Sector served

Orchestrating AI in telecoms: network, billing and customer relationship connected, the right service at the right moment

Break the silos between OSS, BSS, CRM, billing, customer care and shop. Deliver the right action at the right time, without surveilling the customer. An AI orchestration layer designed for mobile and fixed operators, MVNOs and B2B operators, with native ARCEP, GDPR, communication secrecy and AI Act compliance.

Served profiles

Three profiles served by telecom operators

A telecom operator does not serve a single client but three families with radically different expectations. The AI orchestration layer must treat each with its own logic, without applying the B2C grid to B2B clients nor the B2B grid to industrial IoT.

B2C — consumer subscriber

Expectations

Clear plan, fair price, no bad surprise on the bill, available support when an issue arises, adjustable options without hidden re-engagement.

Pains

Commercial push at the wrong moment, support that doesn't know how to answer, disconnection on the move, incomprehensible bills, feeling of being a number.

AI levers

Automatic technical diagnosis before transfer, plan recommendation by real usage, preventive anti-churn on weak signals, advisor copilot for quick answers.

B2B — enterprise and government

Expectations

Guaranteed SLA, single technical contact, consolidated multi-site billing, integration to client IS, proven security, fast escalation on critical incident.

Pains

SLA not held, multiple contacts, billing scattered by site, fragile integrations, support not understanding business stake, slow escalation.

AI levers

Real-time SLA dashboard, predictive escalation on degradation, network engineer copilot, automatic client reporting generation, pro SIM swap fraud.

Industrial IoT — connected fleet

Expectations

Massive and cheap connectivity, low energy consumption, long-term reliability, centralized monitoring, alert management prioritized by criticality, APIs for business integration.

Pains

Cost spiraling on volume, inflationist non-prioritized alerts, lacking monitoring, silent data loss, support chain unsuited to criticality.

AI levers

Anomaly detection on sensor signals, alert prioritization by business criticality, IoT plan optimization by usage, object failure prediction before breakdown.

Observation

The observation: kilometres of fibre, millions of customers, but no shared memory

Telecom operators have deployed gigantic infrastructure. Antennas, fibre, core network, OSS, BSS, CRM, billing, self-care app, physical shops. Each system, in isolation, works. Network indicators come up, bills are calculated, promotions are sent.

But these systems operate in silos. The customer pays the price: a connection problem solved after four escalations because L1 support cannot see OSS indicators, an unexplained bill without usage context, an upsell offer sent the day after an unresolved complaint, a data promotion when they just had a network outage all evening. Each silo is right, the overall experience is broken.

The challenge is no longer to build a new CRM or new network diagnostic. It is to make existing systems talk to each other intelligently, in real time, with a layer that understands the customer's context and triggers the right action — without tracking them, by serving them better.

The problem in detail

The problem in detail: eight systems, none of them knows you lost the network last night

System

Core network and OSS

Knows

Signal quality, local outages, network performance, saturated antennas

System

BSS and billing

Knows

Subscription, options, billing, payment history, delays

System

Telecom CRM

Knows

Customer interactions, shop appointments, segments, sent solicitations

System

Customer care (tickets)

Knows

Ongoing complaints, escalations, reason, commitments made

System

Self-care app

Knows

Real-time consumption, activated options, help searches

System

Physical shop

Knows

Visits, purchases, advice given, demos performed

System

Marketing automation

Knows

Sent campaigns, segmentations, targeting

System

Social networks and NPS

Knows

Brand mentions, public feedback, sentiment

None of these systems sees the whole picture. The customer pays the price: a data upsell is proposed when they just suffered a network outage; they call support for a signal problem and must give again their line number, address, box; an NPS survey is sent two hours after an unresolved complaint; they visit the shop to change plans and the salesperson does not see they called three times this week. Each silo is right, the customer becomes a detractor.

The Access solution

Access AI orchestration layer for telecoms

A software layer that integrates on top of existing systems. It continuously analyzes the customer log (consumption, interactions, network signals, transactions, NPS), scores context and triggers dynamic workflows. Here are nine concrete use cases we deliver for mobile and fixed operators.

Workflow 01

Technical diagnosis that resolves in first line, not in fourth escalation

A customer calls support: their box has not worked since this morning. Before, the L1 agent asked ten questions, checked four systems, escalated to L2, who escalated to L3 if needed. Today, from the call, orchestration cross-references OSS (local outage identified 800m from their home), BSS (bill up to date, line active), ticket history (no prior), self-care (customer rebooted box twice). The agent immediately sees the diagnosis: local outage, intervention scheduled at 2 pm. They announce it, offer automatic flat-rate compensation, hang up in two minutes. The customer leaves reassured, not frustrated.

Technology

Real-time OSS / BSS / tickets / self-care cross-reference, diagnostic complexity scoring, resolution scenario suggestion, agent tool integration.

Customer impact

The customer hangs up in two minutes instead of twenty-five. They did not have to repeat their problem four times. They know when their connection will be restored. Sense of efficiency, not ordeal.

Business impact

Post-incident NPS rises. Customers in outage do not become detractors. Retention on incident-affected accounts measurably improves. Reduction in compensations negotiated under escalation.

Operations impact

L1 resolution rate rises strongly. Escalations to L2 and L3 drop. Per-agent processing capacity increases, with constant team. Support job mental load reduced.

Workflow 02

Subscription onboarding that says yes or no in minutes

A prospect signs up online for a mobile plan or internet box. They upload ID, bank account details, proof of address. Before, human queue for 24 to 72 hours to validate. Today, orchestration analyzes documents (OCR + consistency), validates KYC identity, checks network eligibility (fibre coverage at the address), scores creditworthiness. Response in minutes: line activated and SIM card shipped, or additional request with precise list, or motivated refusal. No more grey zone.

Technology

Advanced OCR, KYC identity verification, fibre address registry integration, creditworthiness scoring, HITL for borderline cases, auditable logging.

Customer impact

The customer perceives a responsive, clear operator. No opaque waiting. If refused, they know why and what they can do. Almost-instant conversion of intent to subscription.

Business impact

Digital path abandonment rate drops sharply. Each abandoned path is a lost customer, often to an MVNO or competitor. Direct recovery in revenue.

Operations impact

The activation department processes five to ten times more cases with the same team. Agents focus on real risk cases, not on triaging incoming flow.

Workflow 03

Predictive anti-churn that acts before cancellation

The analysis engine spots a bundle of signals: drop in data consumption, searches on the competitor site from the operator's wifi, unresolved complaint, recent commitment declaration. Rather than discovering cancellation three months later in figures, the operator detects it three weeks early. Workflow triggered: personalized call with full context, negotiated commercial gesture if justified, or simply attentive listening. Many cancellations are calls for help that were not heard.

Technology

Churn prediction model, multi-signal behavioral analysis, criticality scoring, retention path orchestration, HITL for commercial gestures.

Customer impact

The customer who stays feels truly heard. Not a routine end-of-month call, a call because we understood there was a problem. Recognition and trust restored.

Business impact

Churn rate drops measurably. For a telecom operator, keeping a customer costs three to five times less than acquiring a new one. Direct savings on CAC.

Operations impact

Sales and support teams learn to read signals. Beyond the workflow, a culture transforms: we no longer wait for the loss, we act. Systemic churn causes are identified.

Workflow 04

Plan personalization based on real usage, not on a static segment

A customer regularly exceeds their data plan for three months. They pay 4 to 8 euros out-of-plan per month. Orchestration detects the pattern and triggers: message in the self-care app proposing a higher plan that saves over six months, with personalized calculation visible. The customer accepts or refuses in two clicks. Conversely, a customer consuming far below their plan receives a proposal for a lower plan, no pressure. The bank would do the opposite — the honest telecom operator gains in trust and loyalty.

Technology

Real-time consumption analysis, baseline plan comparison, optimization opportunity scoring, multi-channel orchestration, HITL for atypical cases.

Customer impact

The customer sees the operator offering them the right plan, even if cheaper. Sense of commercial honesty rare in the sector. Trust and loyalty strengthened.

Business impact

Optimized ARPU: the customer pays the right plan, not a too-small with overage nor a too-large unused. Reduction of churn to low-cost MVNOs. Telecom NPS score lastingly improved.

Operations impact

Billing dispute management drops. Self-care teams handle fewer overage complaints. Shop salespeople freed for complex advice.

Workflow 05

Shop and call-center advisor equipped with a senior copilot

A customer enters a shop to change plans. Before, the salesperson searched in several tools: CRM, BSS, product portal, pricing simulator. Today, they query the AI copilot in natural language: customer profile (consumption, options, history), eligible plans, personalized comparison, compliance scripts. The salesperson responds in two minutes instead of ten. The customer leaves with the right plan. Same in the call-center: the agent immediately sees the full context and recommendation.

Technology

RAG on product catalog + procedures + compliance scripts, multi-system customer context aggregation, real-time copilot interface, multi-language.

Customer impact

The customer perceives an operator that knows them, not a counter that changes faces. Personalized advice, not generic script. Decision made with confidence.

Business impact

Conversion rate in shop and call-center rises. Upsell basket share grows because the salesperson has the right argument at the right time. Post-interaction NPS improves.

Operations impact

New salesperson onboarding goes from several weeks to a few days. Senior salesperson departure is no longer catastrophic. Constant service capacity despite sector turnover.

Workflow 06

AI editorial qualification with human validation — already delivered for a national operator

A national telecom operator produces massive editorial content: news, product articles, marketing posts, customer documentation. Each content must be semantically qualified (theme, tone, legal compliance, brand alignment) before publication. The volume makes human-only untenable, AI-only risky. The orchestration layer combines both: tagger rules, NLP models, continuous brand lexicon learning, human validation on uncertain cases via the HITL framework. Production maintained at scale, quality validated by editorial teams.

Technology

NLP, tagger rules, continuous learning models, RAG on editorial guidelines and compliance, HITL framework, auditable logging.

Customer impact

The reader receives relevant content, consistent with the brand, legally compliant. No contradictions or gaffes. Trust in the brand voice strengthened.

Business impact

Capacity to produce content at scale without quality drift. Editorial differentiation in a saturated sector. Systematic regulatory compliance (advertising, mandatory mentions).

Operations impact

The editorial team handles five to ten times more content with the same load. Writers focus on creation, not qualification. Proofreaders validate only uncertain cases.

Workflow 07

Mobile antenna deployment optimization through data analysis — already delivered

A telecom operator deploys or densifies its mobile antenna network. Before, location choices rest on theoretical coverage models. Today, data analysis aggregates real consumption per cell, observed saturation zones, geolocated user complaints, customer movements, competitor deployments. It proposes prioritized recommendations: where to densify, where to decongest, where to plan a new location. Network investment optimized by real usage, not assumptions.

Technology

Multi-source data analysis (consumption, complaints, geolocation), saturation prediction models, network planning tools integration, decision dashboards.

Customer impact

Coverage improves where the customer needs it, not on a theoretical map. Fewer weak signal zones, less saturation at peak hours. Perceived service quality rises.

Business impact

Network CAPEX investment optimized: priority on the right locations. Coverage complaints reduced. Network quality differentiation versus competitors deploying blindly.

Operations impact

Network engineering teams make decisions backed by data, not intuition. Budget arbitrations are faster and fairer. Reduction in deployment rework.

Workflow 08

Automated competitive intelligence for marketing — already delivered (EMEA telecom)

An EMEA telecom operator wants to continuously understand what competitors are doing: new plans, marketing campaigns, social communication, public customer feedback. Before, manual monthly intelligence, partial, quickly obsolete. Today, the data analysis platform extracts daily LinkedIn, Facebook, Instagram, X publications from competitors, normalizes, analyzes trends, identifies strategic pivots. Automatic reports to the marketing committee. Multiplied commercial responsiveness.

Technology

Social APIs and public source extraction, normalization and cleaning, sentiment analysis, Power BI dashboards or data warehouse export, platform and GDPR compliance.

Customer impact

Indirect: the operator reacts faster to market pivots, offers better-positioned offers, does not let competitors carve out a lasting advantage.

Business impact

The marketing department continuously arbitrates its strategy on fresh data. Counter-offers are published in days, not weeks. Market share preserved.

Operations impact

The marketing intelligence team frees itself from repetitive manual work. They focus on strategic interpretation, not collection. Analysis capacity multiplied with constant team.

Workflow 09

SIM swap fraud and abuse detection before they harm the customer

A customer requests a SIM card change (legitimate: loss, theft, upgrade). Orchestration cross-references signals: request geolocation, customer's usual behavior, recent patterns (app searches, calls to a new number), known SIM swap attack history. If suspicious signals (request from another country, absence of consistent history, pattern close to known attacks), investigation workflow: additional validation request to the customer via secure channel, fraud alert, human escalation. Fraud is stopped before the customer is robbed via SIM swap.

Technology

Real-time anomaly detection, multi-system cross-reference (CRM, app, geolocation), HITL framework for critical cases, anti-fraud unit integration.

Customer impact

The customer is protected against impersonation. Their trust in the telecom operator is strengthened. No traumatic experience of discovering an emptied account via suffered SIM swap.

Business impact

Reduction in fraud indemnifications. Reduction in post-serious-incident departures. Reputation preserved on a topic that can severely harm the brand.

Operations impact

The anti-fraud team handles only suspected cases, not the entire flow. Agents focus on complex investigations. Continuous learning: each thwarted attack feeds the model.

Progressive ladder

Anti-churn ladder — five levels of progressive engagement

A client who leaves does not decide overnight. There is a detectable trajectory from weak signals to explicit signal. The orchestration layer detects each step and triggers the adapted action — not more, not less. Over-reacting early scares the client away. Under-reacting late loses them definitively.

Level 1 — Very weak signal
Observed signal

Modest decrease in data or voice usage versus client average, no other alert. 6-month churn probability < 10%.

Triggered action

No invasive action. Silent monitoring, contextualization of future signals. No solicitation, no pushed offer.

Level 2 — Confirmed weak signal
Observed signal

Multiple coherent decreases over 30 days, no complaint yet. 6-month churn probability 10-25%.

Triggered action

Automatic technical service quality check. If all OK, nothing. If degradation detected, proactive intervention without direct contact.

Level 3 — Medium signal
Observed signal

Recently handled complaint + usage decrease + reduced self-care app activity. 6-month churn probability 25-50%.

Triggered action

Contextualized email: recognition of the situation, recent experience verification, opening of a direct channel without commercial pressure.

Level 4 — Strong signal
Observed signal

Active competitive search detected (network, app), portability request simulated, support contact on pricing. 6-month churn probability 50-75%.

Triggered action

Call from a dedicated retention advisor with complete brief: history, probable reasons, leeway, adapted proposals (not a generic promo).

Level 5 — Explicit signal
Observed signal

Formal portability or termination request. Confirmed departure probability. Retention delay counted in days.

Triggered action

Senior loyalty advisor with pricing autonomy, contextualized retention proposal, honest opening on departure if not convincing. Preserve possibility of later return.

Customer experience doctrine

Operating principle: felt service, not perceived surveillance

All these workflows share one goal: increase service offered for customer comfort. A telecom subscriber who feels tracked — solicited at the wrong moment, sold while having an unresolved problem, followed without being served — becomes dissatisfied. A subscriber who feels served — fast diagnosis, competent advisor, offer adapted to real usage — recommends. In a sector where loyalty is the number-one challenge and acquisition cost explodes, the operator that masters orchestration of these signals to serve better is the one that will keep the base.

Compliance

Native telecom compliance

ARCEP and national regulators

Native compliance with national requirements (ARCEP in France, equivalents per market). Integrated regulatory reporting, auditable traceability of automated decisions.

GDPR and telecom personal data

Architecture compartmentalized by data type (geolocation, consumption, communication content). Documented legal bases, automated right to erasure, granular opt-in.

Communication secrecy

Architecture strictly distinguishing usage metadata (volume, duration, location) from communication contents. No access to the latter by AI models. Compliance with applicable legal framework.

AI Act customer profiling

Commercial profiling is regulated (limited to high risk). Transparent architecture: the customer can consult, correct, refuse profiling. Critical automated decisions systematically validated by humans (HITL).

Independent audits

Provided contractually. Documentation, journals, logs and architecture audited by an independent third party at defined frequency. Particularly critical for national operators or trust providers.

Generative AI

Going further with generative AI

Beyond orchestration workflows, generative AI opens use cases that were not accessible two years ago. Here are three avenues we explore with our telecom clients.

GenAI use case 01

Multi-language AI technical support avatar, 24/7

A customer calling at 2 am for a connection problem, or speaking a rare language in the call-center. A photorealistic AI avatar of a support agent, multi-language synthetic voice, accesses the documentary RAG (procedures, scenarios, compliance scripts) and real-time customer context. It diagnoses, proposes a resolution, or escalates to humans the next day. The customer has support available when they need it, not only during opening hours.

Technology

Photorealistic Virtual Twin, multi-language cloned voice, RAG on support procedures, real-time OSS/BSS/CRM integration, escalation to human staff.

GenAI use case 02

Personalized video synthesis of the annual customer statement

Once a year, each customer receives a personalized video presenting their year with the operator: consumption, savings on optimized plan, communication screen time, recommendations for the next year. Not a generic email. A two-minute video spoken to their name, with their numbers, in their language. Personal touch at the scale of millions of customers.

Technology

AI video generation (Virtual Twin), multi-language text-to-speech (ElevenLabs), BSS and usage data aggregation, personalized LLM script generation.

GenAI use case 03

Generation of dynamic visual marketing offers

Instead of sending the same offer to all segments, generative AI produces for each customer profile a personalized visual offer: visual adapted to their segment and interests, message tailored to their situation, individualized savings or benefit calculation. Industrializable to tens of thousands of variations without overloading the creative team. Brand compliance maintained by AI guard-rails.

Technology

AI image generation (text-to-image), LLM copy generation, RAG on brand guidelines and compliance, CRM and BSS integration for personal data.

Typical roadmap

Typical roadmap

Phase 1

Phase 1 — Pilot on one signature workflow

One workflow chosen with you (e.g. automated technical diagnosis or predictive anti-churn), deployed on a customer subsegment. NPS and operational impact measurement. Model validation.

Duration

Three to four months

Phase 2

Phase 2 — Extension to three or four workflows

Expansion to complementary workflows. Industrialization of OSS, BSS, CRM, billing integrations. HITL framework rollout. ARCEP and regulator compliance validated.

Duration

Six to nine months

Phase 3

Phase 3 — Industrialization at operator scale

Full deployment. Connection to all silos. Executive workflow and impact dashboard (NPS, ARPU, churn, support capacity). Independent audit plan established.

Duration

Twelve to eighteen months

FAQ

Frequently asked questions

What AI workflows does Access International deploy in telecoms?

Access International orchestrates 9 AI workflows for telecoms: automatic technical diagnosis before transfer, digital subscription onboarding, predictive anti-churn (5-level ladder), plan personalization by usage, shop advisor copilot, AI editorial qualification + HITL (already delivered at Orange), antenna deployment optimization (already delivered), automated competitive intelligence (already delivered EMEA), SIM swap fraud detection. The orchestration layer connects to OSS, BSS, CRM and customer care without replacing any tool.

How does Access International handle ARCEP compliance and communication secrecy?

Our architecture is compartmentalized by data type: geolocation, consumption, communication content. Communication content is never accessible to AI, in compliance with communication secrecy. Legal bases (consent, contract execution, legitimate interest) are documented per use case. ARCEP obligations (service quality, tariff transparency, portability) are auditable via systematic logging. No AI use is deployed without compliance validation.

What is the AI + HITL editorial qualification delivered at Orange?

A large editorial team at an EMEA telecom operator produces daily articles, briefs, marketing posts, customer documentation. Each must be semantically qualified (theme, tone, legal compliance, brand alignment) before publication. Volume makes humans-only untenable, AI-only risky. Our orchestration layer combines tagger rules, NLP models, continuous brand lexicon learning, human validation on uncertain cases via HITL framework. Production maintained at scale, quality validated by editorial teams.

How does Access International's anti-churn ladder work?

A client who leaves does not decide overnight. There is a trajectory from weak to explicit signals. Our 5-level ladder detects each step (very weak signal, confirmed weak, medium, strong, explicit) and triggers the adapted action. Over-reacting early scares the client away. Under-reacting late loses them. At level 1, we observe silently. At level 5, we engage a senior advisor with pricing autonomy and honest acceptance of departure if not convincing.

How does Access International detect SIM swap fraud?

SIM swap consists in transferring a victim's number to an attacker's SIM to intercept authentication SMS (bank, account access). Our detection cross-references several signals: unusual IMEI change, inconsistent geolocation, recent account info modification, phone loss complaint, atypical post-change behavior. Prioritized alert to fraud cell with context. Automatic temporary blocking of sensitive SMS operations during verification, without interrupting voice.

What is Access International's doctrine on telecom anti-churn?

Felt service, not perceived surveillance. A subscriber who feels tracked — solicited at the wrong moment, sold while having an unresolved problem, followed without being served — becomes dissatisfied and leaves. A subscriber who feels served — fast diagnosis, competent advisor, offer adapted to real usage — recommends. In a sector where loyalty is the number-one challenge and acquisition cost explodes, the operator that masters orchestration of these signals to serve better is the one that will keep the base.

Can Access International serve MVNOs and B2B operators?

Yes. Our orchestration layer adapts to virtual mobile operators (MVNOs) that rent their network and want to differentiate on service, and to B2B operators serving enterprises and government. For MVNOs, focus on customer engagement and anti-churn. For B2B, real-time SLA dashboard, predictive escalation, network engineer copilot, automatic reporting. Our modular approach allows starting on a priority workflow and progressively extending.

How does Access International integrate industrial IoT for telecom operators?

Telecom operators manage increasingly massive IoT fleets (millions of connected objects). Our orchestration addresses specific pains: anomaly detection on sensor signals, alert prioritization by business criticality, IoT plan optimization by observed usage, failure prediction before breakdown. The layer connects to existing IoT platforms (LwM2M, MQTT) without replacing the technical stack. Particularly relevant for energy, transport, smart city.

Solutions addressable to this sector

Solutions addressable to this sector

6 products are available for deployment in this sector.

01
Delivered

WhatsApp — Chatbot and campaigns

Direct, automated engagement on the most open channel in the world.

Complete platform for deploying WhatsApp campaigns and interactive chatbots. The solution orchestrates personalized message sending at scale, ensures real-time performance tracking

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04
Delivered

GEO — Generative Engine Optimization

Measure your positioning in AI search engines.

Solution for analyzing and tracking your visibility in LLM-based conversational engines: Perplexity, ChatGPT, Google AI Mode, Gemini. The platform queries these engines on your tar

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05
Delivered

Digital Audit 360° — Security, UX, SEO, performance, compliance

Complete and actionable view of your digital presence, across all critical dimensions.

In-depth audit on all dimensions of your digital presence: application and HTTP security, user experience and accessibility, performance, organic SEO, legal compliance, social pres

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06
Internal test

Virtual Twin — AI avatar videos

Industrialized video production, from script to social distribution.

Automated generation of professional videos from a simple text script, thanks to digital avatar technologies. The solution covers the entire chain.

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08
Delivered

Social Media Data — Extraction and analysis

Structured social data serving your commercial intelligence.

Structured collection of public data from social networks in strict compliance with terms of use and GDPR. Cleaned, normalized data exported to your analytics tools or data warehou

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16
In progress / available

AI Customer Advisor and complaint management

Qualify your prospects, resolve complaints, measure AI ROI in customer relations.

AI customer advisor agent able to qualify a prospect across multiple axes (situation, objective, level, deadline, budget), recommend adapted or alternative solutions, handle common

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