Data & AI
4 mins

Investing & Building an AI & Data Fabric within the Enterprise

Explore how Gruve is empowering enterprises to transform customer experience, streamline operations, and leverage AI for sustainable growth.
Illustration of AI data fabric integration for enterprise efficiency and data-driven decision-making.
Written by
Tarun Raisoni
Published on
November 8, 2024

The ability for every individual in the enterprise to be empowered with the right information, execute more efficiently and enable data-driven decisions, brings significant productivity, competitiveness, and business advantages.  

Imagine a transformed customer experience within the enterprise, where every step – from capturing requirements and assembling the right product, to delivering it and ensuring an exceptional outcome – is seamlessly enabled and efficiently tracked. This approach guarantees a delightful experience for the customer at every stage.

Large enterprises have the natural advantage of larger data pools, access to talent, and the ability to spend on the resources required to make this happen. This advantage is now being democratized in two ways: one is AI Platforms are becoming accessible, and two, you do not need a massive army of resources to make this happen, expert talent can help you get there quickly.  

At Gruve, we are exploring ways to provide these outcome-oriented services capabilities to various enterprises, and we are continually investing into areas that are extremely relevant to the day to day within the enterprise. I will outline this strategy with our core services offerings and why -

  1. Cybersecurity: Enterprises do not get a weekend off from hackers or an emergency warning. This is something that every day the CISO, CIO, and other C-level execs of enterprises worry about. Cybersecurity is expensive, resources are limited, and hence it is crucial to leverage AI-powered cybersecurity solutions to make this simpler, all the way from day-to-day monitoring to Architecture conversations for the future.
  1. Cloud Engineering: All sorts of workloads exist today in enterprise; they are either on-prem (Colocation included) or in cloud. They were designed either in a monolithic manner (Data Silos) or micro-services based. Enabling your enterprise to leverage the latest technologies and unlocking the Data Silos is critical. Enterprises that get to this faster will grow faster. Think of this as a Revenue Unlock, and AI is at the forefront of enabling this in both on-prem and on cloud.  
  1. Data Life Cycle Management (DLCM): Data Life Cycle Management (DLCM): The most valuable data sits in enterprises, usually behind the firewall, for very good reasons. To maximize its potential, it’s crucial to have a robust data strategy that ensures data is relevant, active, and accessible for both structured and unstructured use.
  1. Platform Engineering: Every product today has a digital life element to it. Architecting your product as a platform and enabling the data strategy in your product is key to enabling a broader strategy of continuous customer engagement with your products or solutions. AI will eventually get embedded in every digital platform of our lives.  

We built some of these offerings keeping in mind that enterprises genuinely care about -

  • Faster Time to Market
  • Lower Cost Delivery Metrics
  • Superior Customer Experience
  • Value Driven Approach  

To cater to Enterprises further, we are very pleased today to announce that we have acquired Trusli AI, with Charlotte Tao leading the Data & AI practice within our team. We look forward to welcoming the team and continuing our growth within the enterprise customer space.  

As a seasoned data scientist, Charlotte has built an impressive career through key roles at Salesforce, Uber, Zoox, and Lyft, where she showcased her technical leadership by creating impactful AI products, including supply and demand forecasting algorithms and self-driving technologies. As the co-founder of Trusli, she advanced her AI expertise by developing automation solutions powered by large language models (LLMs) for enterprise customers. In her new role at Gruve, Charlotte will leverage her AI expertise to serve a wider range of enterprise customers and drive even greater impact.

We are also looking at ways in which we can continue to enhance our practices, our solutions, and our team. Feedback is an important part of our culture, and I would very much welcome it.