Generative AI

Dive into how enterprises are applying generative models across text, image, audio, and beyond. This section captures lessons from real deployments, from early experimentation to production-grade applications.

Trending Products

The most endorsed generative AI solutions on Sagetap, backed by real-world validation from enterprise teams.
1.
Backslash Security
Backslash offers the Unified Vibe Coding Security Platform , the definitive solution for managing the security risks introduced by the rapid adoption of AI-augmented development, also known as "vibe coding". We provide B2B organizations with the preemptive security controls necessary to secure their entire Generative AI development ecosystem, ensuring both speed of innovation and continuous security. The Problem: The rise of AI coding IDEs and agents has created a new governance and security blind spot for engineering teams. Backslash research has shown that popular LLMs, when used with simple or "naive" prompts, frequently generate code that is insecure or vulnerable. Relying on developers to craft effective security prompts is unrealistic, leading to vulnerable code 40%–90% of the time. Furthermore, the introduction of unvetted MCP (Model Context Protocol) servers presents unacceptable infrastructure and data security risk. The Backslash Value Proposition: Vibe Securing. Backslash addresses this challenge by shifting the mindset from merely detecting vulnerabilities after code is written to preventing their creation before code is generated. We call this "vibe securing". The platform provides the built-in guardrails and context-aware system needed to achieve true "security by design" for AI-generated code. Key Platform Capabilities: Visibility and Governance: Gain full visibility into where developers are using AI coding agents, which LLMs are active, and which MCP servers and prompt rules are in use across the developer infrastructure. The Vibe Coding Dashboard provides an immediate assessment of their security posture. Secure AI Prompt Rules: Preemptively create secure code using prompt rules that automatically enhance developer input to adhere to security best practices. These rules are transparent to developers, resulting in secure code that is free of vulnerabilities and exposures from the start. Ecosystem Hardening: AI Agent and IDE Hardening enforces uniform configuration across Agentic IDEs (like Cursor and Windsurf) to fence off agentic AI, reduce the attack surface, and prevent unexpected behaviors. MCP Server Security allows you to analyze and vet MCP servers to prevent excessive permissions and insecure configurations that could be exploited by malicious actors. Contextual Risk Mitigation: The proprietary Backslash App Graph Model provides a core code security engine that models the application. It ensures findings are contextual from the outset, eliminating noise and false positives by only flagging vulnerabilities that have a real, demonstrable risk attached. This empowers developers with actionable, real-time security guidance directly in their workspace. Backslash boosts AI adoption across software engineering teams by providing governance and preemptive security controls for security and AI governance teams

Recent Initiatives

Peer-driven generative AI projects in motion, with direct access to the Sage leading each initiative.
Active
Last Modified: Dec 05 '25

Knowledgebase Transfer and End User Adoption

Goal:
Tool consolidation into unified service.
by
Jul 31 '26
Objective: To create a unified, intelligent, and scalable framework that enhances knowledge accessibility, drives adoption of collaboration and AI tools, and empowers employees through targeted, role-based training—without disrupting productivity. Problem Description: Our organization is currently facing fragmentation in how knowledge is stored, accessed, and shared. Legacy systems like Confluence and SharePoint contain outdated or siloed content, while newer platforms like ServiceNow are underutilized. Simultaneously, the adoption of Microsoft 365 tools and Power Platform is inconsistent, and employees often lack the time or context to fully engage with training resources. The growing interest in generative AI tools adds another layer of complexity, as employees need guidance on responsible and effective usage. Desired Outcome: This initiative aims to centralize and modernize knowledge management, streamline the onboarding and enablement of collaboration and AI tools, and deliver contextual, just-in-time training. By integrating ServiceNow as the knowledge hub, promoting best practices for M365 and Power Platform, and embedding Gen AI tools into workflows with clear governance, we will reduce friction, improve productivity, and foster a culture of continuous learning and innovation.
Fixify
Fixify
Interested
Ray Security
Ray Security
Interested
Import and Export
5,001 - 10,000

Where is your team focusing generative AI efforts?

As capabilities expand, so do the ways generative models reshape enterprise workflows.

It's Time to Rethink How Enterprise Technology Is Bought and Sold

Join the platform where decision-makers and innovators connect to shape the future of enterprise tech.