2/3 of enterprise data is never used for decision-making. Your contact center is producing continuous streams of operational signal — in case notes, transcripts, tickets, knowledge articles, and recordings. LoreVault™ extracts it. Structures it. Makes it actionable.
Dashboards show aggregate metrics — silent on root cause. QA reviews samples — missing systemic drift. Search retrieves documents — without revealing patterns. None of them surface what's actually happening across your operation.
LoreVault™ ingests your unstructured service data — case notes, transcripts, recordings, knowledge articles, process docs — and extracts structured, evidence-backed operational signals. It does not replace your systems. It sits above them.
Files, transcripts, tickets, chats, emails, recordings — across any source system.
Auto-detect dataset type, structure, actor roles, and context. Standardize across sources.
Domain-scoped signal engines generate structured signals with traceable evidence. No black box.
Reveal systemic patterns and recurring themes. Every signal links directly to source evidence.
Data is not just indexed. It is interpreted within its operational domain, scrubbed for sensitive data, and converted into measurable signal.
Most recordings exist only as raw files — impossible to search, analyze, or extract insight from. LoreVault's™ processing engine converts audio and video into structured, speaker-attributed transcripts with precise timestamps.
LoreVault™ is a domain-aware interface grounded in your enterprise data. Not a generic chatbot. Every response is scoped, evidence-linked, and traceable to source.
Users ask execution and coaching questions. Output is behavior-specific and immediately actionable.
Users ask diagnostic and structural questions. Output maps patterns to root causes and initiatives.
QA and QM platforms (NICE CXone, Genesys, Verint, Calabrio, Five9) are optimized to analyze interactions inside the systems that generated them. LoreVault™ works on exported interaction datasets — across systems and time — treating your interaction history as an enterprise knowledge asset.
| Capability | QA / WEM Platforms | LoreVault™ |
|---|---|---|
| Agent performance scoring | ✓ Core function | Not the focus |
| Coaching workflows | ✓ Core function | Not the focus |
| Cross-platform interaction analysis | Requires custom data engineering | ✓ Built for this |
| Analyze full corpus — not samples | Sample-based by design | ✓ Full corpus |
| Systemic pattern detection across systems | Platform-bound analytics | ✓ Cross-system signal |
| Evidence-linked signal outputs | Black-box scoring | ✓ Every signal is traceable |
| Works on exported / historical data | Export is not primary workflow | ✓ Primary use case |
| Combine interactions with tickets, KB, workflows | Not designed for this | ✓ Knowledge Spaces |
Voice, chat, email, tickets, and knowledge records at scale — generating more signal than any team can manually review.
Multiple ticketing platforms, separate knowledge bases, case data that doesn't talk to your interaction data.
Repeat issues, engineering handoffs, aging backlog, and policy breakdowns that your dashboards don't explain.
Chatbots, copilots, and workflow automation being deployed before the underlying operational data is structured and trusted.
We're working with a small number of design partners to refine the product before broader release. If you're running a service operation with data you can't currently extract signal from, we'd like to talk.
Limited spots · Design partner pricing · No commitment required