The signal your operation is already generating.
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.
Your tools show activity.
Not what's causing it.
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.
The gap is not tooling. It is the absence of systematic signal extraction.
Cases repeating without resolution — grouped with traceable evidence
Agents handling identical issues differently across queues and centers
Articles missing, outdated, or unreachable at the moment of resolution
Behavioral and language risk patterns going undetected across interactions
A signal intelligence layer.
Above your existing systems.
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.
01
Ingest
Files, transcripts, tickets, chats, emails, recordings — across any source system.
02
Normalize
Auto-detect dataset type, structure, actor roles, and context. Standardize across sources.
03
Extract
Domain-scoped signal engines generate structured signals with traceable evidence. No black box.
04
Surface
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.
Customer Interaction Operational Workflow Knowledge Integrity Risk & Compliance Revenue Intelligence Narrative Intelligence
Recordings become operational data.
Most recordings exist only as raw files — impossible to search, analyze, or extract insight from. LoreVault's™ media transcription engine converts audio and video into structured, speaker-attributed transcripts with precise timestamps that feed directly into the same signal framework as every other LoreVault™ data source.
This isn't a separate product — it's how LoreVault™ ingests media. Every call, meeting, and support interaction you've recorded becomes a first-class LoreVault™ data source: searchable, attributable, and ready for signal extraction.
- Fully local processing — no external APIs required
- Runs on-premise, GCP, or AWS — air-gap compatible
- Speaker diarization — each voice gets a persistent identifier
- Role inference — agent vs. customer without manual tagging
- JSON output — machine-ready for downstream systems
- Processes calls, support interactions, meetings, interviews, training recordings
[00:01:03] SPEAKER_00
Hello, thank you for calling. How can I help you today?
[00:01:07] SPEAKER_01
I need help with my account — I've called about this twice already.
[00:01:12] SPEAKER_00
Of course — let me pull that up for you right now.
Recordings sit as dark data
- Can't search across recordings for specific issue patterns
- Can't identify which agent handled which part of a call
- Can't feed interaction content into AI analysis workflows
- Can't correlate voice data with ticket resolution outcomes
Recordings become first-class signal sources
- Full-corpus search across every recorded interaction
- Speaker-attributed segments — agent vs. customer clearly separated
- Structured JSON output ready for signal extraction
- Connects directly to LoreVault™ analysis framework
A governed intelligence interface your team can query.
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.
"How should I handle objections about product XYZ to ensure first-contact resolution?"
"How do I avoid escalation when a customer has had a bad portal experience?"
- Behavior-specific guidance
- Clear do and don't recommendations
- Evidence-backed coaching patterns
Users ask diagnostic and structural questions. Output maps patterns to root causes and initiatives.
"How can we reduce digital friction across our customer experience?"
"What areas of our operation contribute most to backlog?"
- Pattern summaries with root cause drivers
- Initiative recommendations
- Measurable impact guidance
1
Domain-scoped responses
2
Visible evidence coverage
3
Traceable outputs
4
No black-box logic
Not a replacement.
A layer above.
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 |
You're a fit if your data exists
but your signal doesn't.
High-volume customer engagement
Voice, chat, email, tickets, and knowledge records at scale — generating more signal than any team can manually review.
Data across disparate systems
Multiple ticketing platforms, separate knowledge bases, case data that doesn't talk to your interaction data.
Escalations and rework that repeat
Repeat issues, engineering handoffs, aging backlog, and policy breakdowns that your dashboards don't explain.
AI initiatives without signal discipline
Chatbots, copilots, and workflow automation being deployed before the underlying operational data is structured and trusted.
VP Support / Technical Services
Head of CX / Customer Operations
AI / Automation Lead
- Hosted on Google Cloud Platform with strict tenant isolation
- Vault = tenant boundary — dedicated vector index per tenant
- Structured 30–60 day convertible POC
- Scoped to measurable operational outcomes
- Managed LLM included or bring your own
- API-accessible Knowledge Spaces — integrates with routing, dashboards, and automation workflows
Start with LoreVault™ today.
Self-serve subscriptions are live. Pick the tier that fits your operation — or talk to us about Enterprise terms if you need SSO/SCIM, custom SLAs, or scale beyond 500 seats.
Start with a 30-minute conversation.
We'll tell you which engagement fits your situation — and if the answer is none of them right now, we'll tell you that too. No pitch. No pressure.