Build Lab – GenAI

Generative AI is reshaping enterprise technology, revolutionizing processes and decision-making. Through advanced machine learning, it can automate tasks, enhance efficiency, and provide innovative solutions to complex challenges. This transformative technology is propelling businesses into a new era of productivity, strategic insight, and competitiveness.

With enterprise-grade security and privacy, access to industry-leading foundation models, and generative AI-powered applications, AWS makes it easy to build and scale your generative AI applications, customized for your data, your use cases, and your customers. Integrating these powerful new tools and technologies into your existing enterprise architecture is the next milestone in your organizations’s cloud journey.

The GenAI Build Lab is a cooperative engagement spanning 4-6 weeks which culminates in a one-week build activity guided by a Uturn Senior Architect. The build team consists of your developers, or Uturn engineers, or a combination of both, depending upon your needs. We believe collaboration is the best approach because it includes your builders from the beginning, reducing knowledge gaps.

Leading up to the engagement, you will have an assigned project manager and Senior Architect, and through a series of planning meetings we step through your use cases, assess your current state, propose an architecture, and ensure that the team is ready to build.

The result of build week is a pilot implementation of your application, built using AWS services alongside tools or SaaS offerings that are already in your arsenal.

GenAI Build Lab Deliverables

When the lab is complete, you will have a pilot version of your application with the following attributes:

• Live Environment: Built and running in your own AWS environment
• Proven Use Cases: Deliverables are focused on connecting components and proving out critical functionality
• Actionable Playbook: Work is not “throw away”. Uturn will leave you with a plan to iterate the application all the way to production future use cases.

Examples of In-Scope AWS Services

Example Use Cases

• LLM Assisted Coding using Code Whisperer
• Content Translation from one market to another market
• Content Creation for Business Application like Marketing Materials, Product Description, etc
• Integrate GenAI application as part of existing Business Workflow
• Consolidate multiple upstream source systems into a single data warehouse, then provide dashboards and gen AI to your key decision makers
• LLM chatbot training on your organization’s data, enabling natural language insights for your users
• Intelligent Document Processing to make the contents of your organization’s contracts and invoices available to analytics tools, chatbots, and data science teams
• Enforcing Data Privacy and Security in the right way to the GenAI Use
• Improving Customer Service and Operations through auto Email Generation based on specific customer queries and requests