Systems | Development | Analytics | API | Testing

Fast, Fair, and Frictionless: Reinventing Claims with AI and Workbenches

In insurance, the claims process is the real “moment of truth.” It's when customers find out if their insurer is truly there for them. They don’t just want fair treatment—they also expect their claims to be handled quickly and easily. But the reality? Claims often take way too long because of outdated, clunky processes. And the growing tsunami of data needed to adjust a claim can create information overload for an adjuster.

Chat SDK vs self-build: How to choose the right architecture for in-app messaging?

In-app chat has gone from a nice-to-have to an essential product feature across gaming, SaaS, social, and live streaming apps. While it’s tempting to treat it as “just another feature,” the reality is that building chat touches nearly every layer of your stack - from low-latency delivery and message ordering to presence, typing indicators, moderation. And then there is operating at scale to consider.

From Pawns to Pipelines: Stream Processing Fundamentals Through Chess

We understand new concepts by linking them to familiar ones. These analogies aren’t just helpful; they’re how we think. For me, that something familiar is chess, and I’ll use it to explain some of the core ideas behind stream processing—a concept that requires a shift from seeing tables as static snapshots to treating tables as materialized projections of a continuous stream of changes.

Boost Insights with Logilica's AI Advisor

In today’s data-driven environment, there is truly no end to the overwhelming amount of information that both contributors and users have access to. People often spend hours combing through logs trying to piece information into usable goods. This turns what could be swift, data-driven decisions, into time-consuming challenges that slow down innovation.

The Generative AI Boom: Crafting Tomorrow's Careers Today

Generative AI, once a niche area of artificial intelligence, has exploded into the mainstream, captivating the world with its ability to create everything from stunning images and compelling text to realistic music and functional code. Far from being a job destroyer, this revolutionary technology is proving to be a powerful job creator, forging entirely new career paths and redefining existing ones across virtually every industry. If you're looking to future-proof your career and ride the wave of innovation, understanding how Generative AI is shaping the job market is crucial.

13 Best Free Datasets for Call Centers and Telcos

Customer service chatbots and co-pilots and smart call center analysis applications are prime use cases for AI and generative AI. These AI systems and agents can provide real-time recommendations, support customer service at scale, generate insights that can be used in downstream applications to reduce churn and increase revenue, and more. How can customer service organizations grow and optimize their use of data and AI?

Machines That Learn Vs Machines That Imagine: GenAI Vs ML

Artificial Intelligence(AI) has recently become a hot topic across industries transforming sectors like finance, healthcare, education and research. The two of its subfields are Generative AI and Machine Learning(ML), but both of these terms are often confused for one another. we will explore the difference in purpose, techniques and capabilities and tools like Keploy’s GenAI-powered testing platform makes big difference in software testing.

What Agentic AI Demands from Your Data Strategy

If you’re leading a data, analytics, or AI initiative right now, you know the pressure. AI is no longer a future project - it’s a business imperative. Executives want results, boards want differentiation, and the window to deliver is closing fast. That’s why Salesforce’s intent to acquire Informatica should raise serious questions for data leaders. Not just because of what it means for Informatica, but for what it could mean for your AI roadmap.