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Lightblue Cognitive Solutions offers the following kinds of Artificial Intelligence consulting or custom solution development & implementation services.

generative ai

Generative AI

  • Question & Answer AI Solutions Using Private Corporate Knowledge – AI systems leverage internal corporate databases to provide accurate answers to specific, organization-related queries. This enhances decision-making and operational efficiency. Key Industries: Legal, Healthcare, Finance, Technology.
  • Conversational User Interfaces to Any Existing Application – AI-driven interfaces allow users to interact with software applications using natural language, enhancing user experience and accessibility. Key Industries: Customer Service, E-Commerce, Healthcare, Banking.
  • Personalisation: Personalised Offers & Recommendations for Customers – AI analyses customer data to provide tailored recommendations, improving customer engagement and sales. Key Industries: Retail, E-Commerce, Entertainment, Travel.
  • Generative Workspaces: Enabling Content Creation for Any Knowledge Worker Workflow Activity – AI tools assist in generating documents, presentations, and other content, enhancing productivity and creativity. Key Industries: Marketing, Legal, Consulting, Education.
  • Autonomous Agents – AI agents operate independently to perform tasks, enhancing efficiency and reducing human workload. Key Industries: Manufacturing, Logistics, Customer Service, Transportation.
  • Compliance & Quality Assurance – AI monitors and ensures adherence to regulations and standards, improving accuracy and reducing risks. Key Industries: Finance, Healthcare, Manufacturing, Technology.
  • Research Assistant – AI aids in data gathering and analysis for research, enhancing insights and speeding up the research process. Key Industries: Academic Research, Pharmaceutical, Market Research, Environmental Studies.
  • Data Synthesis & Augmentation – AI generates or augments data sets for training models, enhancing AI development without compromising data privacy. Key Industries: Healthcare, Finance, Automotive, AI Research.
  • Data Analytics & Visualization – AI tools analyse data and present findings visually, aiding in decision-making and insights. Key Industries: Business Intelligence, Finance, Marketing, Healthcare.
  • Coding Assistant – AI assists in writing, reviewing, and debugging code, improving development speed and quality. Key Industries: Software Development, IT Services, Tech Start-ups, Education.
  • Tutor – AI-driven tutoring systems offer personalized learning experiences, adapting to individual student needs. Key Industries: Education, E-Learning, Corporate Training, EdTech.
  • Candidate Screening and CV to Job Description Scoring – AI automates recruitment by matching candidates with job requirements, enhancing hiring efficiency. Key Industries: Human Resources, Recruitment Agencies, Large Corporations, Tech Companies.
  • Automated Financial Reporting – AI generates financial reports, reducing manual effort and increasing accuracy. Key Industries: Finance, Accounting, Corporate Business, Consulting.
  • AI-Driven Investment Strategies – AI analyses market data for investment insights, aiding financial decision-making. Key Industries: Finance, Banking, Wealth Management, Insurance.
  • Customised News and Content Curation – AI personalises news feeds and content for individual preferences, enhancing user experience. Key Industries: Media, Publishing, News Outlets, Content Platforms.
  • Voice-Activated Virtual Assistants – AI powers voice-responsive assistants, aiding in various tasks and information retrieval. Key Industries: Consumer Electronics, Automotive, Smart Home, Technology.
  • Automated Content Moderation – AI moderates user-generated content on digital platforms for guideline compliance. Key Industries: Social Media, Online Forums, E-commerce, News Outlets.
  • Machine Translation – NLP translates text or speech from one language to another, facilitating cross-lingual communication and content accessibility. Key Industries: Travel and Hospitality, International Business, E-Learning, Technology.
  • Text Summarization – NLP algorithms generate concise summaries of lengthy documents, saving time and making information more accessible. Key Industries: Legal, Academic Research, Media, Corporate Communications.
  • Speech Recognition – NLP technology transcribes spoken language into text, enhancing user interfaces and accessibility features. Key Industries: Healthcare (for patient documentation), Customer Service (voice-to-text services), Legal (transcription services), Education.
natural language processing

Natural Language Processing

  • Chatbots & Virtual Assistants – NLP-driven chatbots and virtual assistants interact with users in natural language, providing information, assistance, or performing tasks. This enhances customer engagement and operational efficiency. Key Industries: Customer Service, E-commerce, Healthcare, Banking.
  • Classification – NLP categorizes text into predefined groups, streamlining data organization and retrieval, crucial for information management and decision-making processes. Key Industries: Legal, Finance, Healthcare, Media.
  • Sentiment Analysis – NLP evaluates the sentiment of text data, such as customer feedback or social media posts, aiding businesses in understanding customer perceptions and market trends. Key Industries: Marketing, Retail, Customer Service, Public Relations.
  • Named Entity Recognition – This NLP capability extracts structured information from unstructured data sources like documents and emails, enhancing data analysis and business intelligence. Key Industries: Legal, Finance, Healthcare, Government.
predictive analytics

Predictive Analytics

  • Churn Prevention – When a business loses a customer, it has to replace the loss of revenue by bringing a new customer. It proves to be expensive as the cost of acquiring a new customer is much higher than retaining the existing customer. Key Industries: Banking, Telecommunications, Retail, Automotive, Insurance
  • Customer Lifetime Value – It is pretty challenging to identify the customer in the market who is most likely to spend large amounts of money consistently over a long period. Key Industries: Insurance, Telecommunications, Banking, Retail
  • Customer Segmentation – Customer segmentation enables you to group the customer by shared traits. Different businesses determine their market differently depending on the aspects that offer the most value to their company, products, and services. Key Industries: Banking, Pharmaceutical, Automotive, Retail, Insurance, Telecommunications, Utilities
  • Next Best Action – Determining your primary marketing goals and customers is a critical use case for predictive analytics. It only provides an incomplete picture of what your marketing approach should be. Key IndustriesBanking, Telecommunications, Insurance, Education
  • Predictive Maintenance – In businesses, maintaining cost plays an essential role in increasing revenue. It is difficult for an organization with a significant investment in equipment and infrastructure to manage capital outlay. It’s where predictive maintenance machine learning techniques come in. Key Industries: Automotive, Logistic & Transportation, Oil & Gas, Manufacture, Utilities
  • Product Propensity – Product propensity combines purchasing activity and behaviour data with online behaviour metrics from social media and e-commerce. It enables you to identify the customer’s interest in buying your product and services and the medium to reach those customers. Key Industries: Banking, Insurance, Retail
  • Quality Assurance – Quality assurance is a key to your customer experience and the bottom line to all your operational expenses. Key Industries: Pharmaceutical, Manufacturing, Automotive, Logistics and Transportation, Utilities
  • Risk Modelling – Prevention and prediction are two sides of the same coin. Risk comes in various forms and initiates from a variety of sources. Predictive analytics can draw potential risk areas from significant data insights collected from most organizations. Key Industries: Banking, Manufacturing, Automotive, Logistics and Transportation, Utilities, Oil and Gas Utilities, Pharmaceuticals
  • Sentiment Analysis – In this era of the online world, it is difficult to be everywhere at all times. Reviewing and capturing everything said about your business or organization is virtually impossible. Key Industries: Pharmaceutical, Education, Retail, Telecommunications, Insurance, Entertainment
  • Up-Selling and Cross-Selling – The customer base is the source of your business’s existing revenue and revenue growth. Eventually, maximizing the possible revenue opportunities within your product set and target market segment becomes critical. Key Industries: Banking, Retail, Telecommunications, Insurance, Ecommerce
  • Predicting Buying Behaviour – One of the popular use cases for predictive analytics is analysing customers’ buying behaviour in retail industries. Companies use advanced analytics to identify the buying behaviour via customers’ purchase history. Key Industries: Ecommerce, Retail, Banking, Insurance
  • Fraud Detection – Cyber security is becoming a growing concern in today’s era, and there are plenty of use cases for predictive analytics in this domain. The most important out of all is fraud detection. The predictive analytics application helps analyse the system’s anomalies and detect unusual behaviours and patterns to determine threats. Key Industries: Banking, Telecommunications, Automotive
  • Healthcare Diagnosis – The healthcare industry benefits the most from the use cases for predictive analytics Health data is critical to diagnose depending on the patient’s history and current illness. The predictive analytics model enables you to understand the disease by accurate diagnosis based on past data provided. Health organizations leverage this prediction to ensure that patients get the treatment they need. Key Industries: Health sectors, Pharmaceuticals
  • Content Recommendation – Content recommender systems are one of the most popular use cases for predictive analytics. Entertainment companies can easily predict what users want to watch based on their watch history and predictive analytics techniques. Key Industries: Entertainment, Retail, Ecommerce
  • Virtual Assistance – Combined with the power of deep learning models, predictive AI works wonders when utilized with virtual assistance. Ok Google, Alexa, and Siri are real-world predictive analytics use cases. Companies use virtual assistants that can act as chatbots. These virtual assistants learn and collect data from users’ behaviour and deliver accurate results. Key IndustriesAutomotive, Ecommerce, Telecommunications
  • Campaign Management – Predictive analytics applications can help you determine where your campaign is best focused. A campaign launched using email work well as a suggestion at check out or, your customer is turning to your website for information. The analytics tools like word clouds generated from call recording data help you analyse the outreach efforts. Key IndustriesTelecommunications, Retail, Automotive
  • Volume Prediction – By analysing the fluctuations in the volume, you can severely impact how well you serve your customers. If you predict the increase in inbound volume, you can easily manage the effect of such changes. You can ensure your facilities can be adequately staffed if you know when spikes will occur. Key Industries: Insurance, Entertainment, Telecommunications, Banking
speech to text

Speech to Text / Text to Speech

  • Customer & Agent Conversation Analytics – Speech to Text AI transcribes customer service calls, allowing for analysis of conversations to improve customer satisfaction and agent performance. Key Industries: Customer Service, Telecommunications, Banking, Insurance.
  • Fully Automated Voice Enabled Intelligent Agents (Next Gen IVR) – Text to Speech and Speech to Text AI provide automated, interactive voice response systems for handling customer inquiries and tasks, enhancing customer experience and operational efficiency. Key Industries: Telecommunications, Retail, Banking, Healthcare.
  • Accessibility Features for Visually Impaired Users – Text to Speech AI converts digital text into spoken words, providing accessibility for visually impaired users in navigating websites, apps, and digital content. Key Industries: Technology, E-Learning, Government Services, Healthcare.
  • Real-Time Translation Services – Speech to Text and Text to Speech AI enable real-time translation of spoken language, breaking down language barriers in international communication. Key Industries: Travel and Hospitality, International Business, Education, Customer Service.
  • Automated Transcription Services – Speech to Text AI provides accurate transcription of lectures, meetings, and interviews, saving time and enhancing data accessibility. Key Industries: Legal, Journalism, Academic Research, Corporate Meetings.
machine vision

Machine Vision

  • Visual Search for Online Apparel Shopping – Machine Vision allows customers to search for clothing and accessories using images, enhancing the shopping experience and increasing sales. Key Industries: E-Commerce, Retail, Fashion, Apparel.
  • Quality Control in Manufacturing – Machine Vision inspects products on assembly lines for defects or deviations, ensuring high quality and reducing waste. Key Industries: Manufacturing, Automotive, Electronics, Consumer Goods.
  • Facial Recognition for Security and Identification – Machine Vision technology is used for identifying or verifying a person’s identity using their facial features, enhancing security measures. Key Industries: Security, Law Enforcement, Banking, Retail.
  • Agricultural Monitoring and Analysis – Machine Vision is used in agriculture to monitor crop health, pest infestation, and to optimize farm management practices. Key Industries: Agriculture, AgriTech, Environmental Science, Food Production.