Dana’s team just launched an internal AI assistant designed to help employees find answers faster.
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The execution was simple: connect a large language model to the company’s documentation so employees could ask questions and get instant guidance on products, policies, and customer issues.
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At first, it seemed to work, leading Dana (their Director of Enterprise Technology) hopeful. But once employees started using the system regularly, the problems surfaced.
Some answers referenced outdated documentation while others pulled information from internal wiki pages that had been abandoned years ago. In some cases, the assistant combined pieces of multiple documents that were never meant to go together.
The AI sounded confident, but answers were often wrong … and soon, employees lost faith. “Why are we not seeing ROI on this?” asked leadership.
Dana realized the issue wasn’t the model, but the knowledge feeding it: their documentation, policies, product information, and internal data had never been organized in a way that an AI system could reliably understand. They’d skipped RAG enablement and paid a heavy price.
Solve These Challenges
Knowledge Is Scattered,
And Nobody Knows What's Current
SharePoint, PDFs, emails, tickets, CRM, tribal knowledge - it's not consistent, not central, and not ready for AI.
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Employee Trust Is Gone.
Slow and inaccurate AI leads to internal escalations, frustration, and waning adoption that means little ROI.
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You Can't Tell If RAG Is Improving Or Not
There's no measurable baseline and regular reporting on this isn't uncovering insights
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Realize Gains Such As:
Measurable KPIs
Answer accuracy above 90%
P95 latency within target
Escalation rate reduced by 25% in 90 days
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Operational Wins
Correct answer retrieval above target accuracy that leads to reduced escalations and avoids repeat tickets
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Executive Wins
AI's actually used across sales, support, and more - with a clear reduction in cost to serve
Trusted By:
How We Help: RAG Enablement
We build reliable, governed RAG-enabled systems tuned to enterprise-grade accuracy with clearly-defined use cases. This includes:
Knowledge Inventory & Unification
Knowledge Schema & Semantic Structuring
Vector Strategy
Golden Set Development
RAG Pipeline Build-Out
Admin Configuration
We Work
Across Systems, Including:
“The experience of working with DoubleTrack has been amazing."
Hearsay Systems
Build RAG for critical workflows, not toy demos.
Most RAG implementations fail because they're built on unstructured knowledge that's outdated at best or wrong at worst.
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We start there, building the right system so AI retrieves accurate data quickly. The result? AI confidence skyrockets and it gets used.
Backed by a Success Guarantee.
SUCCESS STORIES
Customers like you are on the right track
Let's Talk
On Your Schedule
Schedule a time that works best for you, and we look forward to learning how we can help - and adding value right away.
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