[ INDUSTRIES · Telecom ]

Telecom

Telecom operations are a fabric of tickets, orders, and alarms — high volume, high context, unforgiving SLAs. We put agents and models on churn, network operations, order management, and billing, with rep and engineer approval on the consequential moves.

Enterprise-gradeDeploys in your cloudYou own the IP
The landscape

Operators run millions of interactions across care, field, and network — each requiring context scattered across billing, CRM, provisioning, and network systems. Staff spend their time assembling that context under SLA pressure, and customers feel every minute of it.

AI's role is to do the assembly and the first-draft resolution: correlate alarms into incidents, gather the full account picture, diagnose stuck orders, and draft the next step — so reps and engineers start informed and act faster, with a human on anything that touches a customer or live infrastructure.

What's forcing the change

  • Churn and retention economics in a saturated market
  • Context scattered across billing, CRM, and network systems
  • Alarm storms and mean-time-to-resolve pressure in the NOC
  • Order fall-out and billing-dispute volume
Where we build

AI solutions for Telecom.

Churn & save desks

Agents predict at-risk accounts, assemble full context, and draft in-policy retention offers for rep approval.

Propensity MLRAGAgents
↑ save rate on priority accounts

Network-ops triage

Agents correlate alarms into incidents, enrich with topology and history, and draft resolution steps for NOC engineers.

CorrelationRAGGraph
↓ mean time to resolve

Order fall-out

Agents detect stuck orders, diagnose the failure point, and re-drive or escalate with full history attached.

AgentsMCPRules
fewer aged orders

Billing disputes

Intake, investigation, and adjustment drafting for billing complaints, with human sign-off on credits.

Doc AIAgentsAudit logging
faster resolution, less credit leakage

Care copilot

A grounded assistant gives care reps cited answers and the full account picture in one place.

RAGHybrid searchMCP
shorter handle times
On the platform

Agents and models share one platform — wired to billing, CRM, provisioning, and network systems through typed tool access, governed by evaluation and audit logging, and human-gated on customer- and network-facing actions.

Typical outcomes

  • Reps and engineers start every interaction informed
  • MTTR and handle times reduced
  • Save rates and order flow improved
Compliance & governance

Every system is architected to your regulatory surface, with controls and audit trails built in.

CPNIFCC requirementsData privacySLA-backed reliabilitySOC 2Audit logging
Evidence

Related success stories.

Telecom

The save desk that starts with context

min → sec
context assembly
↑ saves
on priority accounts
Read the story
Telecom

The NOC's new first responder

MTTR
↓ on common faults
alarms
correlated, not stacked
Read the story
FAQ

Questions from Telecom teams.

Can agents act on our network directly?
We keep humans on execution against live infrastructure. Agents correlate, diagnose, and draft the resolution; a NOC engineer approves and executes — you get the speed without unattended changes to the network.
How do agents get account context?
Through typed, least-privilege tool access to your billing, CRM, provisioning, and network systems, so the agent assembles the full picture the way a rep would — but in seconds.
Get started

Bring us a hypothesis. Leave with a system.

Tell us what's eating your team's time. We'll give you an honest read on whether AI is the right tool — and if it is, a scoped v1 with a timeline and cost.