Pyramid Analytics

The Power of Generative AI with Pyramid

Pyramid’s generative AI analytics platform, ranked number one by Gartner in 2022 and 2023, enables seamless, secure, and scalable direct integration with existing data sources like Snowflake and Redshift, allowing organizations to rapidly generate accurate insights and make data-driven decisions without duplicating or moving data, while ensuring data privacy by only sharing plain-language queries and necessary metadata with language models.

If you’re looking to take your analytics game to another level, Pyramid’s latest set of generative AI features will change the way you work—specifically, how you analyze data, make decisions, and enable an environment where anyone in your organization can ask anything and get the right answer in seconds.

In both 2022 and 2023, Gartner ranked Pyramid the number one augmented and AI analytics platform. So, what makes Pyramid stand out from the crowd? Let’s break it down.

Plug-and-Play Directly on Your Data

The platform connects directly to your current data sources like Redshift, Snowflake, Databricks, Microsoft Fabric, and SAP. This approach delivers rapid insights, avoids data duplication, and scales with your organization.

This is not an insignificant issue. Imagine you’ve just ported your entire data lake strategy to something like Snowflake. Without the right strategy, you’re left with three bad choices:

  1. 1.Re-shift the data to another data stack so it can operate with a copilot tool;
  2. 2.Duplicate your data lake (again!) so it can be accessed;
  3. 3.Or, worst of all, sit out the Gen-AI revolution until your tech works!

The fourth option, and arguably the best, is to put Pyramid’s Gen-AI solution directly on top of Snowflake. It will work instantly, out of the box. Don’t move data. Don’t change data strategies. Start using Gen-AI tomorrow morning.

Keep Your Data Secure

Ensuring your data remains private and secure must be top of mind when deploying LLMs. The mere thought of your data being leaked into the public domain could be catastrophic.

That’s why Pyramid never shares your actual data. Instead, the platform only passes the plain-language request and the context needed for the language model (LLM) to generate the recipe needed to answer your question.

For example, when I ask the chatbot a question on sales and costs for each of your regions, Pyramid will pass the LLM the message along with certain information such as metadata, schemas, and semantic models for further context.

Notice the actual data isn’t sent itself. The LLM will then use its interpretive capabilities to pass us back an appropriate recipe response which the Pyramid engine will then use to script, query, analyze, and build content.

Data security is a primary concern and Pyramid is making sure your data is protected behind the scenes while everything else is happening right before your eyes.

Sophisticated Handling of Complex Tasks

For the average person, driving sophisticated analyses can be too complicated.

Pyramid has put self-service first and foremost, always striving to make it easier to do more by yourself.

And now generative AI in Pyramid has made self-service even more accessible.

From data prep and analysis to publishing, you can compile unbelievably complex analyses and create multi-layered content using everyday language both in text and speech.

For example: a formal report for distribution. As you might know, creating a report to distribute to a group of users can prove quite an onerous job – It’s not something I really enjoy doing. So, I launched Pyramid’s chatbot and without even touching my keyboard, I literally asked it to create a multi-page report on sales performance for the region, with a summary of key metrics, KPIs, several charts on the customer, products, promotions, and manufacturers. All neatly formatted with logos, headings, and footers. Done!

All these capabilities are out of the box, and I barely lifted a finger.

The Right LLM for the Right Job

You wouldn’t ask your accountant for a medical opinion.

That’s why Pyramid has embraced a ‘multi-LLM’ strategy, enabling customers to attach specific LLMs to the right data problem. This flexible approach caters to the varying needs of organizations, accommodating generalized, specialized, verticalized, and ultimately customized (fine-tuned) LLMs.

For example, LLMs specifically focused on health insurance data will better understand the health sector’s distinct industry terms, nuances, and key metrics, providing users with more sophisticated and accurate answers to their questions.

And while the Gen-AI marketplace is still maturing and such domain-specific LLMs are still in the works, Pyramid is already designed for that eventual outcome.

In Conclusion

To round up, Pyramid’s approach is the next level of generative AI and will provide your organization with an innovative, scalable, and secure decision-making solution that integrates seamlessly with your existing data infrastructure.

If it’s more complicated than that, I’d suggest you question the solution you’re considering. Maybe even use that tool to get the answer: “Hey co-pilot, why can’t I do that?”