The Platform

Built for a world where AI acts, not just advises. AI that acts. Not just advises.

AURA is DvSum's Control Plane for Agentic AI — the intelligence layer that turns every network signal into a closed-loop decision. ANI is the first solution that runs on it. Broadband operators experience ANI. AURA is what makes it possible.

Scroll to explore the architecture
Sovereign
Data stays in your network
Patented edge architecture · no data movement
Domain
DOCSIS-native intelligence
Built from production HFC · not adapted from generic ML
41.7%
Call containment rate
LLA · Genesys Engage · network tech support
50%
NTF truck roll reduction
NTF dispatches only · LLA deployment

How It Works

Sense. Reason. Act. Learn.

Signals in. Decisions out. Humans in control. The loop doesn't stop.

Sense

Every signal. In place.

Network telemetry, modem & CPE data, OSS/NMS, BSS/CRM, contact center — all flowing into one stream. Nothing moved. Nothing copied.

Reason

Graph intelligence. Domain expertise.

Correlate signals, identify root cause, decide the action with confidence. DOCSIS domain knowledge built in — not a generic ML model.

Act

Closed loop. Human in control.

Automated where confidence is high. Recommendation surfaced for human approval where it matters. The automation boundary is yours to define.

Learn

Every action feeds the next decision.

Analyst feedback, post-repair telemetry, outcome signals — continuously sharpening the model. Month three is more accurate than month one.

"Every signal closes a loop. Every loop sharpens the next decision."

The Architecture

Three layers. One platform.

Everything your network needs to go from signal to action — without moving your data.

01 Data Sovereign Edge

Your data stays in your network. A lightweight gateway deploys inside your perimeter. Raw telemetry, subscriber records, topology — processed at the edge. Nothing moves to the cloud. Sovereign by design. Patented.

Edge Gateway Unified Knowledge Graph OSS/BSS Connectors NXT / Aurora Integration
02 Intelligence Core Reasoning

The reasoning engine. DOCSIS domain knowledge, topology graph, three-pillar RCA, confidence scoring, operator-configurable rules. Not a generic LLM. A domain-trained intelligence layer that understands what upstream SNR degradation means — and what to do about it.

Knowledge Graph Domain Reasoning Engine AI Models RCA Cards Confidence Scoring
03 Consumption Action Layer

Where decisions land. NOC workqueue, contact center co-pilot card, automated CMTS config push, ticketing system. DvSum's pre-built solutions (ANI) or your own stack via MCP/APIs. The action layer completes the loop.

NOC Dashboard CC Agent Co-Pilot Ticketing Integration CMTS / Network Element MCP APIs

Data Sovereignty · Patented Architecture

Your data never leaves your network.

Data stays in your network

Raw telemetry, subscriber records, network topology — all processed at the edge inside your perimeter. Nothing moves to the cloud. Sovereign by design. Patented architecture. Not a policy statement — an architectural guarantee.

Unified Knowledge Graph

A single connected graph across every asset — subscribers, nodes, CMTS, OLT, ONT — built and maintained inside your network. Full-stack context, in place. The graph is what makes cross-layer reasoning possible without moving data.

AI acts at the edge

At runtime, LLM instructions flow to the Edge Gateway and execute directly against local data. Results return to the cloud. Your data never moves. The AI comes to the data — not the other way around.

"Patented. Sovereign by design. The only AI control plane that doesn't require you to move your data."

AI Maturity

From answers to action.

AI has four levels. Most tools stop at one.

01

Answer

You ask. You decide.

Co-Pilot Mode

"Which nodes have upstream SNR degradation?"

02

Assist

You review. You confirm.

Co-Pilot + Workflow

"Top 5 at-risk nodes — pre-filled dispatch recommendation ready."

03

Automate

You approve. AI acts.

Human-Gated Action

"Dispatch ticket created, held for NOC sign-off."

04

Autonomous

AI acts. You are informed.

Closed-Loop Agentic

"CMTS config adjusted. NOC alerted with full RCA summary."

DvSum is the only platform built for telecom that operates across all four levels. You define which level your team is ready for — and the boundary moves as your confidence grows.

What's Live. What's Next.

Six capabilities. Three live today.

One platform. Operational AI maturing across the network and the subscriber.

Network Subscriber
Reactive
Live

HFC Alarm Prioritization

P0/P1/P2 ranked by subscriber impact. RCA with reasoning. Pre-loaded work order.

Live

Contact Center Triage

5-domain check at call open. Plant vs. in-home isolation before the agent says a word.

Proactive
Live

Silent Failure Detection

Sub-threshold nodes caught before failure. Fragility index. Chronic dispatch pattern surfaced.

Coming Soon

Subscriber Experience Monitoring

QoE degradation detected before the subscriber calls. Proactive outreach. Churn-risk scoring.

Preventive
Coming Soon

Network Health Intelligence

Congestion root cause typed. Provisioning mismatch caught before impact. Equipment aging ranked.

Coming Soon

Always-On Subscriber Assurance

Continuous QoE baseline. SLA exposure surfaced before breach. Capacity prioritized by revenue at risk.

Platform Foundation

Your existing systems stay in place.

DvSum reads from both OSS and BSS, reasons across both, writes back to the right system.

What Makes This Possible

The Control Plane underneath.

ANI is what operators experience. AURA is what makes it possible — and what makes any agentic AI operational. Four components: Metadata & Ontology, Domain Skills, Data Collection Endpoints, and Closed Loop APIs. Assembled per query. Scoped. Grounded. The reason DvSum doesn't hallucinate in an HFC plant while generic AI tools do.

Explore AURA →

For AWS SAs, SI architects, and technical evaluators who want the full architecture story.

Independently Validated

The architecture wasn't designed. It was forced — then confirmed.

AWS published the Semantic MCP Server pattern — deploy models at the edge, keep sensitive data on-prem, send only structured metadata to the cloud. CableLabs published the AI-Native Networks framework — distributed intelligence that senses, reasons, and acts in real time across edge, access, and centralized domains. DvSum was already running both in production at LLA before either paper was written.

Production, Not Pilot

LLA — 1.2M+ subscribers

Live operational deployment. 8+ integrated source systems. Sovereign data requirements met. 41.7% call containment. 50% NTF-specific truck roll reduction. Live metrics, not benchmarks.

Telco-Native, Not Adapted

DOCSIS knowledge built in

Built from production HFC deployments — not adapted from generic ML. The system knows what upstream SNR degradation means and what ingress noise looks like at 2am vs. 6pm. Earned, not licensed.

Sovereign by Architecture

Patented edge gateway

Data never leaves the operator's perimeter. Not a compliance policy — a patented architecture. The edge gateway processes everything locally. Results return to the cloud. The data never moves.

Domain Is the Moat

What hyperscalers don't replicate

Hyperscalers build the runtime. They don't build the domain. AWS doesn't know that upstream SNR degradation means something different than downstream in an HFC plant. Domain specificity is what they partner for.

Common Questions

What technical evaluators ask.

No. Raw telemetry, subscriber records, and network topology are all processed at the edge inside your perimeter. A lightweight gateway deploys inside your network. Results return to the cloud — the data never moves. This is a patented architecture, not a policy statement.
Purpose-built. DOCSIS domain knowledge — including what upstream SNR degradation means versus downstream, what ingress noise looks like at 2am versus 6pm, and what T3/T4 timeout patterns indicate — was built from production HFC deployments, not licensed or adapted from a generic ML library. That domain specificity is the moat.
DvSum is read-only on NXT. It reasons over NXT's normalized schema natively — NXT handles the collection abstraction across CMTS, R-PHY, and PON. DvSum's job starts above that layer. No rip-and-replace. Your existing systems stay in place.
Full control. DvSum operates across four AI maturity levels — from co-pilot answers to fully autonomous closed-loop action. You define which level your team is ready for. The automation boundary is yours to set, and it moves as your confidence grows. Nothing acts autonomously by default.
In production. Liberty Latin America — a 1.2M+ subscriber HFC network across 20 countries with 8+ integrated source systems — is a live operational deployment. Results include 41.7% call containment, 50% NTF truck roll reduction, and 88% RCA accuracy by week 6. These are live operational metrics, not pilot benchmarks.

Ready to see the platform in your environment?

We'll show you a live data audit on your NXT telemetry — no operations impact, no workflow change. You see your actual node prioritization, RCA patterns, and silent failure risk. It either confirms you have a gap or proves you don't.