By
Shivika Sharma
July 23, 2024
•
5
min read
"With GenAI copilots, you're not just keeping up with the future—you're generating it," said John Doe, CTO of Tech Innovators. This powerful statement captures the transformative potential of Generative AI in today’s business landscape. For systems integrators (SIs) and tech consulting firms, leveraging GenAI copilots can be the secret weapon to outpace competitors and deliver unmatched value to clients. Picture an AI that not only automates mundane tasks but also provides predictive insights, making smarter decisions and streamlining operations. The potential is staggering, and the benefits, game-changing.
In this blog, we explore the myriad applications of GenAI copilots, the development timelines, the strategic advantages of internal development, and the superiority of open-source models over proprietary ones. Whether you're aiming to optimize current operations or find innovative ways to enhance client services, GenAI copilots are the future of SI and tech consulting. Dive in to learn how they can elevate your business to new heights.
Exploring the Current Landscape of GenAI Copilot Use Cases
GenAI copilots are revolutionizing industries with their wide array of applications, offering transformative solutions across various sectors. Here’s a closer look at the diverse use cases:
These diverse applications demonstrate the versatility of GenAI copilots and their potential to transform various business functions.
Learn more about GenAI use cases here
Development Timeline for GenAI Copilots
The development timeline for GenAI copilots can vary depending on the complexity of the project and the specific requirements of the organization. Here’s a breakdown of typical development times:
Real-World Implementations:
Source: https://aimresearch.co/council-posts/gen-ai-in-software-development-revolutionizing-the-planning-and-design-phase
Why GenAI Copilots Should Be Developed Internally
Developing GenAI copilots internally offers several compelling advantages, ensuring that the solutions are perfectly aligned with the specific needs and security requirements of the organization.
Advantages of Internal Development:
Case Studies:
These examples underscore the benefits of internal development and how it can lead to significant improvements in business operations.
Why Choose Open Source Models Over GPT/Claude
Choosing the right AI model is crucial for maximizing the benefits of GenAI copilots. Here’s a comprehensive analysis comparing open source models with proprietary models like GPT/Claude:
Open Source: With open-source models, organizations have complete visibility into the code and data handling processes. This transparency allows for thorough security audits and the implementation of customized security measures to protect sensitive data. Open-source models can be hosted on-premises, further enhancing data control and reducing the risk of data breaches associated with third-party hosting.
Closed Source Models: Proprietary models often operate as black boxes, providing limited insights into how data is processed and stored. This lack of transparency can pose significant security risks, particularly for organizations handling sensitive information. Additionally, these models typically rely on cloud-based services, which may introduce vulnerabilities related to data transmission and storage.
Open Source: Open source models can be hosted on modest infrastructure including CPUs. Cloud services are an order of magnitude cheaper than commercial models.
Closed Soruce Models: Often come with high subscription fees, which can be a significant financial burden for some organizations.
Open Source: Highly customizable, allowing organizations to tailor the models to their specific needs. Open-source models offer the flexibility to finetune on their specific requirements.
Closed Source Models: Limited customization options, as the source code is not available. Organizations must rely on the provider for any modifications or enhancements.
Open Source: Full control over the model and its updates. Organizations can decide when and how to update their AI models, ensuring continuous alignment with their business objectives.
Closed Source Models: Dependent on the provider for updates and changes, which may not always align with the organization's needs.
Open Source: Large, active communities contribute to rapid development and troubleshooting. This collaborative environment fosters innovation and provides a wealth of resources for resolving issues.
Closed Source Models: Limited to the provider's support channels, which can be less responsive and flexible.
Examples:
Meta: You can use Meta AI in your WhatsApp group chats to ask questions or get advice. It is powered by the LLama herd of models.
NVIDIA: Leverages open-source frameworks for AI development, accelerating innovation. NVIDIA's open-source initiatives have led to significant advancements in AI and machine learning technologies.
Google: Employs open-source models like TensorFlow for various AI applications, fostering community collaboration. TensorFlow's open-source nature has made it a leading platform for AI research and development.
Red Hat: Uses open-source AI for cloud solutions, enhancing flexibility and control. Red Hat's commitment to open-source principles ensures that their solutions remain adaptable and cost-effective.
How Insituate Can Help
Insituate revolutionizes enterprise AI by enabling businesses to build state-of-the-art, secure copilots on-site within a day.
Our model Zoo:
Insituate hosts a variety of the cutting edge open source models in the LLM Studio.
We had early belief in the opensource community, which has now been outperforming some of the commercial LLMs.
The only true secure AI:
We go beyond data encryption at rest and transit. To thrive in some of the most regulated sectors such as banking, judiciary and healthcare, we empower the client into streamlining self deployment on-premise on VPC.
Turn around time:
Not months, not weeks, but businesses can create copilots with our platform in under a day! To enable rapid and meaningful integration of GenAI into a complete enterprise ecosystem, it takes time to iterate and test across different versions of copilots. AutoLLM will autonomously search for the best configuration in under a day.
Plethora of use cases:
📊 Report Generation Copilot, 📈 Stock Trading Copilot, and 📋Mind Map Copilot
AutoLLM:
AutoLLM is our proprietary technology that builds reasoning engines powering the copilots. Reasoning engines are more advanced than any LLM/ AI agent in the world - as they are made specifically for the user and by the user!
