Systems | Development | Analytics | API | Testing

AI-Powered Loan Management Software Development

The world has really come a long way due to widespread digital transformation adoption! And, it’s no secret that it has changed the FinTech sector drastically. In light of this evolution, it has become imperative for lenders to adapt and refine their operations with a well-defined Loan Management System.

Fee Transparency: New Rules for Real Estate Listings in 2026

Fee transparency in rental listings is no longer a design or disclosure detail, but a regulatory and commercial requirement for real estate and PropTech platforms. Recent FTC enforcement actions and accelerating state legislation now say that pricing logic must be explainable, consistent, and defensible across every channel where rent is shown. Real estate companies using listing platforms, PMS tools, marketplaces, or leasing experiences now need to update their sites and comply with the new regulation.

What Is MCP? Connecting AI Across the Software Delivery Lifecycle

AI promises speed and automation — but most teams are still stuck jumping between disconnected tools across development, testing, and operations. In this video, we introduce the Model Context Protocol (MCP) and how it enables AI assistants to securely access tools, systems, and real-time context across the software delivery lifecycle. MCP is the foundation of Perforce Intelligence, allowing AI to: The result: less friction, faster feedback, and AI that works with your existing systems — not around them.

Identity Passthrough for AI: Why Your LLM Needs to Know Who's Asking

When a user asks your AI assistant a question, who actually runs the database query? In most enterprise AI deployments, the answer is troubling: a shared service account with broad access to everything. The user's identity evaporates the moment their request enters the AI system. This architectural pattern creates security gaps, compliance failures, and data leakage risks that undermine enterprise AI adoption.

What is an MCP? Breaking Down the Model Context Protocol

70% of teams are already integrating generative AI tools into their daily workflows, according to our 2025 State of Game Technology Report. Now more than ever, teams are looking to connect their AI tools to the services and applications they rely on to get work done. To address this issue, the industry has begun to standardize using the Model Context Protocol (MCP) to connect their existing tools and LLMs like Claude, GPT, and Gemini.

Building Secure AI Agents with Kong's MCP Proxy and Volcano SDK

Modern AI applications are no longer just about sending prompts to an LLM and returning text. As soon as AI systems need to interact with real business data, internal APIs, or operational workflows, the problem becomes one of orchestration, security, and control. The challenge is to build secure AI agents without embedding fragile logic or exposing sensitive systems directly to a model. This is where a layered architecture using Volcano SDK, DataKit, and Kong MCP Proxy becomes compelling.

Escaping the Integration Tax: Why Your Partners Are Stuck in Limbo (and How to Onboard in Days, Not Months)

In a high-interest-rate environment, the most expensive asset a bank can hold is a signed partner contract that isn’t generating transaction revenue. For many regional banks, the 4–6 month gap between “contract signed” and “first transaction” is driven by manual compliance reviews, fragmented security processes, and custom integration work that delays go-live. We call this the “Integration Tax.”

How DreamFactory Accelerates SOC 2 Compliance with Secure API Management

DreamFactory is a secure, self-hosted enterprise data access platform that provides governed API access to any data source, connecting enterprise applications and on-prem LLMs with role-based access and identity passthrough. Organizations working toward SOC 2 compliance face a familiar set of challenges: inconsistent access controls, fragmented data access security, noisy or incomplete logs, risky custom integrations, and difficulty proving governance during an audit.