Dynamic client base expansion is a priority for B2BROKER during 2017 year. There are several more expo’s that we are aiming for the next two quarters, for example: iFX Cyprys, FPE Amsterdam. iFX at HongKong which will be active up to 23th of February already collected a big hype around B2BROKER booth. That means that further success in spreading […]

<p style="color: #111f2a;">Dynamic client base expansion is a priority for B2BROKER during 2017 year. There are several more expo’s that we are aiming for the next two quarters, for example: <span style="font-weight: 600;">iFX Cyprys</span>, <span style="font-weight: 600;">FPE Amsterdam</span>. <span style="font-weight: 600;">iFX at HongKong</span> which will be active up to 23th of February already collected a big hype around B2BROKER booth. That means that further success in spreading company’s highly technological products is guaranteed.</p>We will never miss the opportunity to deliver freshly-made business solutions for brokers and companies, to make their business grow faster!Pay a special attention for the next Expo as you can find <a href="https://b2broker.com/" target="_blank" rel="noopener noreferrer">forex brokerage solutions</a> by B2BROKER that early you wasn’t even able to imagine.

B2BROKER Dynamic Client Expansion

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AI as a Service (AIaaS) delivers cloud-based AI tools for businesses. Learn how AIaaS works, top applications, and the future of AI-driven automation.

Artificial Intelligence (AI) reshapes industries, but building AI from scratch can be costly and complex. AI as a Service (AIaaS) is a 

 that allows businesses to access AI-powered tools without investing in infrastructure or expertise. Just as SaaS revolutionised software delivery, AIaaS makes AI accessible, scalable, and cost-effective for companies of all sizes.

From predictive analytics and NLP to generative AI as a service, AIaaS enables seamless AI integration into workflows, automating tasks, enhancing decision-making, and driving innovation. 

This guide explores how AIaaS works, its major types, key AIaaS applications, and future trends shaping AI automation.

AI as a Service (AIaaS) refers to cloud-based artificial intelligence services that allow businesses and individuals to access AI-powered tools and functionalities without needing to develop, maintain, or host their own 

. AIaaS enables users to leverage AI capabilities on demand without requiring deep technical expertise in AI development.

 provides access to software applications via the cloud, AIaaS delivers AI functionalities — such as machine learning, natural language processing, computer vision, and predictive analytics — through cloud-based platforms. This model helps companies integrate AI into their workflows efficiently, cost-effectively, and with minimal technical complexity.

AIaaS is growing rapidly, with the global market expected 

 as businesses increasingly adopt AI-powered automation.

AI as a Service (AIaaS) allows businesses to access artificial intelligence capabilities via cloud-based platforms without investing in infrastructure or AI expertise.

Operating on cloud computing, AIaaS provides AI functionalities on demand, allowing businesses to scale resources and integrate AI models seamlessly into their workflows. 

The following sections explore the key components of AIaaS, including infrastructure, accessibility, training, deployment, pricing, and continuous improvements.

AIaaS platforms operate on cloud-based infrastructure to deliver high-performance AI capabilities without requiring businesses to invest in in-house hardware or AI teams. These platforms manage and optimise AI models on distributed cloud servers, ensuring seamless scalability.

AI processing requires significant computational resources, which AIaaS providers handle using advanced hardware such as GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units). These specialised components enhance AI model training and inference efficiency, enabling the rapid processing of large datasets and complex computations.

AI models are hosted in the cloud and are continuously optimised to enhance accuracy, reduce latency, and improve real-time decision-making. Regular refinements ensure businesses can always access the most advanced AI capabilities without requiring manual intervention.

AI models rely on vast amounts of structured and unstructured data. AIaaS platforms provide secure cloud storage and high-speed processing solutions, allowing businesses to efficiently analyse and manage extensive datasets for machine learning, automation, and analytics.

Accessing AIaaS: APIs, SDKs, and Web Interfaces

AIaaS solutions are designed to be accessible through multiple interfaces, allowing businesses to integrate AI functionalities differently.

 enable businesses to integrate AI-powered capabilities into their applications without requiring in-depth AI expertise. Data is sent to cloud-based AI models, which return processed insights or results in real time.

 provide developers with pre-built AI tools and libraries, making integration into applications seamless. These kits offer ready-made functionalities to facilitate speech recognition, natural language processing, and predictive analytics.

For businesses without in-house AI expertise, web-based platforms offer intuitive interfaces that allow users to train, test, and deploy AI models with minimal technical knowledge. These platforms support AI-driven automation, analytics, and decision-making.

AIaaS platforms offer two primary approaches for businesses: pre-trained AI models for immediate deployment and custom AI training for specialised applications.

These AI models come pre-built for common applications such as 

, sentiment analysis, and recommendation systems. They require minimal setup and can be integrated directly into business workflows.

For businesses with unique datasets or specific needs, AIaaS allows the customisation of AI models. Companies can train models using proprietary data, fine-tuning them for industry-specific use cases. This approach ensures AI solutions are optimised for particular business requirements.

Once an AI model is developed or selected, it must be deployed and integrated into business operations. AIaaS platforms offer multiple deployment methods based on business needs.

AI models run entirely on cloud servers, minimising infrastructure management. Businesses access AI capabilities via cloud-based interfaces, ensuring flexibility and scalability.

AI models can be optimised for local devices such as smartphones, 

, and on-premise systems. This approach reduces latency and enhances real-time processing by limiting dependence on cloud-based computing.

Businesses can use a combination of cloud-based AI and local processing to balance performance and cost-efficiency. 

 can be leveraged for periodic updates and large-scale model management, while local processing can handle real-time interactions.

AIaaS platforms offer flexible pricing structures, allowing businesses to pay based on usage or subscribe to ongoing AI services.

This model allows businesses to pay only for their AI services, making it a cost-effective choice for startups or companies with fluctuating AI requirements.

For businesses that require consistent AI functionalities, subscription plans provide access to AI services for a fixed monthly or annual fee, ensuring predictable costs.

Some AIaaS providers offer free-tier access to basic AI functionalities, allowing businesses to experiment with AI tools before committing to full-scale deployments. This is particularly useful for startups and developers exploring AI integration.

Continuous AI Model Updates and Enhancements

AIaaS providers regularly improve AI models to ensure businesses benefit from the latest AI-driven automation, analytics, and decision-making advancements.

AI models continuously evolve with new data inputs, improving accuracy and adaptability to changing market conditions. Regular updates enhance performance and enable AI to remain relevant over time.

Cloud-based AI platforms apply regular security patches and compliance updates to safeguard AI models against vulnerabilities. These platforms adhere to global data protection regulations, ensuring secure AI operations.

AI models learn from real-world interactions and user feedback, enabling continuous refinement. This iterative improvement enhances 

, fraud detection, recommendation engines, and other business applications.

AIaaS solutions can be categorised into different types, each serving distinct business needs such as machine learning, natural language processing, computer vision, predictive analytics, and automation.

Below is a detailed explanation of the major types of AIaaS solutions, their use cases, and real-world applications.

Machine Learning as a Service (MLaaS) provides businesses with cloud-based machine learning tools for data analysis, automation, and decision-making. Instead of developing ML models from scratch, companies can use pre-trained models or train their own using AIaaS platforms. These services simplify ML adoption by offering user-friendly interfaces, drag-and-drop tools, and scalable infrastructure.

MLaaS works by providing AI-powered models for various applications such as fraud detection, recommendation engines, and predictive analytics. Businesses can use pre-trained models or upload their own data to refine them for specific needs. This allows even non-technical users to leverage machine learning without deep expertise.

, where banks use AI models for risk assessment and fraud detection. 

 and predictive analytics, while e-commerce companies rely on AI-driven recommendation systems. 

For instance, Amazon SageMaker encourages businesses to build, train, and deploy ML models seamlessly, helping financial institutions detect fraudulent transactions in real-time.

Natural Language Processing as a Service (NLPaaS)

NLPaaS empowers businesses to analyse and process text and speech data using AI. This includes sentiment analysis, speech-to-text conversion, language translation, and chatbot automation. By integrating NLPaaS, companies can extract valuable insights from text-based data and improve customer communication.

NLPaaS operates through AI-powered models that process and interpret human language. Businesses can integrate speech recognition, real-time translation, and chatbot functionalities into their applications to enhance user experiences. Companies in customer service use 

 to handle inquiries, while marketers rely on sentiment analysis tools to monitor brand reputation.

For example, IBM Watson NLP offers AI-powered language processing tools that help businesses analyse customer feedback, detect emotions, and automate multilingual support. A global e-commerce platform can automatically leverage NLPaaS to translate customer inquiries, ensuring seamless communication across different markets.

CVaaS simplifies AI-powered image and video analysis, allowing businesses to implement facial recognition, object detection, and image classification into their applications. Security, healthcare, and retail industries utilise CVaaS for automated visual processing.

CVaaS solutions analyse images and videos to detect patterns, objects, and movements. Businesses use AI-driven facial recognition for authentication, while e-commerce companies implement image-based searches for product discovery. Healthcare providers use AI-assisted diagnostics to analyse medical images more accurately.

One example is Microsoft Azure Computer Vision API, which provides businesses with AI-powered image recognition and tagging. A security company can integrate CVaaS into its surveillance system to detect unauthorised access and monitor suspicious activity in real-time.

Predictive Analytics as a Service enables businesses to use AI-driven insights to forecast trends, detect anomalies, and optimise decision-making. This service is widely used in finance, marketing, healthcare, and logistics to improve efficiency and risk management.

AI models analyse historical data to identify patterns and make accurate predictions. Businesses can use predictive analytics for credit risk assessment, demand forecasting, and customer retention strategies. AI-powered analytics tools help organisations make data-driven decisions with real-time insights.

For example, Google Cloud AutoML Tables allows companies to create AI-powered forecasting models. A logistics company can leverage predictive analytics to optimise delivery routes, reduce fuel costs, and anticipate supply chain disruptions.

AI-powered chatbots and virtual assistants automate customer interactions, provide instant support, and enhance user experiences. Businesses use AI chatbots to handle inquiries, schedule appointments, and assist with transactions, reducing the need for human intervention.

These chatbots process user inputs using NLP models and respond in real-time. Virtual assistants continuously improve by learning from past interactions and providing more accurate and personalised responses. Companies integrate AI chatbots into websites, mobile apps, and messaging platforms to offer 24/7 customer service.

Google Dialogflow powers AI-driven conversational agents that businesses use to automate customer support. For example, a telecommunications company can implement an AI chatbot to assist customers with billing inquiries, reducing wait times and improving service efficiency.

Robotic Process Automation (RPA) with AI helps businesses automate repetitive and rule-based tasks, improving operational efficiency and reducing human errors. It is widely used in 

, HR, customer service, and supply chain management.

AI-powered RPA automates data entry, invoice processing, and document management tasks. Businesses can integrate AI-driven bots with existing software to streamline workflows, saving time and resources. Intelligent automation enhances decision-making by allowing AI to adapt to new data patterns and exceptions.

For example, UiPath’s AI-powered RPA solutions help companies automate financial document processing. A corporate finance department can use RPA to approve invoices, detect inconsistencies, and minimise errors, improving overall productivity.

As artificial intelligence continues to evolve, AI as a Service (AIaaS) is expected to experience significant advancements, making AI more accessible, scalable, and intelligent across industries. The future of AIaaS will be shaped by technological breakthroughs, automation, security improvements, and expanded industry applications. 

Below are the key trends and innovations defining the next phase of AIaaS:

AI-Driven Automation and Autonomous AIaaS

AIaaS platforms are transitioning towards self-learning AI models capable of automating workflows without human intervention. Future AI systems will execute tasks and optimise their performance, reducing the need for manual retraining. 

Automated Machine Learning (AutoML) will streamline AI model development, allowing businesses to implement AI solutions with minimal expertise. Additionally, autonomous AI agents will take over complex decision-making, analysing real-time results and refining strategies independently.

AIaaS is shifting away from cloud-only models to edge computing-based AI deployments, allowing AI processing to occur closer to the data source. This approach particularly benefits IoT devices, autonomous vehicles, and real-time security systems, where speed and efficiency are critical.

To facilitate this shift, AIaaS providers will optimise AI models for local execution on smartphones, industrial sensors, and embedded systems. These compressed AI models will operate with minimal power consumption while maintaining high processing capabilities.

Additionally, businesses will deploy hybrid AI systems that balance cloud computing for large-scale data processing and edge AI for instant decision-making.

AI increasingly merges with blockchain technology and DeFi, enhancing financial transactions' security, automation, and transparency. One major innovation is AI-powered 

, which will become more adaptive and self-executing, responding dynamically to real-time conditions.

Another significant application will be fraud detection and risk analysis in cryptocurrency transactions, where AI models will identify fraudulent activities through pattern recognition and anomaly detection. 

AIaaS will also support decentralised AI models, assuring that data privacy and security are preserved while enabling AI-driven analytics.

AIaaS in Explainable AI (XAI) and Ethical AI

As AI adoption expands, transparency and fairness are becoming key concerns. AIaaS providers now focus on 

 (XAI), ensuring that AI-driven decisions are interpretable, accountable, and bias-free.

Future AIaaS platforms will provide interpreter tools that explain how AI models reach decisions, improving user trust and regulatory compliance. In addition, bias detection frameworks will help businesses identify and correct unfair AI predictions, ensuring AI systems are free from gender, racial, and economic biases.

Quantum AIaaS – The Intersection of Quantum Computing and AI

Quantum computing is set to revolutionise AIaaS by exponentially improving AI's ability to process large datasets, optimise algorithms, and enhance encryption. Future AIaaS platforms will integrate quantum-powered AI model training, enabling machine learning systems to analyse complex datasets at unprecedented speeds.

Quantum cryptography will also enhance AI security, allowing AI-driven communications to be quantum-encrypted, making them virtually unbreakable. 

Additionally, AIaaS platforms will enable AI-driven quantum simulations, helping industries like drug discovery, climate modelling, and financial analytics leverage quantum computing for advanced research.

AIaaS for Hyper-Personalisation and Adaptive AI

AIaaS is evolving towards adaptive AI systems capable of dynamically adjusting AI-driven recommendations, services, and interactions based on real-time user behaviour. AI-powered personal assistants will become more intuitive and capable of understanding user emotions, context, and preferences to provide human-like interactions.

Future AIaaS platforms will also support self-learning personalisation systems, where AI models adjust recommendations based on continuous feedback. This will significantly improve customer engagement, e-commerce suggestions, and digital marketing by delivering tailored, context-aware experiences.

Adaptive AI will also play a key role in content creation, education, and entertainment, enabling AI-driven systems to generate dynamic content, personalise learning experiences, and provide real-time adjustments based on user interactions.

AIaaS for Cybersecurity and Threat Detection

With cybersecurity threats on the rise, AI-driven security solutions are becoming essential for protecting digital infrastructures. AIaaS will be critical in cyber defence, enabling real-time threat detection and automated responses to security breaches.

AI-powered intrusion detection systems will instantly identify and mitigate 

, while automated security response mechanisms will neutralise cyberattacks before they cause damage. 

AIaaS will also introduce self-healing security systems, where AI continuously detects vulnerabilities, applies security patches, and strengthens defence mechanisms without human intervention.

AI as a Service (AIaaS) is revolutionising AI adoption by offering scalable, cost-effective, and easy-to-integrate AI solutions. From cloud-based automation to edge AI and blockchain-driven AI marketplaces, the future of AIaaS is brighter, faster, and more accessible than ever.

As AIaaS evolves, businesses embracing AI-powered automation will gain a strategic edge, leveraging AI-driven decision-making, predictive insights, and adaptive AI solutions. 

Whether you're exploring AIaaS companies, business models, or real-world AIaaS case studies, now is the time to consider AI-as-a-Service for your needs.

What is AI as a Service (AIaaS)?

What are some AIaaS examples?

What is the AI as a Service business model?

How do AIaaS companies improve AI models?

How is generative AI used in AIaaS?

AI as a Service (AIaaS) — What Is It And How Does It Work?

As a hard-working, goal-oriented, and well-rounded person, I always strive to do quality work for every job I do. Faced with challenging tasks in life, I have developed the habit of thinking rationally and creatively to solve problems, which not only helps me develop as a person, but also as a professional.

Speaking about my professional activities, I can say that I have always been attracted to the study of foreign languages, which later led me to the study of translation and linguistics. Having great experience as a translator in Russian, English and Spanish, as well as good knowledge in marketing and economy, I successfully mastered the art of copywriting, which became a solid foundation for writing articles in the spheres of Fintech, Financial markets and crypto.

Constantine Belov

B2BROKER has just launched a short series of videos specialising in the China market. The videos are designed to help brokerage businesses understand the complexities of dealing with the world’s most populous nation when it comes to regulations and government restrictions.

<p>  	 As we know, foreign exchange trading in China has been restricted by tight cross-border capital controls and a ban on currency margin trading. What forex operations that do exist are subject to strict regulations. With China’s FX market crackdown, conducting business there can often be unclear and fraught with obstacles, but with governmental and regulatory changes on the horizon, the future of Forex and doing business in China is looking a lot brighter.  </p>  <p>  	 Our videos give a brief introduction to B2BROKER and the China market and are introduced by CEO Arthur Azizov in 3 parts.  </p>  <p>  	 The first is a short overview of B2BROKER in which Arthur talks about how helping the company’s clients achieve success is a measure of the company’s success as well as sharing his company philosophy in 30 seconds.  </p>   <iframe loading="lazy" title="Arthur Azizov, CEO and Founder of B2BROKER about B2Broker`s philosophy in 30 seconds" width="1280" height="720" src="https://www.youtube.com/embed/98MxB9w92Tg?feature=oembed" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="">  </iframe> <br>   In the second video of the series, Arthur talks about the differences involved in marketing a business in China and the challenges faced in terms of regulations. He explains the necessity for a different approach and how the way business is conducted should be adapted in accordance with specific market conditions.<br>   <br>   <iframe loading="lazy" title="How to Market your Business in China" width="1280" height="720" src="https://www.youtube.com/embed/U-yq_ksPi7U?feature=oembed" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="">  </iframe> <br>   Arthur rounds up by talking about the Chinese government, the future of digital RMB and the company’s plans to further expand into the Chinese market. He concludes by elaborating on government monetary policies and how plans for China as the first country to launch its own sovereign digital currency will play a big part in the mass adoption of crypto.<br>   <br>   <iframe loading="lazy" title="Arthur Azizov about Chinese government, the future of digital RMB and B2Broker`s Plans" width="1280" height="720" src="https://www.youtube.com/embed/_CWANPoRbcA?feature=oembed" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="">  </iframe> <br>  <p>  	 A real insight into the China market, the videos provide a quick and easy-to-understand introduction to the China market that are ideal for companies new to, or thinking about starting out in this prosperous region.   </p>  <p>  	 Watch them <a href="http://www.youtube.com/playlist?list=PL0ZjomsTymbfo-fh3VioEwzTD8zyToMBZ" rel="nofollow noopener noreferrer" target="_blank">here</a>!  </p>   <br>   <br>

B2BROKER Launches New Video Series On Forex Business in China

Forex trading is big business. In 2019 alone, the global foreign exchange market saw an average daily turnover of $6.6 trillion, yet it continues to present opportunities for even more growth. Due to the vast amounts of money involved, the forex market is highly regulated with the introduction of stricter rules and regulations which have come into force to protect all parties concerned. <br /> 

<p>These regulations have important implications as far as brokerages are concerned, especially when it comes to onboarding clients. While a brokerage’s primary aim is to onboard more clients and increase revenue, it is at the same time also necessary to comply with regulations to prevent fraud.</p><h3 class="wp-block-heading">How Regulations Impact Brokerages</h3><p>Due to the substantial interest in forex trading across the globe, brokerages are subject to regulations depending on the regions or countries that they operate in. For brokerage businesses, the regulations which directly impact client onboarding are Anti-Money Laundering (AML) and Know Your Customer (KYC).</p><p>These regulations require companies to carry out forex account verification procedures i.e. due diligence on their clients in order to verify their identity. In doing so, the brokerage can determine whether a customer is who they say they are. Screening processes involving checking their names against AML watchlists also help ensure that they haven’t been involved in financial crimes such as money laundering.</p><h3 class="wp-block-heading">Know Your Customer (KYC) Requirements</h3><p>All brokerage companies are obliged to subject any clients they are onboarding through a KYC process. KYC is a common process where proof of identity is required to verify the identity of clients. This will require them to provide some sensitive personal data to the brokerage in order to open a new trading account and start trading. Failure to meet these requirements may otherwise result in deposit and withdrawal issues.</p><p>Each brokerage will have their own set of requirements regarding the kind of documents they will request. Some brokers have strict KYC requirements while others may be more flexible.</p><p>Brokers regulated by CySEC, for example, have become a lot stricter with KYC regulations in recent years following the introduction of the MIFID II directive. Offshore brokerages, however, tend to be more lenient with their requirements.</p><h3 class="wp-block-heading">Typical KYC Requirements</h3><p>A set of verification documents will be required to confirm the client’s identity and financial status. Typical KYC documents for forex that may be requested include a passport or national ID card to prove the true name of the client, date and place of birth, a recent utility bill to confirm home address and phone number, email address, sample signatures and other financial information such as purpose for opening a trading account, source of funds, etc. </p><p>To make the process as pain-free as possible, brokerages should ensure that they are able to provide their clients with a user-friendly client area. Many brokerages do this via B2CORE where they can quickly submit all the relevant documents for the verification process and complete the forex registration process with ease. </p><p>As it is an obligation to carry out these procedures in accordance with the relevant regulator, it is essential that as a brokerage, you offer your clients an effective forex verification service in order to do so.</p><h3 class="wp-block-heading">Get Verified Quicky and Dependably</h3><p>B2BROKER offers its clients the means to quickly and dependably verify their customers’ ID by offering integration free of charge with industry leading KYC providers such as Identitymind and Sum&Sub. This provides a full-proof way for conducting all the KYC and AML compliance necessities, together with conducting identity proofing, risk-based authentication, regulatory compliance and the prevention of identity fraud.</p><p>Industry regulations are now tougher than ever and in order to be compliant and protect all parties involved, KYC procedures are of prime importance to all brokerage businesses. If you are thinking about launching a brokerage or require assistance with any aspect of forex broker verification, <a href="mailto:sales@B2BROKER.net" target="_blank" rel="noopener noreferrer">contact us </a>today.</p>

Why KYC is Important for Brokerage Companies

B2Broker’s customised version of Devexperts dxTrade combined with its technology and deep liquidity has culminated in an unmatchable offering in the industry.

<p>B2BROKER, a leading liquidity and technology provider of solutions to the Forex and crypto industry, has signed an agreement with Devexperts, a financial software developer, to license their dxTrade platform. dxTrade is a multi-asset trading solution for brokers which, unlike other existing OTC trading platforms, supports the entire spectrum of assets. This feature will allow B2BROKER to become the leading Prime of Prime liquidity provider in the industry.</p><p>B2Broker’s pool of trading platforms currently includes OneZero Hub, PrimeXM xCore, several MT4 and MT5 trading platforms, together with B2TRADER (the company’s own Matching Engine platform). With the addition of dxTrade, clients will be able to gain quick and easy access to one of the deepest liquidity pools in the industry for Stocks/Equities, ETFs, CFDs, Futures, Vanilla Options, Commodities, Metals, Forex, Crypto Futures, Crypto Spot, Crypto CFD and Bonds. </p><p>The company, which recently expanded its Crypto CFD liquidity offering with the addition of 61 new crypto pairs, now totalling 100 pairs, is recognised as being one of the industry’s leading LPs, offering the highest level of support with 24/7 trading and support in English, Russian, Chinese Cantonese and Simplified, Arabic, Spanish, Hindu, Italian, Urdu, Farsi, Pashto, Hebrew and Turkish.</p><p>B2BROKER recently completed its integration with the dxTrade platform in order to spread liquidity amongst brokers who already use dxTrade, and to offer it to newly established or expanding brokers. From now on, they will be able to connect to one of the largest liquidity pools in the industry in just one minute through FIX API or by connecting to dxTrade directly. </p><p>Moreover, B2BROKER has integrated B2CORE with dxTrade. B2CORE, the new name for Trader’s Room, is a ready-made functional solution for brokerages which allows clients to verify and register customers and perform functions such as accepting and sending payments, make deposits and withdrawals and open accounts, etc. Companies who use the dxTrade platform can quickly get connected to B2CORE prior to launching their own brokerage business.</p><p>Finally, the company’s cryptocurrency payment gateway, <a href="https://B2BINPAY.com/" target="_blank" rel="noopener noreferrer">B2BinPay</a>, has also been integrated with dxTrade, enabling clients to securely and cost-effectively send, receive, store, exchange and accept cryptocurrency payments online. </p><p>Arthur Azizov, Founder and CEO of B2BROKER commented, “Our goal to become a global Prime of Prime liquidity provider became a reality thanks to our tailored version of dxTrade which, in combination with our technology and depth of liquidity, makes our offering unmatchable in the industry.”</p><p>Evgeny Sorokin, SVP of Software Engineering, Devexperts added: “We are pleased that B2BROKER has chosen our modular multi-asset trading platform. dxTrade can be configured to serve different clients in different markets and I am certain that our technology will assist B2BROKER with their expansion.”</p><h3 class="wp-block-heading"> </h3><h3 class="wp-block-heading">About B2Broker</h3><p>B2BROKER is a liquidity and technology provider of solutions for the crypto and foreign exchange industry. The company specialises in the sphere of B2B services and products, catering for a wide range of clients including large licensed brokers, crypto exchanges, crypto brokers, forex brokers, hedge and crypto funds and professional managers.</p><p>B2Broker’s advanced base of ready to use technical solutions enable brokers to save time and money on consuming infrastructure projects and focus on enlarging their client base and increasing their revenues.</p><h3 class="wp-block-heading"> </h3><h3 class="wp-block-heading"> </h3><h3 class="wp-block-heading">About Devexperts</h3><p>Devexperts specializes in the development of tailored software solutions for the Capital Markets industry with clients including retail and institutional brokerage houses, exchanges, and wealth management firms. Devexperts are the developers of the thinkorswim platform and numerous recognized and reliable financial applications, with millions of traders using their technology daily. The services from Devexperts include low-latency market data feeds, AR/VR data visualization, AI digital assistants, deep learning, and market analysis.</p>