Surplus
A capacity optimisation tool for mobile network teams that finds congested cells, finds nearby cells with safe spare capacity, explains every decision and lets engineers test a traffic move before touching the network.
- Capacity planning
- Congestion hotspots
- What-if simulation
- Explainable decisions
- Policy-driven
01
Overview
Surplus reads hourly cell KPIs and cell configuration from a telecom operator's radio network. It finds receiver cells under sustained congestion and donor cells with spare PRB headroom that can safely take more load. A donor must pass every safety gate: peak load, headroom, stability over time, no congested neighbour on the same band nearby, and enough backhaul capacity.
- Category
- Network capacity
- Industries
- Telecom
02 · Business value
What it changes for the business
Surplus
Surplus helps an operator use the capacity it already owns before it spends on new sites, while keeping customer experience safe.
- 01
Deferred capital spend
Finding latent capacity in existing cells helps defer site expansions where load can be shared instead.
- 02
Earlier congestion action
Sustained hotspots are flagged from KPI data, so teams can act before customers start to complain.
- 5 safety gates
Lower risk on every change
A donor must pass peak load, headroom, stability, neighbour and backhaul checks, which reduces the chance of moving congestion to another cell.
- 04
Decisions engineers can trust
Explainable results and what-if simulation shorten review cycles because engineers can see the reasoning and the likely outcome.
03 · The Problem → The Outcome
Challenges → Solutions
- 01
Challenges: Congested cells hurt customer experience, and teams often hear about them from complaints first.
Solutions: Sustained hotspots are detected from hourly PRB data and ranked by severity, with peak and off-peak views.
- 02
Challenges: Spare capacity already sits in the network, but nobody can see where it is safe to use.
Solutions: Donor cells and sites are found only when they pass every safety gate, and are scored high or medium confidence.
- 03
Challenges: Engineers distrust tools that recommend a change without showing the reasoning.
Solutions: Every result carries an explainability trace showing each gate, the measured value and the threshold.
- 04
Challenges: A traffic move can push a donor cell into congestion, and testing it live is risky.
Solutions: The what-if simulator estimates the donor and receiver state after the move, with an uncertainty band and historical evidence.
- 05
Challenges: Thresholds differ by band and hardware, and changing them usually needs a developer.
Solutions: A configurable capacity policy and user-defined radio segments let admins tune thresholds from the UI, with data-based suggestions.
04 · Use cases
Where it fits, by industry
Telecom
Purpose-built AI solutions for telecommunications providers.
- 01
Network Advisor: capacity planning
Planning teams find congestion early and see where spare capacity can carry the load, instead of defaulting to new sites.
- 02
Load balancing between cells
Radio engineers pair congested receiver cells with safe donor cells nearby and review the evidence for each pairing.
- 03
Pre-change what-if testing
Before steering traffic, engineers simulate the move to estimate donor load and user throughput after the change.
05
Enterprise Capabilities
Intended Users
Radio and capacity planning engineers at a telecom operator, with admins who manage the capacity policy and access roles.
Surplus
Network capacity
- 01Congestion hotspot detection and severity ranking
- 02Donor cell and site identification with safety gates
- 03Explainability trace for every decision
- 04What-if capacity simulator
- 05Configurable capacity policy and radio segments
- 06Regional map views, site drill-down and Excel export
06 · Highlights
Key Proof Point
Surplus
Surplus only proposes a donor that passes every safety gate, shows the evidence for each check, and lets engineers simulate the move before anyone changes the network.
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