Generative AI, as the name suggests, is artificial intelligence equipped to generate content. We make sure that your generative AI generates accurate, compliant, and tailored solutions for your enterprise whilst maintaining the highest standards of encryption and security. It speaks your language, solves your problems, and enhances your efficiency.
| Aspect | Generative AI Solutions Commonly Available in the Market | E42's Proprietary Generative AI Fine-Tuned for Enterprises | |
|---|---|---|---|
| | Customization and Adaptability | Limited fine-tuning, general-purpose model | Extensive customization for enterprise needs |
| | Data Privacy and Security | Cloud-based, data transmitted and stored externally | On-premises deployment enhances data security |
| | Low Latency and Real-Time | Latency is possible due to cloud operations | Local processing minimizes latency |
| | Integration with Systems | Limited adaptability to specific enterprise systems | Seamless integration with existing workflows |
| | Compliance and Governance | Challenges in adherence to industry regulations | Enhanced control over compliance on-premises |
| | Hallucination and Bias | May produce content lacking in accuracy or context, potential for bias | Customizable to mitigate biases and hallucination |
Our large language models are installed and operated within an organization’s local infrastructure making generative AI your enterprise‘s favorite ally, finely tuned to grasp your language and nuances, delivering precise and relevant solutions for unparalleled accuracy.
On-premises LLMs ensure fortified data security by keeping sensitive information within the organization’s infrastructure, reducing the risk of external breaches or unauthorized access. This localized approach enhances data protection and confidentiality.
Deploying LLMs on-premises allows organizations to tailor language models precisely to industry-specific language nuances and requirements. This customization ensures that the language model is finely tuned to the unique needs of the business, promoting more accurate and relevant outcomes.
By avoiding reliance on external servers, on-premises LLMs minimize exposure to external risks such as data transmission vulnerabilities or server outages. This localized deployment contributes to a more resilient and secure language processing environment.
On-premises LLMs provide greater control over data and model training, enabling organizations to implement rigorous bias mitigation strategies. This control helps reduce the potential for hallucinations and biases in the generated content, ensuring more accurate and unbiased language outputs.
Organizations benefit from enhanced control over their data, ensuring compliance with industry regulations and internal policies. On-premises deployment facilitates meticulous data control, allowing businesses to align with stringent compliance standards and regulatory requirements.
Local deployment of LLMs allows organizations to actively monitor and manage the health of their AI models. With real-time insights into model performance and behavior, businesses can proactively address issues, optimize algorithms, and ensure the sustained well-being of their language models.
There’s a difference between settling for generic, one-size-fits-all solutions and embracing the power of bespoke, precision-engineered systems. On-premises Large Language Models (LLMs) embody this mastery, offering a level of customization and adaptability that sets them apart.
AI co-workers built on E42 are the digital collaborators who excel in handling routine and time-consuming activities, liberating human counterparts to focus on critical thinking and creativity. From document processing to customer service and beyond, E42’s generative AI coupled with CPA enhances efficiency and fosters a collaborative work environment.
This was just one vertical, envision an AI co-worker tailored to your enterprise needs, seamlessly integrating into your business processes and enhancing productivity across diverse verticals.
In the realm of generative AI, E42 has been an early adopter and ardent practitioner of innovative strategies such as LORA and Quantization techniques to address crucial aspects of model efficiency, environmental impact, and cost-effectiveness:
E42 employs LORA (Low-Rank Approximation) and Quantization techniques to significantly reduce the model size and energy footprint during training. This not only enhances computational efficiency but also aligns with sustainable practices, promoting greener AI.
E42 strategically utilizes less expensive GPUs, optimizing the cost associated with model training without compromising performance. This approach ensures economic viability for clients while maintaining computational efficiency.
E42’s approach stands out in sustainability; instead of building LLMs from scratch, it leverages preexisting models available in the market. This not only saves GPU power but also contributes to economic viability. By reusing established models, E42 ensures that its generative AI solutions are both environmentally conscious and economically sustainable.
Ready to unlock the power of generative AI for your enterprise? Let’s explore limitless possibilities together!
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