Artificial Intelligence
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INNOVATIVE ARTIFICIAL INTELLIGENCE FOR NEXT-GEN AUTOMATION

Veritas Automata boasts a rich and diverse reservoir of expertise in artificial intelligence, the cornerstone of modern automation. Our platform, Hivenet, Machine Learning — heralding a new era of efficiency and intelligence. 

At the core of our pioneering approach is the integration of AI and ML, not only within the expansive realm of the cloud but also at the very edge of technological deployment. 

This allows for a seamless fusion of data processing where it’s most impactful.

Veritas Automata's Generative Artificial Intelligence System Tailored for Enterprise Data Offers Several Crucial Advantages

Veritas Automata AI Data Security

Automation

Our IA systems learn from data to make predictions and precisions which then automates tasks, processes, and eases decision-making.
Veritas Automata AI Compliance

Natural Language Processing

AI understands and generates human language, improving communication.
Veritas Automata AI Trust and Confidentiality​​

Computer Vision

AI interprets and analyzes visual information from images and videos.
Veritas Automata AI Robotics

Robotics

AI-powered robots and autonomous systems perform tasks in the physical world.

Veritas Automata AI Customization and Adaptation​​

Anomaly Detection

Inherently built with a self healing system to fix itself. Most systems do not have a self-check feature but Veritas Automata does.
Veritas Automata Rivaling Artificial Intelligence​

Rivaling Artificial Intelligence

Our approach to ethical AI governance is intended to be a type of rival to the AI itself giving the governance to another AI which has the last word in an AI response.
Veritas Automata Artificial Intelligence Data Security​

Data Security

With sensitive enterprise data, ensuring privacy is paramount. A private Gen AI system guarantees that proprietary information remains within the organization’s control, mitigating the risk of data breaches or leaks.
Veritas Automata Artificial Intelligence Compliance​​

Compliance​

Many industries are subject to stringent regulatory requirements regarding data privacy and confidentiality. A private Gen AI system enables enterprises to adhere to these regulations without compromising on the benefits of AI-driven insights.​
Veritas Automata Artificial Intelligence Customization and Adaptation​​

Customization and Adaptation​

Enterprises operate in diverse industries with unique needs. A private Gen AI system can be customized to analyze and generate insights specific to the organization’s domain, fostering innovation and competitive advantage.​
Veritas Automata Artificial Intelligence Trust and Confidentiality​​

Trust and Confidentiality​

Building trust with customers, partners, and stakeholders relies on maintaining the confidentiality of sensitive information. By utilizing a private Gen AI system, enterprises can uphold their commitment to confidentiality and strengthen trust relationships.​

Veritas Automata is here to solve your toughest challenges, and AI does just that. It empowers businesses to tackle complex problems with precision and speed, something that was unimaginable before.

Whether it’s optimizing Supply Chains, Cold Chain, and Chains of Custody or accelerating drug discovery, AI brings logical and intuitive solutions to the table.
In the quest for efficiency, AI is a game-changer. With our expertise in using Rancher K3s Open-source Kubernetes, and other cutting-edge technologies, Veritas Automata ensures that AI-driven solutions are designed to make your toughest tasks manageable.

This increased efficiency translates to reduced costs and improved profitability.

For ambitious leaders and executives, staying ahead of the competition is crucial. 

Veritas Automata’s AI-powered solutions help businesses gain a competitive edge by providing real-time insights, predictive analytics, and automation capabilities that can transform the way they operate.

Trust, clarity, efficiency, and precision are encapsulated in our digital solutions.

AI plays a pivotal role in ensuring the accuracy and clarity of processes. It reduces errors, minimizes risks, and enhances decision-making, all while maintaining a clear digital chain of custody.

Azure Private GPT presents a compelling alternative to open LLMs, offering robust safeguards to maintain user data privacy. Here are key aspects highlighting its commitment to safeguarding user data privacy.
  • The prompts (inputs) and completions (outputs), embeddings, and training data utilized by the Azure OpenAI Service are safeguarded with strict privacy measures

  • They are exclusively accessible to the customer employing the service and are not shared with other customers or OpenAI.

  • Furthermore, they are not utilized to enhance OpenAI models, Microsoft products or services, or any third-party offerings.

  • Additionally, the fine-tuned Azure OpenAI models remain solely available for the customer’s usage, ensuring their proprietary use.

  • Microsoft exercises full control over the Azure OpenAI Service, hosting the models within its Azure environment and ensuring no interaction occurs with services operated by OpenAI, such as ChatGPT or the OpenAI API

ChatGPT / Public LLM​

Vs.

Open Source LLM​

Strengths​

Vast Pre-Trained Knowledge​
ChatGPT has been trained on a diverse range of internet data, providing a broad knowledge base that can be leveraged for various tasks.​
Continuous Improvement
Being part of a large organization like OpenAI, ChatGPT undergoes continual updates and improvements, ensuring access to state-of-the-art language understanding capabilities.​
Ease of Integration​
ChatGPT’s API allows for straightforward integration into existing systems and workflows, making it accessible and easy to implement.​

Strengths​

Customization​
Being open-source allows for extensive customization to tailor the model precisely to enterprise requirements, including privacy and domain-specific needs.​
Community Collaboration​
The open-source nature encourages collaboration and contributions from a diverse community of developers, potentially leading to rapid improvements and innovation.​
Transparency​
Enterprises have full visibility into the model architecture and training data, enhancing trust and allowing for rigorous auditing and validation.​

Weaknesses​

Limited Data Privacy​
As a public LLM, concerns about data privacy may arise, especially when dealing with sensitive enterprise information. This could hinder adoption in industries with strict privacy regulations.​
Generic Insights​
ChatGPT’s pre-training on internet data may not capture the intricacies and nuances specific to enterprise domains, potentially leading to less relevant insights.​
Cost Considerations​
While the API is accessible, there may be associated costs based on usage, which could be a concern for organizations with budget constraints.​
Regulatory Constraints​
Evolving regulations around data privacy and AI usage may impose limitations or additional compliance requirements on the use of public LLMs like ChatGPT in enterprise settings.​

Weaknesses​​

Resource Requirements​
Developing and maintaining a customized LLM requires significant technical expertise and resources, which may be a barrier for smaller organizations.​
Initial Setup Complexity​
Implementing within enterprise infrastructure may involve substantial setup and configuration efforts, particularly concerning data privacy and security measures.​
Limited Support​
While community collaboration is a strength, reliance on community support may pose challenges in terms of obtaining timely assistance and resolving issues.​

More Technologies

Kubernetes

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K3S on AWS EC2

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