This article was also published on LinkedIn
AI-based applications and workflows are showing up in headlines and Board rooms, and for good reason: Many companies still struggle with routine paperwork and business processes across their business functions that demand expensive, ongoing manual effort. Conventional software applications can’t analyze complex, human language documents, evaluate them against corporate policies and other rules, then make intelligent decisions and take appropriate actions, leaving humans to deal with this repetitive toil.
But AI agents powered by LLMs like Claude, chatGPT, Gemini, and others offer a new form of “digital journey” – one that lets companies of all sizes and sectors use AI to power business processes and applications. Using AI to automate routine document-based workflows can lower costs and error rates, improve staffing efficiency, and enhance both customer and employee experiences.
But getting to those outcomes has one critical, challenging requirement: You can’t AI-optimize a business process without first hooking your AI up to your real-time business data and systems. LLM retraining and RAG-based solutions have their place, but to be useful to the business, agents need to be able to not just look at a document but also make changes and interact with operational systems and services. That’s where MCP, the Model Context Protocol, comes in. MCP is the “HTTP of AI” – just like the HTTP protocol made the Internet possible, so too MCP makes enterprise AI possible, by allowing AI agents and enterprise systems to communicate.
But just like HTTP, MCP is only a protocol – a set of “rules and regulations”, not a product or a service. To actually get AI and enterprise systems talking, you need to write code to implement the MCP protocol and integrate it with your enterprise resources, rent servers and deploy your MCP server code to them, monitor service uptime, etc. Or at least, you did before today.
To help companies get to AI solutions faster and easier than ever before, Vendia has launched a free tier MCP-as-a-Service, initially with support for Amazon S3 buckets. We chose S3 for our initial release because it’s the world’s largest storage service, with more data under management for more companies than any other storage service. From SMBs to the Fortune 100, many companies use S3 to house their business critical documents and to implement mission critical business workflows and applications, making it an obvious target for AI-related optimizations. And now with Vendia’s MCP offering, companies can connect documents, images, and other assets in all their S3 buckets to AI clients without writing code.
You can learn more about Vendia’s free, fully managed S3 MCP offering in our launch blog, but here I wanted to focus on some of the powerful business outcomes companies can achieve with it, without needing to invest in complex software development to get started using AI. I’ve highlighted some of these below, by business function.
Sales & Marketing
For go-to-market teams, connecting AI to business documents is a no brainer. AI can help identify and score leads based on customer conversations, intake form content, website visit logs, and with email, call, or video transcripts. AI can also help create personalized content, enabling even small sales and marketing teams to deliver crisp, targeted content to every prospect that’s highly tuned for their particular interests and needs. FAQs, product manuals, pitch decks, website content, and more can be automatically converted into a customer-centric version that helps deliver just the right amount and focus of content for that audience. And on the operational side, AI can help with sales forecasting, using past and present data from sales reports, deal notes, customer communications, and more to identify patterns and predict current and future trends. It can also help analyze won/lost data to identify patterns of success and failure.
HR and Recruiting
HR teams are frequently understaffed and overburdened. But they’re also often a document-centric function, making AI a useful tool to assist with multiple workstreams. On the recruiting side, AI agents can help tune job descriptions, review and rank resumes to maximize the company’s attention on the best candidates, and help automate candidate communications and interview scheduling. For existing employees, AI can help create and analyze feedback surveys and performance reviews to provide an objective view of employee performance and help proactively identify attrition risk and skills gaps.
Finance and Accounting
AI can assist financial and accounting teams with almost every aspect of their business operations. Accounts receivable and payable can be analyzed for ways to help the company collect payments more efficiently or manage payments to improve cashflow. AI analysis of financial reports can detect potential errors prior to outbound communication and also potentially identify opportunities to improve tax shelters, cashflow management, or other financial optimizations. On the compliance side, AI can help ensure tax and other regulatory compliance and in some cases even help prepare complex documents, such as R&D tax credit forms, based on employee assignments and timecards.
Customer Service & Support
Customer support is probably the single most talked about function for AI-based optimizations, and for good reason – it’s an obvious place to bring the power of automation and intelligence to bear on customer experience improvements. From intelligent ticket routing to AI-assisted human agents, to user sentiment analysis, AI agents can be applied to nearly every aspect of this function and the documents it works with.
Product Management
Product management is another document-centric function that offers numerous opportunities for AI agents to assist. Customer feedback and suggestions can be mined and aggregated faster than ever before, and then used to create or evaluate proposed product roadmaps or intersected with specific feature design documents. User flow analysis can be automatically scanned to identify sources of churn, frustration, or slowdown, which can then be turned into UI and UX improvements. A/B test cases can be automatically analyzed and correlated with both objective and subjective feedback to help provide faster and more accurate decision making.
Legal & Compliance
Legal teams can improve the efficiency of their document-centric processes with the help of AI agents. Contracts can be analyzed and reviewed by AI, providing legal teams with a heads up on critical areas to check and providing change detection and impact analysis. Due diligence and other required reporting documents can be monitored for compliance with regulatory frameworks and comparisons to prior versions. And news and government website updates can be monitored for potential business impacts.
IT
IT can leverage AI to assist with application log and website or server trace scanning, enabling it to efficiently detect security vulnerabilities, potential attack patterns, or unexpected operational behaviors. AI can also be used to scan existing resources to apply security, compliance, or infosec policies to both corporate and application-related documents and images. Ticketing, change requests, and other IT processes can employ AI-optimized routing, prioritization, diagnostic analysis, and for basic support questions can even provide direct customer solutions in some cases.
Summary
The use cases above are just a small subset of what’s possible when enterprise documents, forms, and other business assets can be seamlessly connected to AI agents through a managed MCP service like Vendia’s. We look forward to seeing the amazing things companies will achieve and hearing about even more ways in which AI can help help power business processes of all types. Get started using AI with your enterprise resources for free!