Our comprehensive research on AI drives and validates our consulting services enabling our clients to
Reduce the time, effort and resource invested in research
Understand of the scope of the technology and its relevance to the business.
Make informed decisions
What was once a fictional concept, thought of mainly for entertainment, Artificial Intelligence (Al) is now shaping the future of businesses. Al is still in its nascent stage, and we are in the process of authoring a comprehensive research report to demystify the concept for our clients.
The comprehensive report will cover various possible use cases, available tools, end-users stories, vendors and service providers, and lessons learned. The brief AI report is a preview of the comprehensive report.DOWNLOAD NOW
When adopting a new technology, there is always some uncertainty and skepticism within any organization. We understand our clients' requirements and enable them to make informed decisions on how to proceed with their AI journey.
Our advisory practice focuses on providing critical insights and methodologies for both enterprise buyers and service providers in AI.
We work as a part of our clients' team during the implementation phase to ensure a seamless transition. Our implementation process includes scripting, IT architecture, setting security standards, mitigating risks and identifying potential gaps. Our fixed pricing model is charged per process and is based on successful outcomes.
Bluemix training and deployment
Management of APIs
Development andImplementation of Chatbots
AI or Artificial Intelligence is a computer science branch that creates algorithms and systems to perform human-like tasks such as perception, reasoning, learning, and problem-solving. Its technology includes machine learning, natural language processing, computer vision, robotics, and cognitive computing. Automation, on the other hand, automates manual or repetitive tasks through technology, often using rule-based systems such as RPA. While RPA automates rule-based tasks, AI focuses on creating systems that learn from data to recognize patterns and make decisions. AI algorithms analyze data to make predictions and improve their performance over time. Unlike RPA, AI creates systems that learn and improve their performance.
There are multiple possibilities of RPA implementation. A few of them are : Data entry and processing: AI can automate data entry and processing tasks, such as data extraction from documents and databases, data cleaning, and data classification. Customer service: AI can automate customer service tasks, such as answering frequently asked questions, providing product recommendations, and handling customer complaints. Predictive analytics: AI can automate predictive analytics tasks, such as forecasting future trends, identifying potential risks, and detecting anomalies in data. Image and speech recognition: AI can automate image and speech recognition tasks, such as identifying objects in images, transcribing speech, and translating languages. Chatbots: AI-powered chatbots can automate tasks such as customer support, lead generation, and appointment scheduling. Financial analysis: AI can automate financial analysis tasks, such as identifying patterns in financial data, detecting fraud, and predicting market trends. Manufacturing: AI can automate manufacturing tasks such as quality control, predictive maintenance, and inventory management. Healthcare: AI can automate healthcare tasks such as medical image analysis, patient monitoring, and drug discovery.
Enhancing Decision-Making: AI can analyze large amounts of data quickly and accurately, allowing businesses to make more informed decisions. This can help businesses identify patterns, trends, and insights that might be missed by human analysts. Personalizing Customer Experiences: AI can help businesses tailor their products and services to individual customers. This can include personalized recommendations, targeted marketing, and customer service that adapts to each customer's needs. Improving Efficiency: AI can help businesses optimize their processes, reduce waste, and increase productivity. For example, AI can help businesses optimize their supply chain by predicting demand and optimizing inventory levels. Enhancing Security: AI can help businesses identify and prevent security breaches by detecting anomalies and suspicious activity. This can help businesses protect sensitive data and prevent financial losses. Reducing Time: RPA helps businesses reduce time by automating repetitive and rule-based tasks, increasing process efficiency and productivity.
Automation: AI can automate repetitive, manual tasks, and processes, enabling organizations to reduce costs, improve efficiency, and free up time for higher-value tasks. Personalization: AI can help organizations personalize products, services, and experiences based on customer preferences and behavior, leading to improved customer satisfaction and loyalty. Decision-making: AI can help organizations make data-driven decisions by analyzing large amounts of data and providing insights that humans may not be able to identify, leading to better decision-making and improved business outcomes. Efficiency: AI can help organizations optimize operations and processes by identifying areas of improvement, reducing waste, and streamlining workflows. Accuracy: AI can improve the accuracy of tasks such as data entry, data analysis, and quality control, leading to fewer errors and better outcomes. Predictive capabilities: AI can help organizations predict future outcomes based on historical data, leading to better forecasting, risk management, and resource allocation. Personal assistance: AI-powered personal assistants and chatbots can provide personalized assistance and support to customers, leading to improved customer satisfaction and
As AI becomes increasingly integrated into business operations, it is important for companies to consider the ethical and responsible implications of its use. Here are some key practices that businesses can adopt to ensure the ethical and responsible use of AI: Transparency: Businesses should be transparent about how they use AI, what data is being used, and how decisions are made. This can help build trust with customers and stakeholders. Fairness: AI systems should be designed and trained to be fair and unbiased, avoiding discrimination based on race, gender, age, or other factors. Privacy: Businesses should respect individuals' privacy and ensure that data collected through AI systems is properly secured and used only for its intended purpose. Accountability: Businesses should be accountable for the outcomes of AI systems and should take responsibility for any harm caused by these systems. Human Oversight: AI systems should be designed to be transparent and interpretable so that humans can understand how decisions are being made. Humans should also monitor and evaluate AI systems to ensure they are functioning as intended. Continuous Improvement: AI systems should be regularly reviewed and improved to meet ethical and responsible standards. Collaboration: Businesses should collaborate with experts in AI ethics and engage with stakeholders to understand their concerns and perspectives on using AI.
Yes, it can be customized. Data Collection: AI models require large amounts of high-quality data to be trained effectively. Customization can involve identifying the specific data sets that are relevant to your business and training AI models on those specific data sets. Algorithm Design: AI algorithms can be designed to suit specific business needs, such as detecting fraud or predicting demand. Customization can involve selecting or creating algorithms that are optimized for your business use case. Integration: AI can be integrated into existing business systems for optimal functionality and seamless operation, including customization through integration with existing syste