Our generative AI development company offers AI technology consulting services that help you strategize, plan, and kick-start your project. Our experts estimate the impact of innovation on your operations, calculate your ROI, and provide all the levers needed to boost AI acceptance across your company.
Our engineers design and implement custom language models based on the capabilities of GPT, DALL.E2 and more. We bring our NLP, machine learning, and data science expertise to create robust solutions designed specifically for your business.
We customize generative AI tools and fine-tune LLMs with your own proprietary data. This helps the models to support your unique downstream tasks, operate with high accuracy within your business case, and deliver innovation to your company at less cost.
Our support team monitors the performance of your language model, introduces updates, and prevents model drifting. We ensure the long-term value of your AI applications and help them grow according to evolving market needs and your business requirements.
It’s difficult to pin down an exact figure as the accurate pricing depends on a large number of factors. At our generative AI company, the average cost starts from $10,000 and more depending on the project requirements.
The cost varies based on the complexity of your solution (consume vs. customize), a particular business case, and a specific service (consulting vs development). As we typically build on top of the existing large language models (GPT, DALL-E, etc) and customize them for your unique business needs, the costs are lower than training an AI model from scratch.
Generative artificial intelligence is an area of machine learning in which algorithms are designed to generate new data or content based on the training data. It can produce multiple types of content, including text, audio, and video.
Examples of generative AI include a large language model that consists of a neural network with multiple parameters. Large language models are trained on large quantities of unlabelled data to generate outputs.
Companies using generative AI apply the technology in a broad range of tasks – from business-centered to customer-focused functions.
Generative AI use cases span the following areas:
Top generative AI companies rely on language models to automate their customer support and enable personalized interactions with customers. Other high performers apply the technology to analyze vast amounts of data, generate reports and alerts, and handle documentation.
Language models also power chatbots, summarize texts to enable detailed social listening, and track consumer sentiment across channels.
The technology made inroads in many industries, including retail, healthcare, banking, education and manufacturing.
To produce accurate output, a large language model must be trained on terabytes of data. Relying on neural networks, machine learning, and natural language processing, it identifies the patterns and structures within existing data to produce new content. The unique capability of the model is also its ability to leverage different learning approaches. This makes it a universal tool to tackle a wide number of business challenges while supporting multiple applications.
Yes, Chat GPT is a type of generative artificial intelligence called a large language model.