AI consulting services Archives

Ankush Sharma
June 23, 2025
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PoC vs MVP in AI – Your Guide to Strategic Project Launch

There are different ways to convert an idea into a new product, such as proof of concept, minimum viable product, prototyping, etc. Here, we’ll discuss the difference between PoC vs. MVP and the right approach for AI implementation. Artificial intelligence-powered solutions offer various advantages to businesses across industries. AI tools streamline internal processes, automate recurring tasks, save resources, and reduce employee workload. According to Grand View Research, the global AI market is valued at $391 billion and is expected to reach $1.81 trillion by 2030 at a CAGR (compound annual growth rate) of 35.9%. AI adoption and implementation have grown by leaps and bounds during the last few years. Another report shows that 9 out of 10 businesses use AI as it gives them a competitive edge. As per Statista, the AI market in the US alone is worth $75 billion and is projected to grow at a CAGR of 26.91% by 203. With such statistics, it’s clear that artificial intelligence has become an integral part of the business world. Organizations have either implemented AI or are implementing it as a part of their five-year plans. Many are releasing new AI products into the market to provide enhanced services to customers and attract new customers to the business. AI implementation is a complex and sophisticated process that requires careful strategic planning, skills, knowledge, expertise, and access to the right technologies. Typically, there are two ways to introduce an AI product into the market. The first approach results in creating a proof of concept before full-scale implementation or launch, while the latter deals with using a minimum viable product that consists of the basic features and functionalities. So, which method is the best choice? Between PoC vs. MVP, which AI implementation is the right approach? Read to find out! What is Proof of Concept (PoC)? Proof of Concept (PoC) is the process of assessing whether an idea, design, or plan for a product (software, mobile app, AI tool, etc.) is feasible or not. Though PoC is not a compulsory part of product development, it can help clarify your doubts or answer a few questions about whether the product would work in real life. Typically, AI PoC development is useful to reduce risks, clear ambiguity, and make a decision about investments. By using PoC, you can choose the best technology stack for the product you want to develop. After all, no business wants to lose money through failed products, isn’t it? Proof of concept is not a complete project. It is not about creating a prototype. PoC is more useful for internal decisions and discussions for the teams to determine the next step. That doesn’t mean PoC projects are handled only by in-house employees. You can ask the AI product development company for proof of concept before you say yes to a full-scale project. The key characteristics of PoC are listed below: What is Minimum Viable Product (MVP)? Minimum Viable Product is a product that has just enough features to be used by real people (alpha and beta testers, etc.) to understand how it works, whether it serves the required purpose, and what can be done to improve its effectiveness. Frank Robinson coined the term, while Eric Ries made it popular in his book a decade later. AI MVP development can be defined as a continuation of prototyping, as it creates a usable version of the software product, even if it has only the basic or the most important features. Like the proof of concept, MVP is not mandatory. However, it is helpful when you want to understand your target audience and take their feedback. It includes processes like monitoring user behavior, data collection, and analytics. MVP also helps make data-driven decisions, but is focused on how to improve the product. Companies offering product development as AI as a service (AIaaS) solutions assist enterprises test their ideas directly in the market while controlling risk and cost factors. The key characteristics of MVP are as follows: PoC vs MVP: What to Choose for Your Business Now comes the big question of choosing between PoC vs MVP. Which of these approaches is the right choice for your AI product development? How can you determine if the AI development process should include the proof of concept or the minimum viable product? Let’s find out here. When to Choose Poc? In AI project management, proof of concept is an early-stage process that determines whether you can continue with the project or not. Choose PoC in the following circumstances: When to Choose MVP? You create a minimum viable product during the later stages of AI or LLM product development. It doesn’t clash with the PoC stage, nor does it replace it. Choose MVP in the following conditions: As you can see, PoC and MVP have different focuses, purposes, and uses. One cannot be substituted for the other. Though both help in reducing risks, their goals and objectives don’t align. Choose PoC when you are uncertain and in doubt about the project itself. However, go with the MVP approach if you want to ensure the AI product becomes a hit with the target audience. Nevertheless, both approaches require clear planning, objectives, and timelines to deliver the required results. PoC vs. MVP Differences Table Proof of Concept (PoC) Minimum Viable Product (MVP) Focus Proof of feasibility or validity Creating a basic version of the product with core features Purpose Determine the feasibility of the product Get user feedback to improve the product Duration/ Timeline Takes a few days Takes a few months Development Stage In the early stages of product development In the later stages of product development User Group Internal teams External users Investment Minimal investment Moderate investment Conclusion Proof of concept and minimum viable product have their advantages and disadvantages. There’s no one-size-fits-all solution when developing AI products. The right approach depends on your specifications, budget, technical feasibility, user feedback, etc. Talk to a reputed and experienced artificial intelligence consulting company to discuss your

Ankush Sharma
June 18, 2025
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Top Finance AI Chatbots for 2025 & How to Build Yours?

AI chatbots in the finance industry are useful for diverse purposes. They are efficient, cost-effective, scalable, and user-friendly. Here, we’ll discuss the top finance AI chatbots and how to build one for your business. The finance and banking industry has been embracing new technology to streamline various activities and offer personalized products and services to customers. Artificial intelligence is becoming a part of many banks and financial institutions to automate repetitive tasks, develop better financial products, and enhance customer experience through AI chatbots. Statistics show that the global AI in finance market is projected to reach $73.9 billion by 2033 at a CAGR of 19.5%. A finance AI chatbot can be used for customer services, financial planning, advice, analytics, etc. It can help employees and customers in different ways. However, you must determine the purpose of using the AI chatbot to customize it and get greater returns. In this blog, we’ll look at the top finance AI chatbots used by businesses and find out how you can create a robust and reliable chatbot that aligns with your requirements. What is a Finance AI Chatbot? A finance chatbot is an artificial intelligence-powered virtual assistant software app. Typically, machine learning, natural language processing, deep learning, etc., are also used to create the chatbot. Some chatbots are built on large language models to offer advanced services. They are meant to understand input queries and provide a relevant and helpful output, or accept a command and follow the instructions. Finance AI chatbots for customer service have become popular in recent times as they offer 24*7*365 services on behalf of the business. Customers also find it easier to interact with a chatbot that quickly answers their queries. You may already use a CRM and ask if you can integrate an AI chatbot with it to handle financial client queries. Yes. The best thing about AI chatbots is that they can be integrated with various third-party software and applications. By combining the finance AI chatbot with CRM, you can provide enhanced services to customers, reduce overhead costs, automate recurring tasks, and reduce the risk of fraud through predictive analytics and fraud detection. You can use existing finance chatbots or get a new one built from scratch by partnering with an AI company offering tailored generative AI consulting services to clients from the finance and banking industry. The advantage of getting your own AI chatbot is that it will be customized to align with your business mission, goals, and objectives and fine-tuned your your data to give more accurate and reliable results. This leads to higher customer satisfaction and greater revenue. Top Finance AI Chatbots in 2025 The finance industry uses AI chatbots that are built to align with the industry standards as well as general powerful chatbots meant to provide support to businesses from various sectors. We’ll look at both options in this section. AlphaChat AlphaChat is an AI chatbot for customer service. It is customized for finance and other industries based on clients’ specifications. As a conversational AI chatbot, it automates customer service by 65% and provides an average of 70% accuracy in answering their questions. AlphaChat can be integrated with various third-party software applications and scaled as required. The interface can be designed to be more interactive and engaging. Kasisto Kasisto (KAI) is a powerful finance AI chatbot for financial planning, personalizing experiences, predictive customer engagement, etc. The chatbot answers 90% of the questions and provides innovative customer experiences. KAI-GPT, developed by the company is among the leading LLMs built for the finance industry. It not only helps customers but also assists agents, employees, and others. Kasisto can be integrated with other tools in a few minutes. Kore Kore.ai is an AI chatbot and virtual assistant for streamlining workflow, providing customer service, and automating processes. It can be used for frontend (customer care) and backend (employees) requirements. Additionally, it has automated 75% of activities, while providing 95% accuracy and saving millions of dollars for financial institutions. Kore.ai would be a great choice for finance AI chatbots for financial advice, expense tracking, customer support, automated accounting, and more. Haptik Haptik is a conversational AI chatbot offering services as a support agent, lead qualification agent, and booking agent. With multilingual support and the flexibility to choose the foundation model, the chatbot can be customized for the diverse requirements of banks and financial institutions. It provides omnichannel engagement through smart recommendations and greater accuracy. Haptik is used by over 500 leading enterprises as it provides end-to-end automation of customer journeys with the business. Microsoft Bing AI Bing AI is a powerful generative AI chatbot developed by Microsoft. It is integrated with all other Microsoft solutions as well as third-party software. Though the chatbot is meant for general purposes, it can be used as a finance AI chatbot for small businesses and startups that cannot invest more money into building tailored solutions. From automation to customer engagement and data creation, Bing AI can do it all. How to Build a Custom Finance AI Chatbot for Your Business? Many businesses want to know if they can get large language model consulting to build a finance-specific chatbot for their enterprise. The answer is yes. You can get an LLM model built exclusively for your business, trained on your proprietary data for the best results. In fact, some banks and financial institutions are already using custom-built chatbots, while a few others have initiated the process. The global FinTech market was $340.10 billion in 2024 and is expected to grow at a CAGR (compound annual growth rate) of 16.2% to reach $1,126.64 billion by 2032. This shows how quickly the finance industry is adopting new technologies. Here’s how you can build finance AI chatbots for your enterprise: List Your Requirements Before you invest in AI chatbot solutions, it’s vital to know what you want from them. The chatbots have different uses and deliver better outcomes when they are trained for specific purposes. For example, the AI chatbot used for customer

Yashica Chopra
December 15, 2024
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AI as a Service – A Bold Move in 2025?

Artificial intelligence as a service (AIaaS) is a cloud-based solution for enterprises to invest in advanced technology. Here, we’ll discuss AIaaS, its role in today’s market, and how businesses achieve their goals by partnering with AI service providers. The adoption rate of artificial intelligence has increased multifold over the years. Many businesses, be they startups or established enterprises, are investing in AI in varied ways to gain a competitive edge and survive volatile market conditions. According to Grandview Research, the AI market is likely to experience an annual growth rate of 37.7% between 2023 and 2030. A report by Markets & Markets shows that the global AI market is predicted to reach $1.3 trillion by 2030. Fortunately for businesses, nonprofits, and government agencies, any organization can adopt AI technology on any scale. It can be a tiny part of your business process or be 100% integrated into all processes across the departments and verticals. Moreover, artificial intelligence services are diverse and customizable. Naturally, this led to a relatively new cloud-based AI offering called AI as a service (AIaaS). This is more convenient, budget-friendly, and effective compared to large-scale AI adoption and implementation. But what exactly is AIaaS? What does an AI services company do to offer artificial intelligence as a cloud service? Will it be a worthy choice for businesses in 2025? Let’s find out! What is the AI Model as a Service? AI as a service (AIaaS) is a new business model where service providers offer artificial intelligence-based solutions through a cloud platform. Instead of setting up the AI tools/ apps on-premises, the software is hosted on a remote cloud server and accessed by users whenever necessary. All technologies and tools under the umbrella term AI are available on the cloud. Be it machine learning algorithms, natural language processing (NLP) models, large language models (LLMs), generative AI apps, computer vision, advanced analytical tools, etc., can be accessed remotely to get near real-time and real-time results. In the AI as a service business model, you subscribe to use the required tools and software provided by the vendors. You pay only for what to use and not for all the other services offered. Additionally, the pay-as-you-go model allows startups and emerging businesses to save money on unwanted expenses. You can upgrade or downgrade the subscription plan as necessary. Furthermore, there’s no need to invest heavily in building the IT infrastructure in the office. Employees can use their personal devices and work from any location as long as they have been authorized to access the tools. What is the Purpose of AI as a service? As per Global Market Insights, the AI as a service market size is expected to grow at a CAGR (compound annual growth rate) of 28% between 2023 and 2032 and reach $75 billion by 2032. This growth rate can be attributed to the ease of using artificial intelligence as a cloud service. The main purpose of AIaaS is to eliminate the need for unwanted hardware and bring greater flexibility to the business’s IT infrastructure. AI as a service is diverse and can be classified into the following types. Whether you want to implement only one of the above or a combination (and all of them), the AI product development company will create a price plan accordingly and determine the subscription charges. That way, you pay for what you use while ensuring quality, scalability, agility, and personalization are not compromised. Of course, there can be a few concerns like data security, lock-in agreements, and transparency about the core AI systems used. However, these issues are a problem only if you choose a service provider at random. Many reliable companies that offer AI as a service address these concerns proactively. For example, DataToBiz is an ISO-certified AIaaS company that complies with global data regulations and has a transparent pricing model. The developers use existing cloud technologies or build new models based on clients’ requirements. With the right partner, you can vastly benefit from switching to the AIaaS business model. Why You Should Invest in AI as a service? What makes AI as a service a better alternative to implementing artificial intelligence in your business? Check out below. With AIaaS, an organization can quickly build, develop, and release products into the market. The production cycle can be shortened without affecting quality and performance. AI product development in today’s world results in low-code or no-code applications that can be built and customized in a fraction of the time usually required to develop a model from scratch. The drag-and-drop interfaces accelerate time to market and allow you to quickly launch new products before competitors. AI as a service is a long-term solution or an agreement with the service provider. As long as you pay for the subscription, you will get continuous improvements and upgrades offered by the company. In most enterprise price plans, you don’t have to pay extra for troubleshooting, upgrading, or maintenance services. The service provider offers these as a part of the package. Over the years, you gain more from the service and see positive growth in ROI. Advanced technology is not cheap, and not every business has the capacity to buy new tools and software as soon as they are released. What will you do with the existing apps? How many can you buy only to use for a limited period? However, with AI as a service, there’s no need to make huge purchases. You can use the latest tools without buying them outright. That makes it feasible for startups and small businesses to use technology just like large enterprises do. The stakes are lower as you can switch from one service provider to another or use a different platform if the current one doesn’t meet your expectations. As mentioned earlier, AI as a service offers more flexibility in choosing what features, tools, frameworks, and solutions to implement in a business. There’s no need to complicate the systems by trying to use every available option for its own sake.

Yashica Chopra
November 19, 2024
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Fortune 500 Favorites: Top 10 AI Consulting Services Firms

Artificial intelligence is the key to success, but knowing how to use it makes all the difference. That’s where AI consulting companies help. Here, we’ll discuss the top ten AI consulting services firms that work with Fortune 500 companies around the globe. Artificial intelligence is no longer an option for businesses. It is a must-use technology if organizations want to survive market competition and stay active in this ever-changing global scenario. However, every business, big or small, cannot and may not want to build the AI model from scratch or maintain an in-house team of AI experts. In such instances, it makes sense to hire AI consulting services and partner with reputed service providers to integrate artificial intelligence with business processes and embrace digital transformation. This resulted in various firms offering AI consultancy solutions for startups, SMBs, MSMEs, and large enterprises. Even some of the Fortune 500 Companies prefer to collaborate with AI consulting firms to achieve their goals. So, how big is the AI consulting market? Well, according to BCC Research, the global AI consulting services market is expected to touch $64.3 billion by 2028 at a CAGR (compound annual growth rate) of 34.2%. As per Grand View Research, the global AI market is $196.63 billion in 2023 and is estimated to grow at a CAGR of 36.6% from 2024 to 2030. In this blog, we’ll take a look at the top AI consulting companies that work with Fortune 500 businesses and clients from various other industries. What is AI Consultancy? The biggest barrier to AI adoption is the lack of expertise and the cost of building the models from scratch. Choosing the wrong technologies or approach can lead to more challenges and losses instead of empowering the business. But how can an enterprise overcome these issues without increasing expenses? That’s where AI consulting services come into the picture. An AI consulting company is a service provider that assists various businesses in understanding and adopting AI technologies to achieve their goals. From creating the strategy to ensuring long-term maintenance and support, the consulting company has many roles and responsibilities. However, not all firms offer the same services. For example, some AI consultancy companies are limited to strategy formation or tech support. Some companies offer end-to-end support, including AI product development services and staff augmentation services. The top four (Deloitte, EY, PwC, and KPMG) cater exclusively to MNCs and large enterprises and have premium charges. Fortune 500 Companies may prefer to work with such service providers or opt for other leading AI consulting companies. Top 10 AI Consulting Services Firms DataToBiz DataToBiz is a leading AI product development company offering end-to-end and tailored services for clients from various industries, such as manufacturing, finance, EdTech, healthcare, telecommunication, surveillance, logistics, retail and eCommerce, IT, energy, hospitality, and many more. The award-winning company offers full-scale solutions for businesses to address and overcome challenges. Generative AI, NLP, computer vision, ML modeling, etc., are a part of the company’s AI services. Additionally, DataToBiz also offers custom services for data analytics, data engineering, business intelligence, and IT staff augmentation. It is a reliable and cost-effective company providing AI consulting for MNCs, Fortune 500 firms, startups, SMBs, MSMEs, and large-scale enterprises. The company has ISO certification, along with compliance with SOC 2, GDPR, CCPA, DSS, NIST, and HIPPA. From strategy formation to deployment, integration, and maintenance, the experts from the company handle each process with seamless efficiency. Glassdoor Rating: 4.8 Stars IBM IBM is among the top AI consulting companies in the world and works with Fortune 500 firms, multinational companies, and large enterprises. It offers adaptive solutions for clients from healthcare, manufacturing, IT, finance and insurance, marketing, etc. The company uses an open enterprise-grade AI approach to provide flexibility and scalability for clients while prioritizing safety and compliance with holistic AI. Using its decades of experience in the field, the company has developed various artificial intelligence solutions like Watsonx, Granite, and others. IBM’s AI consulting services help businesses redesign workflows and scale the systems quickly using hybrid cloud technologies. Automation, IT modernization, edge computing, data science, ESG reporting, data management, and cloud security are some of the extensive services offered by the service provider. The company’s generative AI services help different departments like customer service, HR, marketing, finance and accounting, etc. It encourages businesses to become more successful using sustainable processes. Glassdoor Rating: 4.0 Stars Accenture Accenture is an AI services company helping various large enterprises and Fortune 500 firms reinvent their processes with data and artificial intelligence. It partners with leading tech providers like Google AWS, SAP, Oracle, Salesforce, etc., to help businesses build a comprehensive ecosystem to streamline their internal systems. The company’s generative AI consulting services are much in demand in the global market along with other services like cloud computing, cyber security, supply chain, sustainability, Metaverse, finance and risk management, and many more. Accenture has a presence in several industries, such as aerospace, banking, capital markets, energy, consumer goods, public sector, insurance, life sciences, etc. It emphasizes responsible AI for businesses to bridge the gap between intention and execution. The company understands the importance of aligning the AI strategy with business requirements and long-term goals. The services are customized to suit each client’s requirements and scaled for large enterprises across all verticals. Glassdoor Rating: 3.9 Stars LeewayHertz LeewayHertz provides AI consulting services and development solutions for enterprises to amplify operational efficiency and streamline workflows. The company works with clients from finance and banking, manufacturing, retail, insurance, hospitality, healthcare, startups, consumer electronics, and other sectors. It offers AI and ML strategy development services, custom app development, Copilot development, AI integration, enterprise AI development, fine-tuning LLMs, data engineering, and generative AI development services. LeewayHertz has expert AI professionals to provide end-to-end development services for Fortune 500 companies, large enterprises, and mid-scale businesses. It prioritizes speedy development and deployment by following agile methodologies. The company’s advanced tech stack makes it easy to complete and deliver projects within the pre-determined schedule without compromising quality or exceeding

Manpreet Kaur
October 15, 2024
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Top 13 AI Implementation Partners to Consider in 2025

As businesses increasingly recognize the importance of AI in driving growth and efficiency, choosing the right AI consulting services partner is important. This blog highlights the top AI implementation partners based on their expertise and industry presence. According to Grand View Research, the global artificial intelligence market was valued at USD 196.63 billion in 2023 and is expected to grow at a CAGR of 36.6% in 2023. As businesses are adopting AI across different industry verticals, it is essential to partner with experienced AI implementation firms that offer the necessary expertise and resources. In this blog, we’ve compiled a list of the top AI implementation partners you must partner with to develop remarkable AI solutions. Top Companies Offering AI Consulting Services in 2025 DataToBiz DataToBiz is a leading AI implementation partner that helps you develop innovative products to solve your business challenges and achieve great results. Their team of experts offers robust AI consulting solutions, such as NLP, product development, and machine learning. The company uses the latest technology stack and offers real-time operational intelligence. Partnering with DataToBiz for AI development ensures you get a business solution that aligns with your objectives. The experts understand your queries, build strategy, collect data, and create models that fulfill the objectives, ensuring efficacy and efficiency. Client Collaborations: Flipkart, ICICI Bank, McDonald’s, NeilsenIQ, NPCI Industries: Manufacturing, healthcare, retail, ecommerce, and IT Average Ratings: 4.7 (Clutch) DataRobot DataRobot has been named a 2024 Gartner Magic Quadrant winner for data science and machine learning platforms. The company specializes in generative and predictive AI solutions and offers a comprehensive suite of tools designed to streamline the AI lifecycle, from data preparation to model deployment and governance. DataRobot offers tailored solutions for various industries like finance, healthcare, retail, and manufacturing. It integrates AI workflows into a single platform, enabling organizations to build, govern, and operate AI solutions efficiently with due consideration to government and compliance. Client Collaborations: MARS, Boston Children’s Hospital, Warner Bros, and Tokio Marine Kiln Industries: Food industry, healthcare, mass media, retail, and financial services Average Ratings: 4.6 (Gartner) Hugging Face Hugging Face Inc. is an American company that offers AI consulting for MNCs. Its main offerings include the Transformers library, which provides a vast collection of pre-trained models optimized that you can use for NLP tasks such as text classification, translation, and summarization. The company offers cloud-based services through its Hugging Face Hub platform, which allows users to host, share, and deploy AI models in the cloud. The platform integrates with machine learning frameworks such as TensorFlow and PyTorch, making it easier for developers to include models in their workflows. Industries: Text generation and classification Average Ratings: 4.0 on Gartner DataTech DataTech is an AI product development company that offers advanced solutions in AI and data analytics. It is popular for its notable work in machine learning, deep learning, and natural language processing. It uses a platform where developers can create contextual chat and offer customizable chat solutions tailored to specific business needs. Datatech is a great partner if you are looking for someone if you are looking for a company to handle image processing and social listening tools. The experts use features such as facial recognition and people counting to process images, making it easy to make valuable decisions. Client Collaborations: IT Motif Inc, Zydus Hospira Oncology, QX KPO Services, Meghamani Dyes and Intermediates Industries: IT, healthcare, BPO, manufacturing Average Ratings: 5.0 (Clutch) InData Labs InData Labs is a data science and analytics consulting firm that offers AI-powered solutions to businesses. It offers advanced and reliable solutions for AI, NLP, machine learning, generative AI, and data engineering solutions. The company offers AI solutions for different sectors, such as advertising, financial services, entertainment, retail, and ecommerce. InData Labs is a certified AWS Partner. The company builds and scales cloud solutions within the AWS ecosystem, solving data and analytics challenges. It offers a collaborative partnership with clients, ensuring easy alignment and communication throughout projects. Client Collaborations: GSMA, Entrance, Naexas, Asstra Industries: Telecommunications, IT, logistics, retail, and ecommerce Average Ratings: 4.9 (Clutch) Markovate Markovate is a generative AI consulting services company specializing in AI and digital transformation solutions. It is known for its modern AI-driven solutions tailored to specific business needs, such as predictive analytics and machine learning applications. The company also offers development services for decentralized applications and blockchain solutions. Markovate’s team has experienced professionals with expertise in mobile technology, AI, blockchain, and digital marketing. They follow a collaborative approach and implement agile methodologies to adapt to changing project requirements. Client Collaborations: Synervoz, Nown, Hawaii Revealed, Aisle24, Trapeze Industries: Software development, IT, travel and tourism, retail Average Ratings: 3.6 (Glassdoor) BrainPool.AI BrainPool.AI is an AI services company that provides comprehensive AI solutions tailored to various industries such as construction, finance, healthcare, real estate, retail, and marketing. It uses AI to empower businesses by using artificial intelligence to enhance operational efficiency and drive innovation. The developers tailor strategies to integrate AI into business operations, create prototypes, and provide expert advice on AI implementation. Some of its other services include custom GPT development, back-office automation, data structuring, design process optimization, data migration, data governance, and design architecture. Client Collaborations: Stair Craft Group, Ocula Technologies, Crown and Paw, Nvidia Industries: Construction, technology, Artificial Intelligence, retail Average Ratings: 4.8 (Clutch) EY (Ernst & Young) EY (Ernst & Young) is an AI implementation giant that offers a wide range of AI consulting services to help organizations use AI to drive growth. The company offers consulting and advisory services to organizations planning to integrate AI into their operations. Some of its core services include strategy development, use case identification, and implementation support for AI solutions. EY also focuses on RPA (Robotic Process Automation) and combines AI with RPA to automate complex business processes, making it easy to make data-driven decisions. It also offers cybersecurity solutions that detect threats, analyze data for unusual patterns, and improve threat response times. Client Collaborations: MNCs, NGOs, and startups Industries: Technology, healthcare, manufacturing, and financial services