INDUSTRY ARCHITECTURE / Telecommunications

Telecommunications architecture

A connected reference design spanning domain information, data engineering, AI services, agent execution, and governance.

DOMAIN DESIGN DECISION

The business context
shapes the architecture.

One underlying network fault can create many alerts, and customer impact depends on the service dependency graph.

Normalize element identifiers, maintain service dependency versions, and distinguish observed alerts from diagnostic hypotheses.

Start with network incident triage rather than attempting to automate the whole industry at once. Define a bounded request, the evidence required to answer it, and the person accountable for accepting the result.

DATA → AI → AGENTIC AIDOMAIN CONTEXT: Network element / Alarm / Service dependency / Incident

Data architecture

01
Domain sources
Network alerts, service inventory, runbooks, incident tickets. Identify the system of record, owner, refresh rate, and approved purpose for each source.
02
Ingestion & contracts
Batch, change-data capture, events, and document intake as appropriate. Validate schema, identity keys, event time, and rejected records.
03
Storage & transformation
Separate raw evidence, validated records, and curated domain products. Preserve version history and reconciliation results.
04
Semantic serving
Network element · Alarm · Service dependency · Incident. Publish agreed definitions, access rules, and reusable interfaces for analytics and AI.

AI architecture

01
Approved information
Use curated domain products and approved documents. Preserve metadata, effective dates, and access scope.
02
Retrieval & features
Build permission-aware retrieval indexes or model features for the specific task. Test relevance and freshness independently.
03
Model & evaluation
Evaluate candidate methods on representative domain examples. Check groundedness, completeness, uncertainty, cost, and failure behavior.
04
Experience & feedback
Serve sourced drafts or scored signals through a review experience. Capture feedback without silently retraining or widening data access.

Agentic AI architecture

01
Task & identity
Record the initiating user, allowed purpose, task boundary, and completion criteria.
02
Reasoning & state
Network triage agent and Service assurance agent. Keep task state, retrieved evidence, and unresolved questions traceable.
03
Scoped enterprise tools
Expose typed, permission-checked search, lookup, and draft tools. Validate arguments and handle retry or timeout safely.
04
Approval & audit
Network configuration changes and service-impacting actions require an authorized operator. Record tool calls, reviewer decisions, and the accepted result under an agreed retention policy.

Shared governance & operationsOwnership · classification · lineage · access · quality · retention · evaluation · observability · incident response · cost management

Implementation decisions
to resolve before build.

Data lifecycle

Identify authoritative records, history requirements, update frequency, retention, and the consequences of stale information. Preserve source event time and ingestion time where ordering matters.

Serving & integration

Choose batch, event, API, or document access based on workload needs. Separate read-only retrieval from tools that alter enterprise records. Define timeouts, retries, and recovery ownership.

Operational evidence

Measure alert grouping usefulness, dependency resolution, runbook relevance, and escalation accuracy. Keep versioned evaluation cases, end-to-end traces, and reviewer feedback so changes can be assessed against an agreed baseline.

CASE

An evidence-led network incident triage workflow

See the proposed architecture applied to a focused workflow.

Network operations intelligence

Connect network events, service knowledge, and investigation tasks.