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@elenamia shared a post, 6 months, 4 weeks ago
Technical Consultant, Damco Solutions

Why Enterprises Are Moving from Break-Fix to Proactive Application Maintenance and Support

Discover why forward-thinking enterprises are replacing break-fix models with proactive application maintenance.

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@brooksamybrook shared a post, 6 months, 4 weeks ago
Executive, CMARIX InfoTech

How to Assess and Improve Growth with the AI Maturity Model

AI maturity measures an organization’s ability to generate consistent business value from AI across strategy, data, people, and technology. The AI Maturity Model spans four stages—Initial, Repeatable, Defined, and Optimized—guiding firms from experimentation to full AI integration. Assessing AI maturity helps identify gaps, align investments, and turn AI from scattered projects into a sustainable, strategic advantage.

Assess Your Organization’s AI Maturity Model
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@arunsinghh011 shared a post, 6 months, 4 weeks ago
Business associate, Xcelore Private Limited

Building the Future: The Art of Smart AI Product Development

Have you ever wondered when “AI” stopped being a sci-fi buzzword and started showing up in your morning to-do list? Somewhere between that first predictive email and the chatbot that apologizes better than most customer reps, it happened. Quietly. Suddenly. Like caffeine sneaking into your bloodstream before the day really begins. That’s where AI product development services come in—not as some sterile tech jargon, but as the very engine redefining how we build, think, and work.

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@alexgrave876 shared a post, 6 months, 4 weeks ago
Content writer, Alpharive

The Architecture of Agentic AI: Building Machines That Think, Act, and Evolve

Explore the layered architecture of Agentic AI—how intelligent systems observe, reason, and act within their environments. Learn how perception, reasoning, and action layers create adaptive, self-improving machines built for real-world decision-making.

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@viktoriiagolovtseva shared a post, 6 months, 4 weeks ago

Why Use Atlassian Forge? Benefits, Pricing & Use Cases

Why Atlassian Needed a Modern App Development Platform

Building apps for Jira, Confluence, and other Atlassian products has traditionally been a resource-heavy process. Developers had to configure their own servers, ensure uptime, and pass rigorous security checks to get their apps approved for the Atlassian Marketplace. This setup required both development expertise and operational support, slowing app development and increasing costs.

Atlassian Forge was introduced to eliminate these barriers. It is a modern cloud-based app development platform that allows developers to build secure, serverless apps directly within Atlassian’s infrastructure. Forge simplifies building apps, giving developers more time to focus on functionality, while Atlassian handles hosting, security, and scaling.

This article explains Forge’s core features, key benefits, pricing model, and common use cases. Whether you are a developer considering your first Atlassian app or a team looking to transition from Connect to Forge, this guide will help you decide if Forge is the right solution for your business.

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@viktoriiagolovtseva shared a post, 7 months ago

Jira For HR: How to Automate HR Processes And Use Checklists in Jira

The more you can automate, the more time you will have for the “H” part of HR—humans. In addition to freeing up time, automation brings you many other benefits. It allows you to build clear and transparent processes, create a smooth employee experience, and improve retention rates.

In this blog post, we explain how to set up various types of automation in Jira for HR management purposes.

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@anjali shared a link, 7 months ago
Customer Marketing Manager, Last9

Sidecar or Agent for OpenTelemetry: How to Decide

Sidecar or agent? See when per-service isolation beats node-level efficiency, and how gateways fit into a scalable OTel pipeline.

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@laura_garcia shared a post, 7 months ago
Software Developer, RELIANOID

In case you missed this update 👇

🌏 Asia Hits 50% IPv6 Capability — A Global Milestone 📶 Asia has officially crossed a key internet threshold: half of all systems in the region are now IPv6 capable, making it a global front-runner in IPv6 adoption. 📌 Why it matters: 🌐 India (78.1%) and China (810M users) are powering this impressive..

apnics top performers relianoid
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@mashka shared a post, 7 months ago
Paid Acquisition and Growth Marketing, xygeni

Why Tool Sprawl Is Hurting AppSec More Than Helping It

Why Tool Sprawl Is Killing AppSec Productivity?

Modern engineering teams ship software faster than ever, but security tools haven’t kept up. Instead of helping, they often slow everything down. With multiple scanners, dashboards, and sources of truth, AppSec has become noisy and fragmented.

All in One Appsec Platforms
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@laura_garcia shared a post, 7 months ago
Software Developer, RELIANOID

Safeguarding Protected Health Information with RELIANOID 🛡️

RELIANOID aligns its organizational practices and Load Balancer platform with the HIPAA Security and Privacy Rule safeguards, ensuring the protection of electronic Protected Health Information (ePHI). ✅ Administrative, physical, and technical safeguards in place ✅ Encryption (TLS v1.2+, AES-256), RB..

HIPAA compliance RELIANOID
Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.