology at Crypto.com, says, “Generative AI on AWS services like Amazon SageMaker and Amazon Bedrock streamlined our adoption of the latest LLMs and AI technologies. We can now take innovative ideas from POC to full-scale production in weeks.”
To ensure domain-specific knowledge is applied in model output, Crypto.com used its own data to fine-tune open-source models including Mistral AI and Meta Llama on Amazon Elastic Compute Cloud (Amazon EC2). This approach is crucial when a new coin appears on the market, as off-the-shelf models often deliver subpar results. Crypto.com then began using Amazon SageMaker as an on-demand, end-to-end ML development platform to fine-tune its custom models.
Raymond Lam, senior engineer at Crypto.com, says, “Amazon SageMaker provides the tools and APIs to easily adapt our models with a user-friendly interface. Similar to Amazon Bedrock, we only need to run machine learning jobs as needed, and it’s much easier to manage custom modeling than if we were doing it on our own.”
Crypto.com received extensive support from AWS throughout the idea generation, POC, and production phases of multi-agent deployment. "We had several discussions on what tools or frameworks to deploy for different use cases,” says Lam. “The AWS team shared existing use cases, provided sample code, and demonstrated each step. When technical issues came up, AWS solutions architects helped troubleshoot and offered suggestions, which sped up our onboarding to generative AI on AWS services."
By implementing a multi-agent consensus-seeking solution for sentiment analysis on AWS, Crypto.com can efficiently deliver accurate, comprehensive, and localized crypto market insights to its global user base. Fok explains, "We can share more instant, updated news with users on the sentiment of coins—whether they’re bullish or bearish, for example. Users become more informed, which means they can make better-planned investments." Engineers have also noted improved accuracy for large-context QE with Claude 3 models on Amazon Bedrock.
Furthermore, with Amazon Bedrock, Crypto.com benefits from highly scalable models that automate insight generation to save time and resources. “We’re becoming more efficient with ready-to-use models we can access via API, which gives us more flexibility in development,” Lam says. “With generative AI on AWS, we have more options for different use cases or requirements, so we can easily test new models as they come out.”
Crypto.com is currently exploring new use cases for Claude 3 models on Amazon Bedrock, such as processing documents, tables, and charts. Initial tests have shown promising results in terms of accuracy compared to ML-driven optical character recognition (OCR) readers on the market. The company is also actively developing new generative AI use cases, such as capturing sentiment in social media.
Customers have expressed satisfaction with the work underway, which encourages Crypto.com to keep testing ways to deploy generative AI across the organization. “The feedback from our generative AI projects has been quite amazing, both internally and from our users,” Fok shares.
Crypto.com is on a mission to accelerate the world’s transition to cryptocurrency. With approximately 100 million users across 90 countries, the Singapore-based company offers a trading platform, derivative exchanges, and more. Crypto.com also partners with merchants and payment gateways to support the development of a global crypto network.
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