Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Few security practices carry as much weight as patch management. Consider the cautionary tale of Travelex. In early 2020, the British currency exchange was hit by a ransomware attack that spread quickly across its network, locking staff out of their systems. Reports suggest the company paid millions to restore access and prevent sensitive data from being sold; an outcome that underscores how a single gap in patching can cascade into a business-wide crisis.

Every IT team is under pressure to “do more with AI.” A new tool promises smarter workflows, a new agent claims to replace manual tasks. But if you’re managing service requests, availability SLAs, patch cycles, infrastructure capacity, and application performance every day, you know the truth: AI doesn’t automatically reduce complexity on its own.

Businesses everywhere are moving fast to adopt AI. Yet many initiatives are fragmented, siloed, difficult to scale, and lacking adequate governance. New research from Forrester Consulting, commissioned by Tines, surveyed more than 400 IT leaders in North America and Europe on the challenges of scaling AI and the role IT can play. The findings show that while governance, security, and cross-functional alignment are top priorities, they’re also some of the biggest barriers.

Did you hear the news? You can now build MCP Servers on Tines! Connect Tines stories to your LLM ecosystem in seconds using a new action template, enabling secure Model Context Protocol (MCP) server deployment. We also enhanced our AI usage reporting, allowing you to track AI adoption and manage costs more efficiently with better visibility into detailed AI reporting, including.

At the RSAC Conference this year, it seemed that every cybersecurity company had suddenly become an agentic AI company. According to such vendors, AI agents were the solution to every security problem keeping CISOs up at night. The audience, however, was understandably skeptical. Concerns over vendor promises fell into two camps. The first camp: companies that took whatever AI capabilities they had and slapped the word ‘agentic’ on them (aka ‘agent-washing’). Or even worse.

Financial services and insurance companies live under some of the toughest compliance rules in the world. Regulations keep multiplying. Cyber threats keep evolving. And the penalties for getting it wrong range from multi-million-dollar fines to reputational damage that takes years to recover. The problem? Too many GRC programs are still manual, reactive, and siloed. Outdated tools and processes force teams to spend countless hours chasing evidence and preparing for point-in-time audits.

At Tines, we use our workflow orchestration and AI platform to power our mission-critical processes, and the Revenue Operations team is no exception. In this post, we’ll share how we use Tines to automate a key part of our go-to-market motion: lead management. The workflow we’re sharing powers every inbound lead we receive, whether it comes from a demo request, a webinar sign-up, or a bulk CSV upload from the marketing team.

Model Context Protocol (MCP) is gaining traction because it enables LLMs to interact with live systems and enhance context by retrieving and managing relevant real-time information. LLMs can’t query Salesforce, trigger an Okta password reset, or fetch context from your SIEM, for example. MCP bridges that gap by connecting AI models to real-world APIs, powering AI applications like retrieval-augmented generation and multi-step agent workflows. They’re fast to deploy.

Over the past few months, the team has been working on some pretty cool things for the Tines platform. Check out this video for the biggest highlights, or use the following timestamps to jump to a specific topic.

At Tines, our mission is to power the world’s most important workflows. That extends to how you implement and control AI across your business. We're excited to introduce the ability to build Model Context Protocol (MCP) servers directly on your Tines storyboard.