Unlock the Power of AI with Our Custom Generative AI Development Services. We empower your enterprise by tapping into the transformative potential of foundational AI models like GPT-4, Llama and PaLM-2. Our GenAI solutions help businesses automate and streamline workflows for heightened productivity and efficiency.
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We provide AI technology consulting services that offer expert advice and guidance on the most effective strategy for designing a generative AI solution aligned with a project’s unique needs and objectives.
We leverage machine learning algorithms like RNNs, transformers, Markov Chain, GANs, and autoencoders to develop, configure and train generative AI models based on clients’ specific requirements. Post-training, we validate models with data sets and ensure they meet industry standards with security audits and testing.
We develop generative AI tools similar to ChatGPT, Midjouney, Dall-E and chatbots with high NLP and NLU accuracy tailored to clients’ specific business needs.
We provide post-production optimization services like fine-tuning and upgradation of the model to ensure it performs optimally as per the latest AI trends while meeting the changing needs of your business.
We thoroughly evaluate and understand your requirements to ensure secure and effective integration and deployment. Our OpenAI model integration and deployment service covers the entire process, from model selection and configuration to integration, testing and deployment.
We apply techniques such as transfer learning, learning rate scheduling, data augmentation, regularization, and hyperparameter tuning to fine- tune a generative AI model for a specific task, enabling the model to leverage existing knowledge to improve performance on the target task.
LLaMA (Large Language Model Meta AI)
The newest extensive language model from Google
Claude is a large language model (LLM) by Anthropic
Google's Bard, powered by LaMDA, is a text-to-text generative AI chatbot
DALL·E by OpenAI generates realistic images and artwork based on text prompts.
Whisper is a general-purpose speech recognition OpenAI model that can perform language identification, speech translation and multilingual speech recognition.
OpenAI's Embeddings that capture the semantic meaning and relationships between them.
Moderation models are machine learning OpenAI models designed to assist in content moderation tasks.
Stable Diffusion generates detailed images from text prompts
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The first step in the AI development process is to define the problem that needs to be solved. This involves identifying the business problem and understanding the scope of the project. Once the problem has been defined, the next step is to collect and prepare the data that will be used to train the AI model. This data must be representative of the problem being solved and must be cleaned and pre-processed to ensure accuracy and consistency.
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The second step in the AI development process is to choose the appropriate AI algorithm that will solve the problem based on the data that has been collected. There are many different AI algorithms to choose from, each with its strengths and weaknesses. Once the algorithm has been selected, the next step is to train the AI model using the data and algorithm that has been chosen. This step involves feeding the data to the algorithm and adjusting the model parameters until it can accurately predict outcomes.
The third step in the AI development process is to test the accuracy and performance of the AI model using a separate dataset that was not used during the training process. This step is important to ensure that the AI model is effective in solving the problem and is able to provide accurate and reliable predictions. Once the model has been validated, the next step is to deploy it in a real-world environment.
The fourth and final step in the AI development process is to deploy the AI model in a real-world environment and integrate it with existing systems and processes. Once the model has been deployed, it is important to monitor its performance over time and make necessary adjustments to ensure continued accuracy and relevance.
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With Generative AI solutions, you can automate tasks, including data processing, analysis and content creation, allowing you to save time and workload and focus more on higher levels of human intelligence.
We help you to increase productivity by developing new solutions and ideas for complex problems with Generative AI systems that can analyze large amounts of customer feedback to generate new ideas and solutions for improving customer experience.
Using Generative AI, we develop new solutions following the models of chatGPT, Midjourney, DALL-E and Stable Diffusion, which allow you to be more innovative and creative by improving the performance of products and services.
Our Generative AI solutions automate repetitive tasks and reduce manual labor, which allows you to lower operating costs and increase profitability.