Posts by: narwal@
Smarter AI for the Enterprise: Agentic RAG and Intelligent Automation
As enterprises embrace Large Language Models (LLMs) for automation, they’re discovering that raw language capabilities alone aren’t enough. Enter Agentic RAG (Retrieval-Augmented Generation) a next-generation approach combining the reasoning power of LLMs, real-time information retrieval,…
- May 30
Unified, Intelligent, Scalable: Why Next-Gen Frameworks Are the Future of Test Automation
As software development speeds up, test automation must evolve with it. Yet, many enterprises still rely on fragmented automation setups multiple frameworks, scattered pipelines, inconsistent maintenance. The result? Slowed releases, rising defect rates, and mounting…
- May 23
Intelligent Solutions for Modern Enterprise Challenges: Automating Quality, Accelerating Transformation
The enterprise technology landscape is evolving faster than ever yet global organizations still face familiar pain points: fragmented quality assurance processes, rising costs, increasing compliance demands, and the pressure to release faster without compromising accuracy….
- May 09
The Automation Advantage in Data Integrity: Preventing BI Reporting Failures
In the modern enterprise, data is not just a byproduct of operations—it is the foundation of strategic decisions. Nowhere is this more evident than in Business Intelligence (BI) dashboards, which inform investments, resource allocations, customer…
- May 02
From Data Lake to Business Assurance: Transforming Unstructured Data Management with Tricentis and Narwal
Data lakes have become the preferred storage for unstructured data in enterprises, offering the flexibility to accommodate diverse data formats. However, the rise of unstructured data in data lakes brings with it new challenges in…
- Apr 17
Unlocking Confidence in Unstructured Data: Addressing Top Challenges in the Data Lake Ecosystem
As organizations expand their digital transformation efforts, they increasingly rely on data lakes for unstructured data storage and analysis. Unstructured data text files, XMLs, raw logs doesn’t fit into traditional data structures, making it complex…
- Apr 17
Establishing a Gen AI Center of Excellence: A Strategic Imperative for Enterprise Transformation
Introduction Generative AI (Gen AI) has transitioned from experimental pilots to enterprise-scale transformation drivers. Organizations across sectors are investing in Gen AI to accelerate innovation, automate complex tasks, and enhance decision-making. However, the journey from…
- Apr 11
LLMs and Agentic AI: Building the Future of Autonomous Intelligence
Large Language Models (LLMs) are evolving rapidly—and with them, a new era of intelligent, autonomous systems is emerging. From conversational AI to fully agentic systems that plan, reason, and act independently, enterprises are now at…
- Mar 28
AI in DevOps: Driving Intelligent Automation and Continuous Delivery
In today’s fast-paced digital landscape, the pressure to deliver high-quality software faster and more reliably has never been greater. Traditional DevOps practices have made significant strides in bridging development and operations—but with increasing complexity, scaling…
- Mar 21
AI-Driven Data Integrity: Ensuring Trust, Security, and Compliance
In an era where data drives business decisions, AI-driven data integrity has become a strategic imperative. Organizations collect, process, and store vast amounts of data, but without proper integrity measures, data can become inaccurate, inconsistent,…
- Mar 14
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