Generative AI: A fast-paced solution, looking for problems to solve.
Identify opportunities for generative AI adoption, assess your existing infrastructure & business processes, and create a roadmap for implementation, with our generative AI consulting solutions.
The Process Our Developers Follow to Build Generative AI Solutions
Requirement Assessment
Uncover and record precise requirements, goals, and limitations of the project. Gain actionable insight into your stakeholders' expectations for offering an ultimate product or system.
Strategy Building
Develop a strategic plan outlining a generative AI model selection, training approach, resource allocation, and deployment strategy tailored to the project’s goals.
Design and Development
Craft detailed specifications and architectural designs for the solution, followed by its development using a fine-tuned model, ensuring seamless alignment with the client’s unique requirements.
Testing
Rigorously test the generative AI solution, improving it through iterative cycles to ensure better output quality and minimize biases.
Deployment and Optimization
Deploy the generative AI solution into the production environment, and undertake optimization efforts to enhance its performance and output quality.
Integration and Support
Integrate the generative AI solution into the client’s existing ecosystem, followed by ongoing support and maintenance to ensure its alignment with evolving requirements.
Our Services
AI Strategy & Advisory
- Generative AI Strategy & Roadmap
- AI Automation Strategy & Roadmap
- Prompt Engineering Consultation
- AI Transformation Workshops
- AI/ML Strategy
AI Training & Capacity Building:
- AI/ML Training Workshops
- Specialized Training
AI Development and Deployment
- Generative AI Implementations
- Customs AI Implementations
- Chatbot Development
- AI Automations
- Computer Vision Solutions
- NLP Systems
AI Data Management:
- Data Strategy & Management
- Data Augmentation with
- Generative AI
- Data Annotation Services
Lead The Market With
Our Generative AI Development Series.
Increased Automation
Our generative AI development services empower you to stay ahead of the competition by significantly increasing automation across various aspects of your business. With AI-driven processes handling repetitive tasks, you can allocate your workforce more strategically, focusing on innovation and growth.
Increased Productivity
Our services boost your productivity by harnessing the power of generative AI to augment your team’s capabilities. This translates to quicker decision-making, improved resource allocation, and streamlined workflows, enabling you to achieve more in less time and gain a competitive edge.
Enhanced Creativity
Leveraging generative AI allows you to foster innovation and creativity within your organization. We build solutions that can generate content, ideas, and roadmaps that inspire new directions for your products or services, helping you stay ahead of the curve and captivate your audience.
Cost Optimization
By automating tasks, improving efficiency, and reducing the scope of errors, you can significantly cut operational costs while maintaining or even improving the quality of your products or services, ensuring a competitive advantage in today’s dynamic market.
Risk Mitigation
From fraud detection to predictive maintenance, AI can identify risks before they become problems.
Competitive Edge
AI-driven insights and automation can give you a leg up over competitors who are slower to adopt technology.
Al Models We Have Expertise in
GPT - 4
OpenAI models can solve complex problems with high accuracy, thanks to their advanced reasoning capabilities and broader general knowledge.
LLaMA
LLaMA (Large Language Model Meta AI) is a foundational large language model designed to generate text, have conversations, summarize written content, solve math theorems, or predict protein structures.
PaLM 2
The newest extensive language model from Google, PaLM 2 stands out in performing intricate reasoning assignments, such as code interpretation, mathematical solutions, categorization, query responses, and translation with proficiency in multiple languages. This model highlights Google's commitment to responsible AI, surpassing previous capabilities in natural language generation.
Claude
Claude is a large language model (LLM) by Anthropic, trained as a virtual assistant that can be integrated with business workflows. Claude, accessible through both a chat interface and API in Anthropic’s developer console, can perform an extensive range of conversational and text-processing tasks.
Bard
Google Bard, powered by LaMDA, is a text-to-text generative AI chatbot designed to generate human-like responses to natural language prompts (NLP), making it capable of engaging in conversations with humans.
Our Generative AI
Consulting Services
Gen AI Use Case Identification and Opportunity Assessment
We begin by analyzing your business environment to discover unexplored possibilities where Gen AI will have a profound influence. Our comprehensive evaluation takes into account all aspects of your operations and product offerings, to provide you with a well-defined roadmap for an AI-driven transformation.
Technology Assessment and Selection
Our team of experts performs extensive evaluations on gen AI tech tools like OpenAI ChatGPT & DALL-E, and Google BERT. By analyzing their capabilities and assessing their compatibility with your organization's specific needs, we ensure the ideal selection and seamless implementation of these advanced solutions.
Actionable AI Roadmap
After carefully evaluating your business, we design a practical AI roadmap customized to your specific needs. This roadmap built on SMART goals provides necessary resources for implementing cutting-edge Gen AI solutions. The exhaustive plan empowers you to execute it independently or with our expert assistance.
Ethical & Responsible AI Consulting
At our company, we believe that AI is not only intelligent but also morally upright. Through our consulting services, we provide thorough guidelines and industry best practices to ensure that your AI projects are in sync with ethical standards and responsible approaches.
Real-World
Applications of AI
Discover how our diverse AI services have delivered transformative results for businesses.
- Publishing
- Legal Firms
- Telecommunications
- Transport & Logistics
- Manufacturing
- Retail & E-commerce
- Banking & Finance
- Healthcare
- Content Recommendation Engines: Personalizing reading experiences by suggesting articles, books, or journals based on past preferences.
- Automated Content Creation: Using AI to draft reports, summaries, or news updates.
- Copyright Infringement Detection: Scanning the web for unauthorized reproductions of copyright content.
- Predictive Analytics for Publishing Trends: Anticipating what genres, topics, or authors might be popular in the near future.
- Chatbots for Customer Support: Assisting readers with queries, purchases, or subscription details.
- Sentiment Analysis: Reviewing reader comments and feedback to inform content strategies and improve engagement.
- Document Review & Analysis: AI systems that can quickly sift through large volumes of documents, extracting pertinent information.
- Contract Analysis: Identifying potential risks or issues in contract drafts.
- Legal Research Assistance: Helping lawyers find relevant case laws or statutes using natural language queries.
- Predictive Case Outcomes: Using historical data to predict potential outcomes of cases.
- Automated Legal Drafting: AI tools that assist in drafting standard legal documents based on inputs.
- Network Optimization: Predictive analytics for improving network quality and reducing downtimes.
- Predictive Maintenance: AI models that forecast when network equipment might fail.
- Customer Service Chatbots: Offering instant support and handling common customer queries.
- Fraud Detection: Recognizing unusual patterns to prevent fraudulent activities.
- Demand Forecasting: Predicting data traffic and bandwidth requirements.
- Personalized Marketing: AI-driven systems that recommend tailored services and offers to users based on their usage patterns and preferences.
- Route Optimization: AI models to determine the most efficient path considering traffic, weather, and other dynamic factors.
- Predictive Maintenance: Detecting potential vehicle or equipment failures in advance.
- Demand Forecasting: Anticipating transportation needs based on historical data, trends, and events.
- Autonomous Vehicles: Self-driving trucks, cars, or drones for goods delivery and passenger transit.
- Warehouse Management: Automated robots and systems to streamline storage and retrieval processes.
- Tracking and Monitoring: Real-time tracking of shipments or fleets using sensors and GPS data.
- Medical Imaging: Deep learning techniques, especially Convolutional Neural Networks (CNNs), that are used to detect anomalies or diseases in X-rays, MRIs, and other imaging.
- Drug Discovery: AI to analyze complex biochemical interactions. Machine learning models can predict how different chemical compounds can affect human cells.
- Predictive Analytics: Using past patient data to foresee diseases or health deterioration.
- Virtual Health Assistants: Chatbots or voice assistants providing medical info, prescription clarifications, or appointment scheduling.
- Remote Monitoring: Wearable devices connected to AI algorithms that track patient vitals in real-time, alerting health professionals of any irregularities.
- Recommendation Systems: Algorithms that analyze a user's browsing and purchase history to suggest products.
- Visual Search: Enabling customers to search for products using images rather than text.
- Chatbots and Virtual Assistants: Providing instant customer support, tracking orders, and answering product-related queries.
- Supply Chain Optimization: Predictive analytics for better inventory management and demand forecasting.
- Dynamic Pricing: Adjusting prices in real-time based on demand, availability, and other external factors.
- Virtual Try-On: Using Augmented Reality (AR) to allow users to virtually try on clothes, accessories, or makeup.
- Fraud Detection: Machine learning models to analyze transaction patterns in real-time and detect unusual or suspicious activities.
- Risk Assessment: AI-driven credit scoring by analyzing traditional and non-traditional data sources to determine loan eligibility.
- Chatbots and Virtual Assistants: Automating customer support and helping with queries, account management, or even investment advice.
- Algorithmic Trading: Using AI to analyze market data and execute trades at high speeds.
- Personalized Banking: Offering tailored product recommendations based on customer behavior and spending habits.
- Regulatory Compliance: AI tools that ensure financial process and transaction compliance with local and international regulations.
- Medical Imaging: Deep learning techniques, especially Convolutional Neural Networks (CNNs), are now being used to detect anomalies or diseases in X-rays, MRIs, and other imaging.
- Drug Discovery: AI can analyze complex biochemical interactions. Machine learning models can predict how different chemical compounds can affect human cells.
- Predictive Analytics: Using past patient data to foresee diseases or health deterioration.
- Virtual Health Assistants: Chatbots or voice assistants providing medical info, prescription clarifications, or appointment scheduling.
- Remote Monitoring: Wearable devices connected to AI algorithms that track patient vitals in real-time, alerting health professionals of any irregularities.
Meet Our Team
Kamal Chawla
AI Advisor
(Strategy & Solutions)
Mudit Sharma
AI Advisor
(AI Implementation)
Nishant Gupta
AI Sales Leader
Jatin Chhabra
AI Marketing Leader
Book a meeting.
FAQs
Generative AI, short for Generative Artificial Intelligence, is a subset of artificial intelligence that focuses on creating new, original content or data. It involves using algorithms and models to generate data that is not explicitly provided in the training dataset. This technology is capable of generating text, images, audio, and more, often by learning patterns and relationships from existing data. Generative AI has applications in a wide range of fields, including content generation, creative arts, data augmentation, chatbots, and even drug discovery. It’s a powerful tool for automating tasks that require creative or novel outputs.
Generative AI has a wide range of applications across various domains. Some common applications of generative AI include:
- Text Generation: Generative AI can produce human-like text, making it useful for applications like content generation, automatic summarization, and even creative writing. Language models like GPT-3 and GPT-4 excel in this area.
- Image Generation: Generative Adversarial Networks (GANs) are commonly used to generate realistic images. This technology finds applications in art creation, design, and even deepfake generation.
- Voice and Audio Synthesis: Generative AI can create human-like speech and music, making it valuable in voice assistants, personalized audio content, and music composition.
- Data Augmentation: Generative AI can generate synthetic data to augment real datasets, improving the performance of machine learning models, particularly in cases of limited training data.
- Style Transfer: This involves changing the style or appearance of content, such as transforming a photograph into the style of a famous artist’s painting.
- Chatbots and Virtual Assistants: Generative AI is used to create conversational agents capable of generating responses and engaging in natural language conversations with users.
- Content Recommendation: It can be used to personalize content recommendations in e-commerce, content streaming platforms, and marketing.
- Anomaly Detection: Generative models can learn normal patterns in data and identify anomalies or outliers, which is useful in cybersecurity and fraud detection.
- Art and Creativity: Generative AI is utilized to create art, generate music, and explore new creative frontiers.
- Video Synthesis: It can generate video content, such as deepfake videos for entertainment or synthetic training data for computer vision applications.
- Language Translation: Generative AI can assist in language translation by generating translations for text or speech.
- Medical Image Generation: It can create synthetic medical images for training and testing diagnostic AI systems.
- Game Design: Generative AI can be used to design levels, characters, and content in video games.
These are just a few examples, and the applications of generative AI continue to expand as the technology advances. Generative AI’s ability to generate creative, novel, and contextually relevant content makes it a powerful tool in various industries and fields.
We work with a wide range of industries, from healthcare and finance to retail and manufacturing. Our consulting services are designed to identify areas where Gen AI can bring value, irrespective of the industry.
Our consulting process involves four key steps: Opportunity Assessment, Data Readiness & Strategy, Actionable AI Roadmap, and Ethical & Responsible AI Consulting. Each step is designed to provide you with a comprehensive plan for Gen AI implementation.
Absolutely. Our primary goal is to provide you with an actionable Gen AI roadmap that you can execute with or without us. We equip you with all the necessary knowledge and guidelines.
Ethical considerations are integral to our consulting services. We provide guidelines and best practices to ensure that your AI initiatives are responsible and comply with ethical standards.
The ROI can vary but implementing Gen AI can lead to cost savings, increased efficiency, and new revenue streams. Our Opportunity Assessment will give you a clearer picture of the potential ROI.