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Envision AI

Large language models can provide significant benefits to businesses in various ways. The key to success when using AI like LLMs is to identify specific problems can be solved with them. It is also critical to choose the right LLM for the job and implement a solution that is secure and responsible.  

 

Overview

Our Envision AI offering is designed to help your business glean insights on the state of LLMs and identify key business problems that can be solved with LLMs in a secure and responsible fashion. Our team of experts will work with you to define business outcomes and formulate a strategy to choose the right LLMs to achieve them. 

 

State of LLMs today

Our experts will share our perspective of the LLM landscape today, including types of LLMs and common scenarios that are applicable to them. We will also share common use-cases across various industries applicable to LLMs.

 

Key deliverables 
  • Discuss current state of LLMs and common use-cases across industries. 
  • Importance of a Knowledge-base utilizing GenAccel to obtain specific outcomes. 
  • Value of prompt engineering and fine-tuning. 
  • De-risking your data/KB with SecureGPT.

 

Define problem statement

We will work with your stakeholders to brainstorm existing or new business ideas and identify key areas of LLM use. As a part of this exercise, we will work with your team to define desired outcomes as dictated by your business priorities.

 

Key Deliverables 

  • Gather feedback and brainstorm use-cases for LLMs in the context of your business. 

  • Define clear business objectives, prioritize use-cases based on impact. Ex: Improving customer service, reducing cost, improve decision making etc. 

  • Demonstrate the Emerscient approach with customer data. 

 

Choose LLM and evaluate feasibility

It is critical to choose the right tool for the job. Once the problem statement is defined, we will recommend LLMs options and work with your team to evaluate feasibility of deployment. 

 

Key Deliverables 

  • Identify appropriate LLM(s) for each prioritized use-case. 

  • Identify data sources and evaluate for quality and feasibility. 

  • Evaluate existing infrastructure and skills required to deploy and maintain LLM apps. 

  • Evaluate cost: Data acquisition cost, hardware/software cost, maintenance support costs. 

  • Evaluate potential risks: security, legal and ethical. 

Prove AI

Businesses across several industries are thinking of using Generative AI to solve unique problems, boost productivity and introduce efficiencies. The first step in the journey is to identify the problems you want to solve and test the technology for potential fit. It can be challenging to prove capability at a smaller scale and identify the practical pitfalls before scaling up to meet the desired business goals. 

 

Overview

Our Prove AI offering is designed to help your business test the right Generative AI models and prove capability fit against specific outcomes. Our experts will partner with your team to calibrate the use-cases derived from the Envision AI workshop. We will then deploy the appropriate LLM, a Knowledge-base, SecureGPT along with other tools using our accelerator solution in your environment and test for a specific use-case at POC scale. 

 

Assess technology and prioritize ‘Envision AI’ outcomes

Our team will assess the artefacts from the Envision AI workshop and with your feedback, identify the use-case/outcome to be tested in your environment.  

 

Key deliverables

  • Identify one use-case and related metrics for POC trial. 

  • Design reference architecture for POC deployment. 

  • Identify and assess data sources to be used for training.  

  • Assess technical infrastructure for POC deployment. 

 

Deploy POC environment 

We will work with your technical team to deploy the arrived upon architecture with all key technical components and data. 

 

Key Deliverables   

  • Deploy and configure desired LLM for testing and fine-tuning. 

  • Deploy Knowledge-base and ingest/migrate appropriate data. 

  • Deploy SecureGPT and configure access control policies against KB. 

  • Deploy LLM-supporting tools to assist in accuracy in query responses. 

 

Test and fine tune

 We will then test the POC environment with specific prompts and iteratively fine tune the model against desired outcomes. 

 

Key Deliverables 

  • Test the model contextual accuracy with specific prompts. 

  • Test SecureGPT access policies against data sources and users/groups. 

  • Fine tune model and prompts to enhance accuracy. 

 

Realize AI

Generative AI can bring significant benefits to businesses by optimizing the output of tasks, identifying patterns in data, and providing insights for decision-making. It is critical that Generative AI-based Large Language Models (LLMs) are deployed in a secure, accurate and scalable fashion, where organizations and employees can take advantage of the benefits without incurring major risks to their business and data.

 

Overview

The AI realization offering is designed to empower your firm with the requisite technical expertise and services needed to deploy and manage generative LLMs in a robust and secure manner.

 

Infrastructure evaluation and deployment

We will work with your team to prioritize pre-defined use-cases for deployment. Our experienced technical team will then work with you to define the best architecture for realizing those use-cases (we recommend our Envision AI offering to help evaluate and identify business objectives for generative AI use).

 

Key Deliverables
  • Evaluate data sources, technology infrastructure and user access rights.
  • Define architecture for production implementation of LLMs, customized to your environment.

 

Building a Secure Knowledge Base 

LLMs can yield enormous productivity benefits for your business; however, they are not trained on proprietary or private data related to your organization. Emerscient will help implement a knowledge base using LLM accelerator solution that will be used to include company or use-case specific context into LLM interactions. The output from such interactions may contain sensitive data, therefore requiring authorization prior to display. SecureGPT allows you to easily control who can view data produced by an LLM thus bridging the access controls gap.

 

Key Deliverables 
  • Define data sources and implement Knowledge base to production.
  • Implement SecureGPT along with defined access control policies to secure your organizations knowledge base. 
  • Define operational governance standards for secure use of Generative models within your business.

 

Design for Precision and Accuracy

For specific use cases, LLMs will require access to content in databases, perform complex math, reasoning functions or perhaps conduct public internet searches in order to achieve a goal, task or query. Our team will work with you to ensure the models operate with such functions/tools and are designed to perform as expected with precision and accuracy.

 

Key Deliverables
  • Chaining for specific functions/tools based on use cases tied to knowledge base 
  • Design secure prompting engineering and guardrail mechanisms for controlled output
  • Controls for input and output monitoring for responsible use
 

Envision AI

Large language models can provide significant benefits to businesses in various ways. The key to success when using AI like LLMs is to identify specific problems can be solved with them. It is also critical to choose the right LLM for the job and implement a solution that is secure and responsible.  

 

Overview

Our Envision AI offering is designed to help your business glean insights on the state of LLMs and identify key business problems that can be solved with LLMs in a secure and responsible fashion. Our team of experts will work with you to define business outcomes and formulate a strategy to choose the right LLMs to achieve them. 

 

State of LLMs today

Our experts will share our perspective of the LLM landscape today, including types of LLMs and common scenarios that are applicable to them. We will also share common use-cases across various industries applicable to LLMs.

Key deliverables 
  • Discuss current state of LLMs and common use-cases across industries. 
  • Importance of a Knowledge-base utilizing GenAccel to obtain specific outcomes. 
  • Value of prompt engineering and fine-tuning. 
  • De-risking your data/KB with SecureGPT.

 

Define problem statement

We will work with your stakeholders to brainstorm existing or new business ideas and identify key areas of LLM use. As a part of this exercise, we will work with your team to define desired outcomes as dictated by your business priorities.

Key Deliverables 

  • Gather feedback and brainstorm use-cases for LLMs in the context of your business. 

  • Define clear business objectives, prioritize use-cases based on impact.
    Ex: Improving customer service, reducing cost, improve decision making etc.     

  • Demonstrate the Emerscient approach with customer data. 

 

Choose LLM and evaluate feasibility

It is critical to choose the right tool for the job. Once the problem statement is defined, we will recommend LLMs options and work with your team to evaluate feasibility of deployment. 

Key Deliverables 

  • Identify appropriate LLM(s) for each prioritized use-case. 

  • Identify data sources and evaluate for quality and feasibility. 

  • Evaluate existing infrastructure and skills required to deploy and maintain LLM apps. 

  • Evaluate cost: Data acquisition cost, hardware/software cost, maintenance support costs. 

  • Evaluate potential risks: security, legal and ethical.