The CloudSoda AI Assistant: What We Learned Building Our First AI-Powered Solution
In his latest Medium post, our VP of Product, Olivier Rivard, shares the behind-the-scenes story of how we built the CloudSoda AI Data Assistant—our first AI-powered solution.
From MCP to Prototype
The idea grew from Olivier’s experiments with Anthropic’s Model Context Protocol (MCP), which allows AI assistants to connect directly to real-world systems. If MCP could make his own workflows more powerful, why not bring the same approach to customers? That question set the stage for building an assistant that could make unstructured data instantly actionable.
The NAB Show in Las Vegas became the forcing function: a deadline to design, build, and demo a working prototype in front of thousands of industry professionals.
Strategic Choices
A core decision was which AI models to support. Customers generally fell into two camps:
- Security-focused organizations restricted to tools like Microsoft Copilot that keep data contained.
- Enterprise-standardized organizations built around a single LLM like ChatGPT.
By supporting both, and by leveraging MCP, the assistant could meet customers where they were while maintaining flexibility. To ensure accuracy, we also exposed a structured set of functions through our APIs, preventing AI “hallucinations” and ensuring trustworthy results.
What We Enabled
The initial release gave the assistant reliable capabilities, including:
- Analyzing storage usage, capacity, and costs
- Simulating cost savings for different storage scenarios
- Identifying duplicate files and their impact
- Auditing file age and access history
- Listing connected storage systems for planning
Why It Stood Out
At NAB, the AI Assistant didn’t just capture engineers’ attention—it drew in executives. Leaders saw they could finally ask questions in plain language (“How much cold data do we have in PowerScale?”) and get instant, actionable answers, without waiting on reports or pulling in staff.
Why It Stood Out
The NAB prototype was just the first step. In his next post, Olivier will share how we took the concept further—using AI itself to help design, implement, and review a new connector for the Diskover platform.
Read Olivier’s full blog on Medium.