BLOG

Accelerating Gen AI innovations with Gathr’s Gen AI Fabric

We continue to witness advancements in the realms of Gen AI and LLM with numerous startups pioneering innovative solutions and approaches to harness this evolving technology. According to McKinsey, Gen AI would increase the overall impact of AI technologies by 15 to 40 percent, adding $2.6 Tn to $4.4 Tn to global economy annually. While it has identified the impact across 63 major Gen AI business use cases, McKinsey says that three fourths of the value will be generated from just four major areas viz. customer operations, marketing and sales, software engineering, and R&D.

generative-ai-could-generate-additional-value

Source: McKinsey

McKinsey’s observations are in line with the current market trends. This is nearly 13 times more than the estimated growth of worldwide IT spending during the same five-year period.

However, it is hard for enterprises to keep up with Gen AI developments. Although Chat GPT has captured everyone’s imagination with its potential to democratize Gen AI and LLMs, most organizations don’t possess the maturity and technical readiness to adopt the latest developments in this rapidly evolving field. Most organizations can prepare a prototype, but operationalizing Gen AI powered solutions is not always as straightforward as it seems.

Gathr recognized these challenges and added capabilities to its data to outcome to platform to enable enterprises build production-ready Gen AI solutions quickly. In this article, we will explore how Gathr helps its users build innovative Gen AI solutions with ease.

Gen AI fabric – the go to Gen AI framework for enterprises

Gathr recently launched Gen AI fabric, an integrated platform approach to building Gen AI solutions over a visual canvas. Gen AI fabric allows users to leverage augmented data pipelines, plug-and-play Gen AI operators, reusable solution templates, and flexible deployments over distributed environments. With Gen AI fabric, users can now leverage ready integration with major LLM providers to accelerate Gen AI application development. While Gathr already offers several features for model training and operationalization, the new integrations further simplify Gen AI application development for businesses.

What are Gen AI operators

If you are an existing Gathr user, you might be aware that Gathr offers several out-of-the-box operators (processors), which can be dragged and dropped into your pipelines for data processing and model training purposes. In the same way, you can now use OpenAI and Azure OpenAI operators in your pipelines to create Gen AI applications. Gathr will be adding more such operators in the coming months to help you quickly integrate with LLM providers.

How to build a Gen AI application on Gathr

A typical LLM use case involves processing large volumes of structured and unstructured data, which could be in the form of social media content (posts, comments, tweets, etc.), medical diagnostic data across millions of patient records, financial reports, etc. Gathr helps you easily collect all such data using pre-built connectors. Whether unstructured data in formats like PDFs, emails, and images, or structured data in JSON or CSV formats – Gathr supports everything.

Once you have ingested the data, it needs to be processed before you apply LLM models. Gathr helps you perform advanced transformations using drag and drop processors, parsers, and other tools to turn your data into AI consumable formats easily. Once the data is ready, you can integrate with LLM providers like OpenAI, Azure OpenAI, and more using the Gathr’s Gen AI operators.

You can use system and custom prompts to guide LLM providers. As Gen AI models don’t always produce the most accurate response, you might need to tweak the prompts, use sample data and submit requests multiple times till you start getting the desired responses. You can also include a previous response as an input while resubmitting the requests or specify additional prompts to your model to improve LLM responses. This is where GathrIQ, Gathr’s own Gen AI powered chat assistant can help you out; it can automatically iterate and resubmit your requests till you get the desired output.

Finally, you can use the Gen AI output to solve your use cases. For instance, you can persist the data in your preferred storage or use Gathr’s data visualization and analytics capabilities to create interactive dashboards and draw actionable insights. Here are some examples of use cases you can solve leveraging Gen AI:

  • Summarize complex information from thousands of documents such as candidate resumes, legal documents, financial statements, social media content, and more.
  • Analyze medical diagnostic reports with better accuracy and speed.
  • Use Gen AI powered recommendations to deliver personalized media (videos, articles, music, etc.).
  • Integrate with Vector databases to power RAG use cases, bringing additional context to LLMs by using the context from a vector search to refine user prompt.
  • Build and expand knowledge graphs by extracting, linking, and organizing information from various sources.
  • Train your chatbots on custom data to improve customer service and tech support.
  • Augment product information management (PIM) systems for e-commerce.
  • Optimize migration of legacy code using natural language.

The road ahead

As leading LLM providers are continuously rolling out new updates, it is important to keep up with these developments. Gathr frequently updates its Gen operators and is also going to add many new operators to its platform to improve Gen AI capabilities. As an enterprise-grade data to outcome platform, Gathr also ensures that your application development journeys are always fully secure and compliant. As the road ahead unfolds with the evolution of Gen AI, Gathr remains a steadfast partner in driving innovation and realizing the full potential of this transformative technology.

Recent Posts

View more posts

Blog

GathrIQ: Unleashing the power of Gen AI in data...

Blog

GathrIQ - Unleashing the power of Gen AI in data...

Blog

50X faster time to value with Confluent and Gathr...

Blog

Data + AI summit 2023: A must-attend for data scientists,...