- Generative AI
Generative AI
Chazey Partners offer end-to-end AI solutions with domain and industry insight to harness the power of human-machine collaboration. Our approach to AI solutions combines strategic thinking, industry know-how, and deep AI knowledge to deliver insights that help clients realize their complex ambitions.
What is Generative AI?
Generative AI, or “Generative Artificial intelligence” to give its full name, is a type of artificial intelligence technology that can produce various types of original content, including text, imagery, video, audio, and synthetic data.
Generative AI models use neural networks to identify patterns and structures within existing data to generate content that is new and entirely unique. It can do this without explicit instructions, unlike traditional AI which requires specific instructions to perform a task.
A neural network is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain. It is a type of machine learning process, called deep learning, that uses interconnected nodes or neurons in a layered structure that resembles the way the human brain works.
Generative AI Services Offered
Generative AI consulting
Our team of AI experts specialize in developing and implementing Generative AI solutions tailored to your business needs. We provide end-to-end support, from selecting the right AI model to designing and fine-tuning it for optimal results. With our expertise and support, you can unlock the full potential of Generative AI for your business.
Generative AI Use Case Identification and Feasibility Assessment
Our team assists in identifying potential use cases for generative AI within your organization. We conduct feasibility studies to assess the viability and potential impact of implementing generative AI solutions, providing you with insights to make informed decisions.
Compliance and Security Consultation
Leveraging our knowledge of critical regulations like GDPR, CCPA, and HIPAA, we assess your generative AI solution ensuring system compliance. This mitigates potential risks while maintaining utmost data integrity.
Model integration and deployment
Our Generative AI services are expertly designed to alleviate common pain points such as resource-intensive development cycles and budget constraints. By leveraging existing Generative AI tools and solutions, we swiftly unlock untapped potential within your data, driving innovation, minimizing disruption, and delivering cost-effective yet remarkable outcomes.
Generative AI application development
Our team develops bespoke generative AI solutions that cater to your business needs. We specialize in performance optimization, model integration and deployment, and ongoing support and maintenance. This is to ensure the seamless integration of generative AI technology into your existing systems. Our services include data preparation and modeling, algorithm development and implementation, and ongoing support and maintenance.
Fine-tuning LLMs (Large Language Models)
Our experts employ prompt engineering to fine-tune LLMs for your tasks. We select suitable pre-trained models and train them on relevant datasets. Utilizing transfer learning, data augmentation, gradient descent, and hyperparameter tuning, we enhance performance. Careful data curation, precise instructions and performance evaluation ensure LLMs efficacy.
Training and Support
We offer comprehensive training and support programs, empowering you with the necessary skills and knowledge to effectively utilize the developed generative AI solutions along with a smooth adoption process.
Generative AI maintenance
Generative AI involves monitoring and updating the generative AI model over time to ensure that it continues to produce high-quality output. This may include retraining the model with new data, adjusting the hyperparameters or architecture of the model, or applying other techniques to improve its performance. Maintenance also involves addressing any issues or errors that may arise during deployment, such as bias in the generated output or computational inefficiencies. In addition, maintenance may include updating the model to comply with changing regulations or ethical considerations, as well as optimizing its energy consumption and carbon footprint.