5G, OSS/BSS replatforming, and AI-driven network operations for carriers.

5G standalone core and network-slicing work is the architecture-and-operating-model discipline of turning slicing from a marketing claim into a billable, operable service that the OSS/BSS can actually provision and bill against. The work begins with a current-state core architecture assessment, a slicing-use-case inventory aligned to the enterprise-vertical opportunities the carrier is pursuing, and an OSS/BSS-readiness review that determines what would have to change for slicing to be commercializable. A senior consultant produces a 5G SA core architecture decision record, a slicing-orchestration design aligned to the 3GPP and ETSI specifications and the carrier's existing service-orchestration footprint, an OSS/BSS-integration design that supports slice lifecycle management and slice-aware billing, and a measurement framework that ties slice performance to the Service Level Agreement (SLA) commitments the carrier can defensibly offer enterprise customers. Deliverables include the core architecture decision record, the slicing orchestration design, the OSS/BSS integration plan, and a commercialization-readiness assessment per priority slice use case. Successful outcomes look like a slice provisioned end-to-end inside the SLA, a billing-and-assurance pipeline that closes per slice, and an enterprise-customer launch the sales organization can sell against rather than around. An engagement typically runs twelve to eighteen weeks, embedded with the network-architecture organization, OSS/BSS engineering, the enterprise-product team, and the field-operations function.

OSS/BSS replatforming is the program-design discipline that determines whether a billing or order-management cutover is a controlled migration or a churn event. The work begins with a current-state OSS/BSS capability assessment, a TM Forum ODA and Open Application Programming Interface (API) alignment review, and a customer-segment migration assessment that identifies the populations where cutover risk concentrates. A senior consultant produces an ODA-aligned target architecture, a migration-strategy decision record (phased by segment, by region, or by product), a parallel-run reconciliation design with tolerance bands defined per product class, and a customer-impact-management plan that the field-operations and care organizations operate. Deliverables include the architecture decision record, the migration strategy, the parallel-run framework, and a cutover playbook reviewed by network operations, billing, customer care, and finance. Successful outcomes look like a cutover that closes inside the planned window with no customer-billing-disruption event, a parallel-run period that converges on plan, and a target-state OSS/BSS that supports new product introduction without bespoke development each time. An engagement typically runs sixteen to twenty-four weeks for the program-design and pre-cutover phases, embedded with the BSS-program leadership, network operations, customer care, and finance.

Customer-experience-management platform work is the integration discipline of building care, billing, and digital channels that produce a coherent customer experience rather than a set of channel-specific frustrations. The work begins with a current-state channel inventory, a customer-journey audit across self-service, assisted, and field, and a Customer Relationship Management (CRM)-and-care-platform capability assessment. A senior consultant produces a target-state architecture that integrates CRM, billing, and channel platforms with appropriate event-driven patterns, a digital-channel design that handles the failure modes (real issues, not happy paths), an integration design that lets the care agent see what the customer just experienced in self-service, and a measurement framework that ties customer-experience metrics to operating outcomes (NPS, churn, cost-to-serve). Deliverables include the architecture decision record, the integration design, the customer-journey playbook, and an operating-model framework for the care, digital, and field functions. Successful outcomes look like a self-service experience that handles real issues without producing repeat care contacts, a care-agent desktop that reflects the customer's last interaction, and a measurable NPS-and-churn improvement sustained beyond the project. An engagement typically runs ten to fourteen weeks, embedded with customer operations, the CRM and care platform teams, the digital channel team, and the BSS function.

Network-data-lake architecture is the data-platform discipline of ingesting telemetry at network scale, balancing retention against cost, and producing a foundation that operations, planning, and customer-care actually use. The work begins with a telemetry-source inventory across radio, transport, and core, a retention-and-cost analysis that surfaces the gap between what the network produces and what the business consumes, and a data-contract review across the consuming functions. A senior consultant produces a target-state architecture that distinguishes hot, warm, and cold telemetry tiers with the cost-and-latency tradeoffs documented, a data-contract framework between the network-operations source systems and the consuming analytics, an integration design that supports both batch analytics and stream-processing use cases, and a measurement framework that ties data-platform investment to consuming-function outcomes. Deliverables include the architecture decision record, the retention-and-cost framework, the data-contract catalog, and a roadmap that sequences data-product delivery against the consuming-function priorities. Successful outcomes look like a network-data-lake the operations team uses for real-time troubleshooting and the planning team uses for capacity decisions, a retention-and-cost posture that the CFO accepts, and a data-platform foundation that supports new use cases without bespoke pipeline work. An engagement typically runs ten to fourteen weeks, embedded with network operations, network engineering, the data-platform team, and the analytics functions.

AI-driven network-operations work is the modeling-and-operating-model discipline that turns model output into work the field-operations team will act on. The work begins with a use-case inventory across anomaly detection, capacity forecasting, and fault prediction, an honest cost-of-intervention model per use case, a current-state assessment of the data foundation feeding each model, and a workflow audit that surfaces how the model output would reach the operator. A senior consultant produces a use-case prioritization grounded in measurable cost of false-positive and false-negative outcomes, a model-architecture decision per use case, an integration design that puts the model output inside the operator's existing workflow tooling rather than a parallel dashboard, and a model-monitoring framework that distinguishes drift from real network change. Deliverables include the use-case decision records, the integration design, the operating-model that defines the operator-versus-model responsibility split, and a measurement framework tied to network KPIs the operations team already tracks. Successful outcomes look like an anomaly-detection model where the operator acceptance rate is high enough to justify the investment, a capacity-forecasting model the planning team trusts, and an AI-program scope that converges rather than expanding. An engagement typically runs ten to fourteen weeks, embedded with network operations, network engineering, the data-science function, and the OSS engineering team.

Carrier-grade cloud landing-zone work is the architecture-and-resilience discipline that meets the regulator-driven posture every multinational carrier is now navigating, particularly under the EU NIS2 Directive and the per-country implementing regulations. The work begins with a current-state cloud-footprint assessment, a regulatory-exposure inventory under NIS2, the EU Electronic Communications Code, and the relevant national security and lawful-interception frameworks, and a cloud-shared-responsibility audit. A senior consultant produces a landing-zone architecture aligned to NIS2 article 21 risk-management measures and the operational-resilience expectations the regulator imposes, a sovereign-cloud and data-residency strategy where required, an incident-response design aligned to the NIS2 reporting timelines, and a third-party risk posture for the cloud and Software as a Service (SaaS) dependencies on the carrier's critical path. Deliverables include the landing-zone decision record, the regulatory-mapping evidence catalog, the incident-response runbooks, and a third-party risk register aligned to NIS2 supply-chain expectations. Successful outcomes look like a NIS2 readiness assessment that closes without major findings, a cloud-platform footprint that supports new workloads without re-architecture for each new regulatory ask, and an incident-response posture that meets the NIS2 reporting timeline in actual rehearsal. An engagement typically runs ten to sixteen weeks, embedded with the security organization, the cloud-platform team, regulatory affairs, and the network-operations function.