The Generative AI That Belongs to Your Enterprise

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.

The Disparity

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

On-Premises LLMs: Synergizing Security and Generative AI Potential

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. 

Why Choose On-Premises LLMs?

Fortified Data
Security

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.

Industry-Tailored Precision

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.

Minimized External
Risks

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.

Reduced Hallucinations and Bias Mitigation

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.

Data Control and Compliance

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.

Better AI Health

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.

Why Settle for the Ordinary 'One Size Fits All' When You Can Leverage 'Tailored to Fit' for Your Needs?

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.

Use Cases Across Industry Verticals

BFSI

In BFSI, generative AI enables robust anomaly detection, fraud pattern synthesis, FAQ management with query-relevant responses, and the development of algorithmic trading strategies for optimizing investment strategies in real time along enhanced risk management.

Legal Services

In the legal domain, generative AI streamlines contract review by automatically analyzing and extracting key information, generates precise legal documents, processes vast case law data for semantic understanding, and ensures continuous monitoring and compliance checks.

Information Technology

In IT, generative AI accelerates processes with code generation, automated software testing, natural language interface development, and advanced network security analysis, ushering in a new era of innovation and efficiency.

Telecommunications

In telecom, generative AI optimizes operations with predictive network maintenance, tailored conversational AI experiences, advanced network optimization algorithms, and predictive resource allocation for peak efficiency.

Healthcare

In healthcare, generative AI revolutionizes patient care through medical image analysis, continuous patient health monitoring, cutting-edge clinical decision support systems, and personalized treatment plans tailored to individual needs.

Retail

In retail, generative AI transforms the landscape with demand forecasting models, personalized customer experiences, optimized visual merchandising, and sophisticated price optimization algorithms, creating a dynamic and customer-centric shopping environment.

The E42 Impact

Advantages of E42's Generative AI coupled with Cognitive Process Automation

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.

How an AI Marketing Analyst Built on E42 is Weaving Magic for Marketing and Sales Teams

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.

E42 Model Overview

The E42 model offers the following advantages:

Outperforms Llama 2 13B on all benchmarks

Outperforms Llama 1 34B on many benchmarks

Approaches CodeLlama 7B performance on code, while remaining good at English tasks

Uses Grouped-Query Attention (GQA) for faster inference

Uses Sliding Window Attention (SWA) to handle longer sequences at a smaller cost

Sustainable Solutions

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:

Model Size and Energy Footprint Reduction

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.

Cost-Effective GPU Usage

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.

Utilizing Preexisting Models

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!

Performance Comparison

The E42 model significantly outperforms Llama 2 13B on all metrics and is on par with Llama 34B. It is also vastly superior in code and reasoning benchmarks.

Benchmark Categories

  • Commonsense Reasoning: 0-shot average of Hellaswag, Winogrande, PIQA, SIQA, OpenbookQA, ARC-Easy, ARC-Challenge, and CommonsenseQA.
  • World Knowledge: 5-shot average of NaturalQuestions and TriviaQA.
  • Reading Comprehension: 0-shot average of BoolQ and QuAC.
  • Math: Average of 8-shot GSM8K with maj@8 and 4-shot MATH with maj@4.
  • Code: Average of 0-shot Humaneval and 3-shot MBPP.
  • Popular Aggregated Results: 5-shot MMLU, 3-shot BBH, and 3-5-shot AGI Eval (English multiple-choice questions only).

Equivalent Model Sizes

An interesting metric to compare how models fare in the cost/performance plane is to compute “equivalent model sizes”. On reasoning, comprehension, and STEM reasoning (MMLU), the E42 model performs equivalently to a Llama 2 model that would be more than 3 times its size. This results in significant savings in memory and gains in throughput.

Equivalent-Model-Sizes
Cognitive automation platform

At E42, creating a safe and healthy working environment takes precedence above all. The company has zero tolerance for prejudice, gender bias, and sexual harassment. For a comprehensive overview of our safety policy, please feel free to contact us at interact@e42.ai