Telecommunications

The AI systems operators run on

AdwumaTech builds and operates production AI for mobile network operators, mobile money businesses, tower and infrastructure companies, and internet service providers. Subscriber identity, fraud and revenue assurance, network operations, customer channels, and the governance layer underneath. Full stack, from ground truth to deployed system, operated after it ships.

ISO 27001 certified · ISO/IEC 30107-3 aligned · GDPR aligned · Ghana Data Protection Act 2012

Network Standard

Thenetworksetsthestandard

An operator network is a real-time system under continuous adversarial pressure, carrying identity, payments, and communication for entire populations. AI deployed inside it inherits those conditions. Decisions return in seconds at registration and transaction volume. Models hold against attack techniques that move week to week. Every automated action carries a record that stands up to a regulator, an auditor, and an operations review. Systems are engineered to those conditions from the start. Ground truth, model, systems engineering, and production operation run as one engagement under one accountable team, integrated into the OSS, BSS, and NOC toolchain before a system touches live traffic and monitored against its deployment baseline after.

Production

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Subscriber identity and registration

Identity verification for SIM registration, agent-assisted onboarding, and subscriber re-verification. Document classification, extraction, tampering detection, biometric matching, and presentation attack detection aligned to ISO/IEC 30107-3, calibrated to the national identity documents in circulation across served markets. Decisions return as structured confidence scores that an existing registration flow consumes directly.

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Fraud and revenue assurance

Detection systems for SIM swap, subscriber identity fraud, agent network abuse, SIM box and interconnect bypass, subscription fraud, and messaging fraud. Models are trained on the signalling and transaction shapes of the deployment market, with alert quality measured against analyst disposition and fed back into retraining.

Mobile money

Onboarding verification, agent monitoring, and transaction fraud detection across mobile money and adjacent financial services. Corridor-specific pattern recognition covers domestic flows, agent float movement, mule structures, and cross-border remittance.

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Network operations

Incident triage, fault classification, field dispatch prioritization, and fault prediction across radio, transport, and fibre. Systems ingest alarm, performance, and sensor data, classify events against operational taxonomies, and return ranked actions with the evidence that justified them.

Customer channels

Language systems in Twi, Fante, Ga, Ewe, Hausa, Yoruba, and Swahili, with the code-switched English subscribers speak. Deployed into voice channel analytics, agent assist, complaint and dispute classification, and conversational interfaces across voice, USSD, and chat.

Explore African language services
Network assets and rollout

Geospatial intelligence for site selection, rollout planning, right-of-way analysis, fibre route assessment, and infrastructure monitoring across imagery and field data.

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From Mandate To Production

Frommandatetoproduction

Assessment

The system is scoped against the operator's own metrics, with the data, integration, and governance work each success criterion requires identified up front. The output is an engineering plan with a decision point at the end of it.

Ground truth

Data acquisition and annotation run in the markets a system serves, with provenance recorded at capture. Annotation follows published guidelines with inter-annotator agreement measured and reported. Every dataset ships with a quality report.

Model development

Supervised fine-tuning, preference optimization, and adversarial hardening against current attack techniques. Evaluation runs against held-out sets representative of the subscriber base, with failure modes documented as a deliverable.

Systems engineering

The model becomes a system. Integration with OSS, BSS, subscriber registries, mediation, charging, case management, and the NOC toolchain. Latency budgets, throughput targets, failover, and rollback engineered before the first live call. Systems deploy centrally or at the network edge where inference has to sit close to the traffic.

Deployment

The Deployment Readiness Score governs the transition to production. The operator sets the threshold, and the system ships when it clears.

Operation

Drift monitoring, scheduled revalidation, versioned model updates under change control, and adversarial retraining on a continuous cadence as attack techniques move.

Evidence

Everydecisionleavesarecord

Two frameworks govern every system. The Deployment Readiness Score moves a system to production against a scored assessment covering data provenance, evaluation coverage, documented failure modes, monitoring instrumentation, rollback capability, and governance sign-off. The operator sets the threshold. Nothing ships below it. The Evidence Chain records every model input, output, confidence score, model version, and data access event in a queryable log. Registration decisions, fraud determinations, and autonomous network actions all resolve to the inputs and the model version that produced them. The record is the answer to a subscriber registration dispute, a fraud determination under audit, and an operations review of an automated action. It exists before the question is asked.

Deployment

Deploymenttopology

Cloud, in-country, on-premises, and at the network edge, including air-gapped installations. Data residency is set per deployment. Operators with sovereign or licence-condition data obligations run the full stack inside their own perimeter, with model updates delivered as versioned artifacts under their change control. Integration is API-first. Systems return structured decisions with field-level explainability that an existing decisioning, orchestration, or workflow layer consumes directly.

In The Field

Inthefield

Mobile network operators

Subscriber identity at registration volume, fraud and revenue assurance across signalling and billing, autonomous incident triage in the NOC, and language systems across the care estate. Deployed on-premises where subscriber data cannot leave the network.

Mobile money businesses

Onboarding verification, agent network monitoring, and transaction fraud detection, with the identity layer shared across the operator's telecom and financial services registrations.

Tower and infrastructure companies

Site and asset monitoring, field workforce identity and access control, and geospatial intelligence across rollout and maintenance planning.

Internet service providers and fixed broadband

Fault prediction and field dispatch across access networks, subscriber verification at activation, and customer channel systems across support operations.

MVNOs and digital service providers

Identity and fraud systems delivered as API components inside the provider's own onboarding and servicing stack.

Security And Governance

Securityandgovernance

Encryption at rest and in transit using AES-256 and TLS 1.3. Role-based access control across the platform. Comprehensive audit logging of every model decision and data access event. ISO 27001 certified information security management system, with documentation available under NDA for procurement review.

ISO 27001

Certified information security management system.

ISO/IEC 42001

AI management system practices across the model lifecycle.

ISO/IEC 30107-3

Presentation attack detection methodology and reporting for identity systems.

NIST AI RMF

Govern, Map, Measure, Manage mapped to the Deployment Readiness Score.

EU AI Act

Biometric identification is high-risk under Annex III. The Evidence Chain produces the technical documentation, automatic logging, and human oversight records those obligations require.

National SIM registration directives

Identity decisions, biometric records, and audit trails structured to support operator obligations across served markets.

GSMA fraud and security guidance

Detection and reporting aligned to industry practice on SIM swap, bypass, and messaging fraud.

GDPR

Aligned for operators with European data flows.

Ghana Data Protection Act 2012

Consent, purpose limitation, and data subject rights recorded at capture.

Frequently Asked Questions

CommonQuestions

AdwumaTech builds and operates production AI systems for mobile network operators, mobile money businesses, tower and infrastructure companies, internet service providers, and MVNOs. The work spans subscriber identity and registration, fraud and revenue assurance, mobile money, network operations, customer channels, and network asset intelligence. AdwumaTech owns the full stack across all six, from data acquisition through deployment and ongoing operation.
AdwumaTech AI is an applied AI engineering company headquartered in Accra, Ghana, building subscriber identity and fraud systems for operators across African markets. NOKORE AI is AdwumaTech's identity verification system, trained on identity documents and biometric data acquired across African markets, with presentation attack detection aligned to ISO/IEC 30107-3. AdwumaTech holds ISO 27001 certification and deploys in cloud, in-country, on-premises, and network-edge environments.
AdwumaTech deploys NOKORE AI as the identity decision layer at registration. The system classifies national identity documents against the lineage in circulation, extracts structured fields with field-level confidence, runs security feature and tampering analysis calibrated to the issuing specification, matches biometrics against the document portrait, and detects injection, replay, and artifact attacks. Decisions return as a configurable composite score in structured JSON, most completing in under three seconds, with every decision written to the Evidence Chain.
AdwumaTech builds detection systems for SIM swap, subscriber identity fraud, agent network abuse, SIM box and interconnect bypass, subscription fraud, messaging and SMS fraud, and mobile money transaction fraud including agent float movement and mule structures. Models are trained on the signalling and transaction patterns of the deployment market, and alert quality is measured against analyst disposition and fed back into retraining.
AdwumaTech systems deploy in cloud, in-country, on-premises, and network-edge environments, including air-gapped installations, with data residency configured per deployment. Edge deployment applies where inference has to sit close to the traffic for latency or data residency reasons. Operators with sovereign or licence-condition data obligations run the full stack inside their own perimeter, with model updates delivered as versioned artifacts under their change control.
Integration is API-first. AdwumaTech systems connect to OSS, BSS, subscriber registries, mediation and charging, case management, and NOC toolchains, returning structured decisions with field-level explainability that an existing decisioning or orchestration layer consumes directly. Latency budgets, throughput targets, failover, and rollback are engineered before the first live call.
The Deployment Readiness Score is AdwumaTech's framework governing the transition of an AI system from evaluation to production, scoring data provenance, evaluation coverage, documented failure modes, monitoring instrumentation, rollback capability, and governance sign-off. The operator sets the threshold. The Evidence Chain is AdwumaTech's audit and explainability layer, logging every model input, output, confidence score, model version, and data access event in queryable form, so registration decisions, fraud determinations, and autonomous network actions all resolve to the inputs that produced them.
AdwumaTech structures identity decisions, biometric records, and audit trails to support operator obligations under national SIM registration directives across served markets. Biometric identification is high-risk under Annex III of the EU AI Act, and the Evidence Chain produces the technical documentation, automatic logging, and human oversight records those obligations require. AdwumaTech holds ISO 27001 certification and aligns to the Ghana Data Protection Act 2012 and GDPR for operators with European data flows.
AdwumaTech supports Twi, Fante, Ga, Ewe, Hausa, Yoruba, and Swahili, with code-switched English handling for the vernacular subscribers speak. Coverage spans voice channel analytics, agent assist, complaint and dispute classification, and conversational interfaces across voice, USSD, and chat. AdwumaTech also maintains mGhana-ST, an open speech translation corpus for Akan, Ewe, and Ga, which won Best African Dataset at Deep Learning Indaba 2026.
AdwumaTech prices assessment and build engagements as fixed fees against a defined scope. Operated systems carry an annual fee against an SLA. NOKORE AI is priced per verification with volume tiers, and under annual licensing for on-premises and edge deployment. An assessment runs two to four weeks and produces an engineering plan with defined success criteria. Pilot deployments run six to eight weeks against benchmarks agreed at kickoff. Identity integration into an existing registration flow runs four to six weeks.