A multinational finance company has taken a bold step in the world of enterprise AI, rolling out a secure artificial intelligence agent developed with CloudX to 250 staff members. The move reflects a growing demand for productivity gains from AI while addressing one of the sector’s biggest challenges protecting sensitive data.
The rollout comes against the backdrop of an MIT study, which found that 95% of enterprise AI pilots never make it to deployment, largely due to concerns around security and compliance. Of the small percentage that do succeed, two-thirds achieve results by partnering with AI specialists to tailor solutions for real-world business problems.
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In this case, the finance firm partnered with CloudX to create a system that would let employees tap into large language models (LLMs) without putting confidential company information at risk. CloudX’s solution works by connecting users to models from leading providers including Anthropic, OpenAI, Meta, and DeepSeek while first auditing prompts and responses to ensure strict compliance with company guardrails.
“Establishing robust guardrails is essential for managing AI-human interactions and safeguarding organizational integrity,” explained CloudX CTO Pablo Romeo. These guardrails include rules to ensure sensitive data is never used to train external models, answer validation protocols, response length limitations, and fallback logic when model confidence is low. “These measures help maintain control over the AI’s outputs and reduce the risk of unintended consequences,” Romeo added.
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CloudX has also emphasized that for AI agents to move from pilot stage to production, they need to be fine-tuned for specific business tasks. By grounding the technology in company data, the agents consistently deliver higher levels of accuracy and reliability. At the same finance firm, another agent designed for invoice reconciliation recently cut processing time by nearly one-third in a system that involved multiple platforms and a high transaction volume.
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The collaboration between the finance company and CloudX has been ongoing for more than three years, and both sides describe it as a model for balancing innovation with security. As enterprise adoption of AI accelerates, their work demonstrates how carefully designed systems can deliver real productivity benefits while still protecting the integrity of business data.
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