Industrial
Your knowledge base isn’t the problem.
How it is searched or used, is.
How Eddyfi Technologies replaced Microsoft Copilot with a purpose-built agentic search solution on Forra, achieving 87.5% accuracy against a validated benchmark, versus 12% for Copilot.
The challenge
The answers exist. Finding them is the problem.
Eddyfi Technologies is a global leader in advanced non-destructive testing (NDT) inspection technologies, serving critical industries like aerospace, energy, mining, and transportation. Their teams work with highly specialized technical knowledge: product specifications, project documentation, planning data, engineering standards.
The problem wasn’t a lack of information. It was that the information was everywhere at once, spread across multiple systems, documents, and platforms, with no reliable way to surface the right answer quickly. Engineers and specialists were losing significant time just trying to find what they needed to do their jobs. The organization had already invested in Microsoft Copilot as a solution, but the results weren’t matching the expectations.
The solution
Not a generic assistant. A purpose-built search architecture.
Mirego built an agentic search solution on Forra, designed specifically around how the client’s teams actually look for information. Rather than a single general-purpose AI pointed at a pile of documents, the system uses specialized agents, each focused on a specific domain:
- A project planning agent that understands scheduling, resources, teams, and milestones
- A Jira agent that tracks who worked on what and for how long — bridging the gap between planned schedules and actual time spent
- A specification expert agent that handles technical documentation, product specs, and client specifications
When a user asks a question, the right agent is engaged for the right context. The result is answers that are grounded, traceable, and actually correct, not plausible-sounding guesses pulled from a broad language model with no understanding of the organization’s systems.
The outcomes
The benchmark doesn’t lie.
- Forra answered correctly 87.5% of the time on the client’s validated benchmark question set, against real answers defined by the client.
- Microsoft Copilot answered correctly 12% of the time on the exact same questions, under the same conditions.
- The gap isn’t marginal. It reflects a fundamental difference between a generic assistant and a purpose-built agentic architecture tuned to the actual systems and knowledge structures of the organization.
- Specialized agents for Jira, project planning, and technical and client specifications mean the right source is always consulted, not just the most statistically likely one.
- Teams spend less time searching and more time working, with answers they can trust and trace back to source.
- Built on Forra, the solution was validated and production-ready without the infrastructure overhead that a custom-built alternative would have required.
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