How a 2,000-Person MedTech Company Cut AI Costs by 50% and Made RFPs 70% Faster

Note: The customer name and specific individuals have been anonymized for this case study.

The Situation

A mid-market medical technology SaaS company with roughly 2,000 employees had a problem that will sound familiar to most IT and transformation leaders: AI was happening whether they liked it or not.

Employees across the organization were using consumer AI tools to get work done faster. The IT team knew it was happening but couldn't quantify the scope or the risk. For a company handling sensitive healthcare data, this wasn't just an efficiency problem. It was a compliance liability waiting to happen.

"We weren't anti-AI," said the company's VP of IT. "We wanted our teams to have access to these tools. But we needed visibility and control. We couldn't have patient data or proprietary information flowing into tools we didn't manage."

The Copilot Experiment

Like many enterprises, the company bet on Microsoft Copilot as their sanctioned AI solution. The logic was straightforward: they were already a Microsoft shop, the security story was solid, and it seemed like the path of least resistance.

A year later, the results were underwhelming.

Adoption never took off. The interface didn't resonate with employees, and the tool didn't integrate very well (or, in some cases, at all) with the systems teams actually needed to do their jobs. Building custom agents or workflows required technical resources the company didn't have available, and Microsoft offered little support for implementation or training.

"We considered hiring a consultant to help us get more out of Copilot," said the Director of Digital Transformation. "But we were already spending a fortune on licenses that weren't being used. Throwing more money at training didn't feel like it would solve the fundamental adoption problem."

The team also explored reducing their seat count to get costs under control. But that created a different problem: if only certain employees had access to AI tools, how could they actually transform the company? Limiting seats meant limiting who could participate in the shift they were trying to make. It was a dead end.

The company found itself in a frustrating position: paying enterprise prices for a tool that only a handful of power users touched, while shadow AI continued to spread.

Finding elvex

When the team evaluated elvex, three things stood out immediately.

First, security that matched their requirements. As a healthcare technology company, HIPAA compliance wasn't optional. elvex's SOC 2 Type II and HIPAA certifications meant they could deploy to the entire organization without carving out exceptions for teams handling sensitive data. The team also liked that elvex supports hosting GPT, Claude, and Gemini on Azure Foundry, giving them an additional layer of control over where their data flows.

Second, integrations that actually worked. Unlike Copilot, elvex’s connection to the systems their teams relied on daily (Salesforce, OneDrive, Excel, PowerPoint, more) actually worked well. Agents could pull from real company data and deliver accurate, contextual responses.

Third, a path to value that didn't require a six-month implementation. The team was skeptical of another long rollout that might not pay off. elvex offered something different: start small, prove value, then scale.

The Rollout

The company took an intentional, iterative approach.

Weeks 1-2: Initial user groups in sales and marketing were onboarded with modest expectations. The focus was on straightforward use cases: writing and editing content in the company's voice, fact-checking against internal documentation, and answering product questions on demand.

"We wanted quick wins," said the Director of Digital Transformation. "If we could show value in two weeks, we'd have the credibility to expand."

Weeks 3-8: Access and training rolled out rapidly via SSO. Users were automatically aligned into groups for permissioning and governance. Each functional team received training tailored to their specific use cases and agents, rather than generic AI education. As users created agents tailored to their specific work, these agents were shared with everyone else in their specific group, reinforcing immediate utility (as opposed to generic AI tools like CoPilot that weren’t specific enough to work intuitively).

By week 8: The entire company was onboarded.

The contrast with Copilot was stark. Where the previous rollout had stalled at power users, elvex adoption spread organically because employees could immediately see how it applied to their actual work.

The Use Cases

The company now runs several high-impact workflows on elvex:

RFP Response: Sales and sales engineering teams use elvex to draft responses to RFPs, pulling from a knowledge base of past responses, product documentation, and competitive positioning. What used to require pulling in leadership for complex deals now happens within the team.

Vendor Security Evaluation: Given the nature of their business, evaluating vendor infosec policies is critical. The team built an agent that accelerates this review process, ensuring consistency and thoroughness.

Proposal and Handoff Documentation: Based on contract details, call transcripts, and deal notes, elvex generates proposals and customer success handoff documents. This eliminated hours of manual synthesis after every closed deal.

HR Policy Agent: Deployed directly in Microsoft Teams, this agent answers employee questions about internal policies, benefits, and procedures. What would have taken months to build internally (engineering a RAG pipeline, building a UI, integrating with Teams) was ready for testing in a couple of hours.

"The Teams integration made things instant," noted the VP of IT. "That's when I knew this was different. We weren't waiting on engineering resources or custom development. We were just... using it."

The Results

Six months in, the numbers tell a clear story:

• 50% cost reduction compared to their Copilot investment
• 70% faster RFP completion
• 120% increase in marketing content production

But the qualitative feedback has been just as meaningful.

"People are having fun with this," said the Director of Digital Transformation. "They're telling us they've finally been able to clear out projects that have been sitting on the backlog for months. They're doing more of the work they actually want to do."

The governance model has also delivered. With SSO-based group permissions, IT maintains visibility and control without becoming a bottleneck. Security and compliance signed off because the controls were built in from the start, not bolted on after the fact.

What's Next

The company continues to find new use cases weekly, often from unexpected corners of the organization.

"This is just the beginning," said the VP of IT. "We're six months in and teams I never expected are coming to us with ideas. That's the difference. With Copilot, we were pushing adoption. With elvex, people are pulling us forward."