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<div>
 
 A look at NVIDIAs Q3 FY2025 announcements and their implications for EDGE industries..
 
</div>

<div>
 <h1>
 Key takeaways
 </h1>
 <ul>
 <li>
 
 <a href="https://sp-edge.com/industry/178">
 GenAI Infrastructure
 </a>
 &nbsp;
 
 <ul>
 <li>
 
 Announced plans to scale the output of the next-generation Blackwell GPU, aiming to deliver increasing quantities each quarter. Notably, the company had already shipped 13,000 Blackwell samples to customers during the quarter.
 
 </li>
 <li>
 
 A surge in infrastructure demands has resulted in NVIDIA 
 <a href="https://www.theverge.com/2024/5/22/24162860/nvidia-ai-chip-every-year-blackwell-rubin">
 accelerating
 </a>
 its development timelines, committing to release new chips annually instead of the previous two-year cadence.
 
 </li>
 </ul>
 </li>
 <li>
 
 <a href="https://sp-edge.com/industry/133">
 Next-gen Mobile Networks
 </a>
 &nbsp;
 
 <ul>
 <li>
 
 Launched 
 <a href="https://blogs.nvidia.com/blog/ai-aerial-wireless-networks/">
 AI Aerial
 </a>
 during Q3, offering AI-driven radio access network (AI-RAN) solutions to meet growing 5G and 6G infrastructure demands.
 
 </li>
 </ul>
 </li>
 <li>
 
 <a href="https://sp-edge.com/industry/149">
 Digital Twin
 </a>
 &nbsp;
 
 <ul>
 <li>
 
 Announced partnerships with Foxconn, Toyota, and Reliance to utilize NVIDIA Omniverse to create digital replicas of factories, enabling more efficient workflows and capitalizing on strengths in graphics processing and real-time simulation.
 
 </li>
 </ul>
 </li>
 <li>
 
 <a href="https://sp-edge.com/industry/185">
 Humanoid Robotics&nbsp;
 </a>
 
 <ul>
 <li>
 
 Launched 
 <a href="https://blogs.nvidia.com/blog/robot-learning-humanoid-development/">
 AI simulation tools
 </a>
 to advance robot learning and humanoid development, complementing its GPUs' strengths in powering AI workloads, particularly in computer vision&mdash;a crucial technology that enables robots to &quot;see&quot; through camera scans and image-processing ML algorithms.
 
 </li>
 </ul>
 </li>
 <li>
 
 <a href="https://sp-edge.com/industry/24">
 Quantum Computing
 </a>
 
 <ul>
 <li>
 
 SPEEDA Edge&rsquo;s proprietary 
 <a href="https://sp-edge.com/companies/4353#activities">
 activities tracker
 </a>
 showed partnerships with 
 <a href="https://nvidianews.nvidia.com/news/nvidia-supercharges-google-quantum-processor-design-with-simulation-of-quantum-device-physics">
 Google
 </a>
 , 
 <a href="https://sp-edge.com/updates/36154">
 AlgorithmQ
 </a>
 , and 
 <a href="https://sp-edge.com/updates/34200">
 Equal1
 </a>
 to utilize CUDA-Q&mdash;a software toolkit for orchestrating large-scale quantum computing applications, underscoring NVIDIA&rsquo;s efforts in the space.
 
 </li>
 </ul>
 </li>
 <li>
 
 <a href="https://sp-edge.com/industry/106">
 Hospital Management
 </a>
 
 <ul>
 <li>
 
 NVIDIA ventured into the area via 
 <a href="https://sp-edge.com/updates/34200">
 partnerships
 </a>
 with 
 <a href="https://sp-edge.com/companies/2555">
 Oracle
 </a>
 and 
 <a href="https://sp-edge.com/companies/120687">
 AvaSure Holdings
 </a>
 . By leveraging its accelerated computing infrastructure, the company aided the development of an AI-powered virtual concierge solution to enhance patient care and streamline clinical workflows.&nbsp;&nbsp;
 
 </li>
 </ul>
 </li>
 </ul>
 
 
</div>

NVIDIA Q3 FY2025 recap

Providing AI-driven market intelligence and workflow automation to give firms an edge

Capital Markets Tech

<div>
 
 This trend discusses how regulatory technology (RegTech) is streamlining labor-intensive processes related to Anti-Money Laundering (AML) compliance. It highlights the increasing complexity and scope of AML regulations, which now extend to industries such as gambling, insurance, and real estate in addition to financial services and the role of RegTech in simplifying the KYC and KYB processes.
 
</div>

<div>
 <ul>
 <li>
 
 A
 ML compliance requires 
 Know-Your-Customer (KYC)
 and 
 Know-Your-Business (KYB)
 processes, which are typically manual, time-consuming, and labor-intensive.
 
 </li>
 <li>
 
 RegTech solutions
 automates key compliance tasks, such as regulatory monitoring, reporting, and risk management, with a primary focus on AML requirements.
 
 </li>
 <li>
 
 RegTech addresses 
 customer identification, due diligence, and ongoing monitoring
 through tools for identity management, risk assessment, transaction monitoring, and regulatory reporting.
 
 </li>
 <li>
 
 RegTech firms are acquiring other RegTech companies to expand their service portfolios and market presence, focusing on functional areas like i
 dentity management, risk management, and transaction monitoring.
 
 </li>
 <li>
 
 Gen AI generates 
 authentic-looking fake content
 , such as social media personas and legal documentation, that could evade detection in AML compliance systems.
 
 </li>
 </ul>
 
 
</div>

RegTech

Quantum information processing is slowly becoming a reality, ushering in a new technological era.

Quantum Computing

<div>
 
 A deep dive into PsiQuantum's product, business model, competitive environment, and market opportunities...
 
</div>

<div>
 
 
 <ul>
 <li>
 
 PsiQuantum, founded in 2015 by quantum physicists and photonics experts, is developing a scalable, fault-tolerant quantum computer using silicon photonics. Its system aims to scale to over 1 million qubits, enabling applications in drug discovery, materials science, and finance.
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 PsiQuantum prioritizes building utility-scale quantum computers with millions of qubits for error-corrected algorithms, leveraging established silicon manufacturing and proprietary optical switching technology.
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 PsiQuantum competes in the quantum computing hardware market against tech giants (e.g., IBM, Google, and Microsoft), quantum-focused startups (e.g., IonQ, Rigetti, and Quantinuum), and photonic quantum rivals like Xanadu.
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 PsiQuantum faces risks from its exclusive reliance on silicon photonics, making it vulnerable to technical barriers and costly pivots due to deep integration with GlobalFoundries. Its focus on building million-qubit systems bypasses incremental milestones, risking delays and allowing competitors to secure early market advantages. Additionally, scaling novel components like photon sources, detectors, and high-performance optical switches involves significant manufacturing challenges, with potential yield and performance issues that could impact costs and timelines.
 
 </li>
 </ul>
 
 
</div>

PsiQuantum: A pioneer in advancing quantum computing hardware development

<div>
 <ul>
 <li>
 
 57% of banks use AI in fraud detection, and 48% in risk assessment. Major initiatives include Wells Fargo's AI in trade finance and Abound's USD 1 billion raise for AI lending.
 
 </li>
 <li>
 
 GenAI is growing, 69% of wealth management firms using GenAI in customer service.
 
 </li>
 <li>
 
 Blockchain and AI-enhanced biometrics are active, with 60%&ndash;75% biometric adoption in financial services.
 
 </li>
 </ul>
 
 
</div>

<div>
 <h1>
 Key takeaways
 </h1>
 <ul>
 <li>
 
 Classical AI (predominantly machine learning [ML] and natural language processing [NLP]) has found its footing in backend operations, 
 with
 
 57% of banks having deployed it in fraud detection and 48% in risk assessment. Notable developments included 
 <a href="https://www.fintechfutures.com/2024/04/wells-fargo-to-integrate-ai-into-trade-finance-operations-with-tradesun/">
 Wells Fargo
 </a>
 and 
 <a href="https://www.bobsguide.com/lloyds-and-cleareye-ai-forge-ai-centric-trade-finance-alliance/">
 Lloyds'
 </a>
 AI integrations in trade finance and significant funding rounds like 
 <a href="https://sp-edge.com/updates/31021">
 Abound's USD 1 billion
 </a>
 raise for international AI lending platform expansion
 
 </li>
 <li>
 
 GenAI is gaining momentum across customer-facing operations:
 Major initiatives included Wells Fargo's 
 <a href="https://itrexgroup.com/blog/generative-ai-in-banking/">
 Fargo
 </a>
 assistant (handling 100 million annual interactions) and NatWest's
 <a href="https://www.natwestgroup.com/news-and-insights/news-room/press-releases/data-and-technology/2024/jun/natwest-launches-cora-plus-the-latest-generative-ai-upgrade-to-t.html">
 Cora+
 </a>
 having practical applications of GenAI in this space. Notably, Temenos' 
 <a href="https://www.temenos.com/news/2024/05/13/temenos-launches-the-first-responsible-generative-ai-solutions-for-core-banking/">
 launch
 </a>
 of &ldquo;Responsible Generative AI&rdquo; solutions for core banking operations aimed to address regulatory compliance and data security challenges in financial operations.
 
 </li>
 <li>
 
 Blockchain and AI-enhanced biometrics appear as active trends across payments:
 Blockchain is making substantial progress in backend and customer-facing payment applications, with Worldpay reporting a 50% reduction in payment processing time through its stablecoin system and 29% of retail investors using crypto for transactions (up from 23% in 2022). Biometric adoption in financial services has reached 60%&ndash;75%&mdash;among the highest across sectors&mdash;with solutions like Mastercard's
 <a href="https://www.mastercard.com/news/press/2024/april/mastercard-transforms-the-fight-against-scams-with-latest-ai-tech/">
 Scam Protect
 </a>
 combining identity verification and behavioral biometrics.&nbsp;
 
 </li>
 <li>
 
 AI-driven personalization supports retail investment strategies and back-office automation for wealth managers:
 Product updates such as Revolut's 
 <a href="https://www.revolut.com/en-FR/news/revolut_launches_robo_advisor_in_eea_to_automate_investing/#:~:text=Revolut%20has%20made%20investing%20more,Advisor%20service%20in%20the%20EEA.">
 robo-advisory service
 </a>
 s and EarnUp's 
 <a href="https://sp-edge.com/updates/32186">
 AI Advisor
 </a>
 are examples of hyper-personalized investment products. GenAI adoption in wealth management is particularly strong in 
 customer service (69% of firms) and investment research (50%),
 with BCG estimating potential time savings of up to 30% in areas like customer boarding.
 
 </li>
 <li>
 
 Open banking data sharing receives big regulatory boost:
 Relaxation of regulations surrounding open banking has enabled banks to seamlessly share data among themselves, resulting in the emergence of new payment models, such as account-to-account (A2A) and multi-currency payments. Notable developments included 
 <a href="https://sp-edge.com/companies/41928">
 HSBC
 </a>
 &rsquo;s launch of 
 <a href="https://fintechmagazine.com/articles/hsbc-set-to-launch-international-payments-app-zing">
 Zing
 </a>
 , a 
 <a href="https://investor.visa.com/news/news-details/2024/HSBC-Partnered-with-Visa-to-Develop-Zing-International-Money-App/default.aspx">
 multi-currency payments app
 </a>
 , in collaboration with 
 <a href="https://sp-edge.com/companies/13061">
 Visa
 </a>
 
 </li>
 <li>
 
 Asset tokenization regains traction for institutional wealth management:
 The value of tokenized assets reached USD 15 billion as of September 2024 (excluding stablecoins). Major financial institutions, including BlackRock, Fidelity, and JPMorgan,&nbsp; actively implemented blockchain technology for tokenization, players such as State Street 
 <a href="https://www.paymentsjournal.com/state-street-to-launch-tokenization-platform-for-institutional-investors/">
 introduced tokenization
 </a>
 platforms, and partnerships between companies like AlphaPoint, Polymesh, 
 <a href="https://archax.com/insights/assetera-and-archax-announce-first-pan-european-strategic-partnership">
 Archax, and Assetera
 </a>
 aimed to enhance and facilitate asset tokenization.
 
 </li>
 <li>
 
 <a href="https://sp-edge.com/industry/24">
 Quantum computing
 </a>
 also showed promising use cases,
 particularly in portfolio optimization, simulations, and credit analysis. Key players such as 
 <a href="https://aws.amazon.com/blogs/quantum-computing/goldman-sachs-and-aws-examine-efficient-ways-to-load-data-into-quantum-computers/">
 Goldman Sachs
 </a>
 , 
 <a href="https://www.jpmorgan.com/technology/applied-research">
 JPMorgan
 </a>
 , and 
 <a href="https://www.hsbc.com/who-we-are/businesses-and-customers/hsbc-and-quantum">
 HSBC
 </a>
 were among the major institutions frontlining research into quantum computing in financial services. However, most real-world implementations are still in experimental phases, with 60% of regulators expecting a significant impact within as late as 
 <a href="https://www.theasianbanker.com/updates-and-articles/quantum-technology-can-revolutionise-finance,-but-create-new-problems">
 seven years
 </a>
 . Notably, 
 <a href="https://sp-edge.com/companies/29093">
 D-Wave Systems
 </a>
 , a maker of 
 <a href="https://www.dwavesys.com/solutions-and-products/financial-services/">
 quantum annealing systems
 </a>
 , is exploring applications in financial services, a hybrid approach that combines classical CPUs/GPUs with their quantum annealing hardware.
 
 </li>
 </ul>
 
 
</div>

State of tech in Financial Services: How AI, blockchain, and biometrics are forging the future

Speeding up sales, cutting costs, and preparing for the future of retail—whether brick-and-mortar or online.

Retail Industry Robots

<div>
 
 This trend refers to the deployment of ultra-fast delivery services, where goods reach customers within hours or even minutes of ordering. The report covers methods of inventory placement in close proximity to customers, automation technology used to enable efficient order fulfillment, and flexible modes of last-mile delivery.
 
</div>

<div>
 <ol>
 <li>
 
 Ultra-Fast Delivery Brings Instant Gratification to Digital Shopping
 
 Ultra-Fast Delivery (UFD) has transformed digital shopping by reducing the waiting period to hours or even minutes, particularly through quick-commerce. This rapid service meets the consumer desire for immediacy, combining the convenience of online shopping with nearly instant access to goods.
 
 </li>
 <li>
 
 Decentralised Fulfilment Centres in Urban Areas Store Inventory Near Customers
 
 Decentralised fulfilment centres, or micro-fulfilment hubs, are strategically placed in urban areas to bring inventory closer to customers. This structure reduces delivery times and enhances efficiency by focusing on fast-moving products in smaller, localised centres.
 
 </li>
 <li>
 
 UFD Helps Retailers Improve Sales and Reduce Cart Abandonment
 
 Retailers offering UFD benefit from increased conversion rates and reduced cart abandonment, as quick delivery options meet consumer expectations for speed. Studies indicate that offering same-day delivery can significantly boost sales and customer retention.
 
 </li>
 <li>
 
 Q-Commerce Market Growth Signals Favourable Prospects for UFD Market
 
 Quick-commerce, which handles ultra-fast deliveries, is experiencing significant growth, with projections indicating a strong upward trend. This growth reflects a broad market shift toward rapid delivery services across various regions, driven by high demand in densely populated urban areas.
 
 </li>
 <li>
 
 UFD with Automation Could Slash Picking Labour Cost; Other Strategies Needed to Further Improve Margins
 
 Automating UFD processes reduces picking costs and enhances order fulfilment efficiency. However, additional strategies, like subscription models and minimum order thresholds, are needed to make UFD financially sustainable for retailers.
 
 </li>
 <li>
 
 Incumbent Retailers, E-Commerce Players Acquire Tech Firms to Boost In-House Capabilities
 
 Major retailers and e-commerce platforms are acquiring tech companies to strengthen in-house UFD capabilities. This approach supports automation, inventory management, and last-mile delivery, enabling established players to integrate UFD seamlessly into their operations.
 
 </li>
 <li>
 
 Dark Store Failures Lead to Consolidation; Public Criticism Prompts Regulation in Europe, the US
 
 While dark stores drive ultra-fast delivery, their high operational costs and local disruptions have led to business failures and consolidations. Public backlash and regulatory responses, particularly in Europe and the US, are pushing dark stores out of residential areas to mitigate their impact on communities.
 
 </li>
 </ol>
 
 
</div>

Ultra-Fast Delivery

Exploring the limitless possibilities of AI

Generative AI Applications

<div>
 
 A deep dive into ElevenLab's financials, product, competitive environment, and market opportunities...
 
</div>

<div>
 
 
 <ul>
 <li>
 
 Sacra estimates that ElevenLabs achieved&nbsp; USD 90 million in annual recurring revenue (ARR) as of October 2024, a sizable increase from USD 25 million at the beginning of the year, reflecting a 260% growth.
 
 </li>
 <li>
 
 The company generates revenue primarily through its AI voice platform, which is utilized by 41% of Fortune 500 companies. Its competitive edge lies in its ability to produce high-quality, lifelike speech synthesis and voice cloning, with features that allow for contextual emotional expression.
 
 </li>
 <li>
 
 ElevenLabs competes with major tech companies like OpenAI and Google, as well as specialized voice AI firms. While these larger companies have voice synthesis capabilities, ElevenLabs focuses exclusively on audio quality and user experience, positioning itself as a leader in the generative speech market.
 
 </li>
 <li>
 
 The company is well-positioned to expand its total addressable market into sectors such as healthcare, education, and enterprise communications, leveraging its advanced voice technology to meet the growing demand for AI-generated content and localized media.
 
 </li>
 </ul>
 
 
</div>

ElevenLabs: The software platform for generating natural-sounding text-to-speech.

<div>
 
 A deep dive into Glean's revenue, product, competition, and TAM expansion
 
</div>

<div>
 
 
 <ul>
 <li>
 
 Sacra estimates Glean's revenue will reach USD 80 million in 2024, growing 105% YoY, driven by the adoption of its AI-powered enterprise search platform.
 
 </li>
 <li>
 
 The company serves mid-market and enterprise clients with 500+ employees through per-seat subscription licensing, with contracts starting from USD 100,000 annually for mid-market clients.
 
 </li>
 <li>
 
 Glean competes with players offering traditional enterprise search (Microsoft SharePoint Search, Elastic Enterprise Search) and newer AI-powered workplace assistants (Moveworks, Guru). 
 
 </li>
 <li>
 
 Glean's product functions as a unified search layer across enterprise applications like Slack, Google Workspace, and Salesforce, providing AI-powered search capabilities while maintaining security and permissions controls.
 
 </li>
 </ul>
 
 
</div>

Glean: An enterprise search and knowledge discovery platform to improve workplace productivity

<div>
 
 A deep dive into Hebbias' financials, product, competitive environment, and market opportunities...
 
</div>

<div>
 
 
 <ul>
 <li>
 
 Hebbia has achieved USD 13 million in ARR, reflecting a 15x growth over the past 18 months, as of June 2024. The company&rsquo;s revenue surged from approximately USD 900,000 in December 2022 to USD 10 million by December 2023.
 
 </li>
 </ul>
 <ul>
 <li>
 
 Hebbia's flagship product, Matrix, allows users to analyze large volumes of unstructured data across multiple document types simultaneously. This tool is particularly beneficial to private equity analysts conducting due diligence.
 
 </li>
 </ul>
 <ul>
 <li>
 
 Matrix features a distinctive &quot;data-grid&quot; interface that facilitates interaction with LLMs in a more intuitive manner than traditional chat interfaces. It can ingest various document formats and automate complex queries, significantly reducing analysis time.
 
 </li>
 <li>
 
 During its Series B funding round in July 2024, led by Andreessen Horowitz, Hebbia was valued at USD 700 million. The company raised a total of USD 161.1 million across four funding rounds, with Series B accounting for USD 130 million.
 
 </li>
 <li>
 
 The valuation represents an approximate 54x revenue multiple, indicating strong investor confidence based on the reported ARR.
 
 </li>
 <li>
 
 Hebbia operates as a subscription-based SaaS company, primarily targeting financial institutions, law firms, and government agencies. Pricing is approximately USD 15,000 per seat annually, placing it in the premium enterprise software category.
 
 </li>
 <li>
 
 Hebbia competes with established enterprise search platforms and new AI-focused startups. Notable competitors include Microsoft SharePoint Search and Glean, which emphasize security and integration but may lack Hebbia's specialized features for financial document analysis.
 
 </li>
 <li>
 
 Hebbia is positioned to expand into adjacent markets such as enterprise knowledge management and workflow automation. Its capabilities allow it to unify fragmented knowledge across various SaaS applications, enhancing its appeal as an AI-powered workplace assistant.
 
 </li>
 </ul>
 
 
</div>

Hebbia

Membership-based, non-insurance healthcare companies helping maintain a steady state of well being.

Preventive Healthcare

<div>
 
 A deep dive into Virta Health's revenue, product, competition, and TAM expansion
 
</div>

<div>
 <ul>
 <li>
 
 Sacra estimated that Virta Health&rsquo;s revenue will reach USD 175 million in 2024, up 51% YoY from USD 116 million in 2023. Its revenue sources include diabetes reversal (54%), obesity treatment (27%), diabetes management (14%), and platform fees (5%).
 
 </li>
 <li>
 
 Virta partners with around 550 B2B clients, achieving an average revenue per client of USD 318,000, significantly higher than competitors (Omada Health: USD 158,000) due to its focus on high-value diabetes reversal patients. The company operates on an outcome-based pricing model, with all fees at risk, tying payments to clinical success.
 
 </li>
 <li>
 
 Last valued at USD 2 billion in 2021, Virta has raised USD 376.5 million since 2014 from investors like Tiger Global and Sequoia Capital.
 
 </li>
 <li>
 
 Virta&rsquo;s product combines continuous remote monitoring with ketogenic diet support to reverse Type 2 diabetes, differentiating it from competitors who focus on disease management.
 
 </li>
 <li>
 
 Growth is driven by increased enrollment in obesity programs (45% of new enrollments), positioning it as a cost-effective alternative to GLP-1 drugs. Future expansion may include other metabolic conditions like cardiovascular disease.
 
 </li>
 <li>
 
 Virta Health faces competition from digital health platforms like Omada Health and Livongo, which focus on diabetes management rather than reversal, as well as traditional diabetes management providers like DarioHealth, Glooko, Perry Health, and Verily (Onduo) and new entrants offering GLP-1 medication programs.
 
 </li>
 <li>
 
 Key risks include limited patient selection, competition from GLP-1 medications, and a shifting revenue mix from high-margin diabetes programs to lower-margin obesity treatments.
 
 </li>
 </ul>
 
 
</div>

Virta Health: The virtual care platform reversing Type 2 diabetes and reducing medication for chronic metabolic conditions

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

<div>
 
 
 <ul>
 <li>
 
 Towaki Takikawa (ex-Nvidia), co-founder and CEO at Outerport, a deployment platform for AI models, talks about the critical &quot;cold start&quot; problem in AI model deployment, where loading large models (often 17GB or larger) from storage to CPU and GPU memory can cause significant delays and costs. He also discusses how Outerport's daemon process solution manages model weights in CPU memory, enabling quick model swapping and reducing latency from minutes to seconds.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 The platform particularly resonates with companies developing diffusion models and compound AI systems, where multiple models need to work together efficiently. While initially focused on CPU/GPU performance optimization, Outerport aims to become a comprehensive MLOps solution, bridging the gap between research-oriented and production-grade AI deployments. The company serves both individual developers seeking immediate value and enterprise clients requiring robust infrastructure, positioning itself as a crucial tool in the evolving landscape of AI model deployment and management.
 
 </li>
 </ul>
 
 
</div>

EDGE Insights