Unifying incident operations at a Fortune 50 telecom
From a multitude of disconnected systems to one command center for visibility and faster resolution.
All visuals on this page are abstracted recreations drawn with fictional data. The client's actual interfaces, branding, and data are confidential.
Context
Network operations at national scale: thousands of incidents moving through monitoring, field operations, engineering, construction, and communications teams at once. Each team tracked its area of responsibility in its own tool, with spreadsheets and chat threads filling the gaps. No system held the whole incident.
Problem
Fragmented visibility made every question expensive. Triage was slow because assembling the current state of an incident meant checking several systems and asking around. Teams duplicated work they couldn't see each other doing. And the most common question — "what's the status?" — was answered by phone call, because no screen could answer it.
Approach
We designed a unified command center: one place where an incident is seen, worked, and resolved. Role-based views arrange a single shared record for each job to be done. An incident timeline holds the one ordered history of what happened. Cross-team workflows hand work off without losing context. Global search spans every entity in the system. And AI-generated summaries were treated as a designed trust surface to enhance efficiency — with visible confidence, fallbacks, and human takeover to mitigate risks.
Design decisions
1 · One incident record, many lenses
Every team had asked for "their own dashboard." To maintain a unified system, we built a single shared incident record, with role-based views that rearrange it for the job at hand. Operations sees the queue and severity; field crews see location and tasking; leadership sees impact and trend. Same facts, no reconciliation, no version drift.
Multiple systems, one record. Every event names the source it came from.
2 · The timeline is the source of truth
Events from every connected system land in one ordered incident history: detections, dispatches, escalations, notes, status changes. Conversations and status displays live in the timeline. When the history lives in one place, "what's the status?" becomes a screen instead of a phone call, and handoffs stop losing context.
Scattered event streams merged into a single ordered incident history.
3 · AI summaries as a designed trust surface
Long incidents accumulate hundreds of timeline events, so the console generates plain-language summaries. We designed the summary as a trust surface: confidence is displayed, every claim links back to its timeline sources, the fallback when the model is unavailable or uncertain is the raw timeline itself, the timeframe that the summary was derived from is displayed, and a human can take over the narrative in one action. The system earns trust by exposing its limits.
The summary's anatomy: confidence, sources, a fallback that degrades to the raw record, and a one-action human takeover.
4 · Search that spans every entity
One of the most recognized information architecture philosophies is enabling the user to find what they need, as quickly and easily as possible. Global search covers every entity in the system — incidents, locations, equipment, teams — from one keyboard-first field, with results grouped by type. No more confusion around which tool to ask; the global search answers for all of them.
One query, every entity type — grouped results.
5 · The failure state is designed for a person
Everything above still has to work in the worst hour, for someone who did not choose this moment to learn an interface. Therefore, the system features redundancies: when the AI summary is unavailable, the screen shows the raw timeline. Handing the situation to a human is one action, not a support ticket. Designed for the operator having a bad day; in insurance, that operator is standing between you and a policyholder having a worse one.
The fallback is the record itself: timeline still visible, one action to a human, no dead end.
Commercial outcomes
Without stating specific numbers covered by confidentiality agreements, this system saved millions in avoided customer service calls, faster resolution times, and enhanced employee efficiency. It also vastly increased customer satisfaction. While this project was for a different industry, what travels is the architecture: the decisions above shipped, and the section below is what they mean for insurance operations.
The transferable pattern
Strip away the industry and this is the architecture insurance operations run on: high volumes of time-sensitive cases, worked by multiple teams, under scrutiny, where the cost of a lost handoff is measured in customer trust. The same four decisions map directly.
One record, many lensesA claims workbench where adjusters, SIU, and supervisors work one claim file through role-based views without having to reconcile conflicting copies.
The timeline as source of truthClaim status a policyholder or agent can read instead of calling about, and an audit-ready history when a regulator or compliance review asks what happened and when.
AI as a trust surfaceAI triage and claim summaries with visible confidence, sources, and adjuster takeover. This makes the difference between automation your team trusts and automation they route around.
Search across every entityCAT dashboards and fraud-triage queues that surface the right case at the right moment, when volume spikes and prioritization is the whole game.
If your claims workbench, CAT operation, or triage queue still looks like the "before" picture, with many tools, no shared record, and statuses frequently answered by phone, that's one of many problems the audit will uncover and help remedy.