Years in industry
In-house automotive software developers
Automotive projects delivered
Of middle & senior specialists
Years in industry
In-house automotive software developers
Automotive projects delivered
Of middle & senior specialists
Elinext est une société de développement de logiciels sur mesure avec une expertise approfondie dans l'industrie automobile.
Nous développons une large gamme de produits logiciels, y compris les logiciels de gestion automobile, les logiciels de gestion des réparations et de diagnostic des pièces et d'autres solutions logicielles automobiles.
CE SONT LES SPHÈRES SUR LESQUELLES ELINEXT MET LE PLUS L'ACCENT LORS DU DÉVELOPPEMENT DE PRODUITS POUR NOS CLIENTS.
Let's discuss your needsLes développeurs d'Elinext sont des experts en données, nous savons donc comment créer un logiciel qui rassemblera, digérera, analysera et tirera des conclusions exploitables. Les appareils IoT (capteurs et similaires) permettent de collecter des données sur la direction, le freinage, la navigation automobile, et nos produits logiciels analysent ces données pour obtenir des informations viables pour l'amélioration continue des capacités de conduite.
Les constructeurs automobiles ont de nombreux nouveaux besoins informatiques inédits. Parfois, seuls les modèles de cloud computing et de calcul hybride peuvent y remédier, car les solutions sur site n'ont pas la capacité de retenir la charge de travail sur les puissances actuelles. Nous produisons des logiciels personnalisés basés sur le cloud de la plus haute qualité pour les entreprises automobiles.
Les voitures modernes ont tendance à être remplies de logiciels, et parfois ces solutions ne sont pas plus simples que celles utilisées dans les avions modernes. Il permet de collecter de grandes quantités de données, tandis que l'analyse de ces données permet de les exploiter pour ajouter de la valeur à l'expérience de conduite via des applications embarquées. Elinext conçoit une large gamme de solutions embarquées.
La fabrication automobile exploite l'énorme quantité de données générées. Les entreprises ont tendance à se tourner vers des plateformes d'analyse et d'IA basées sur l'industrie. Pour que la voiture devienne automatisée, il y a un besoin en IA, en analytique. L'analyse peut être appliquée de nombreuses manières dans le domaine de l'automobile, de l'évaluation de l'efficacité et des coûts de production à l'analyse des préférences des clients et à l'anticipation des rappels.
Elinext développe le logiciel de maintenance prédictive capable de gérer un grand volume de données sur les véhicules. Si vous êtes à la recherche d'un partenaire de développement logiciel expérimenté dans l'industrie automobile et le développement SaaS, nous sommes la bonne entreprise pour traiter vos projets. Pour l'analyse des données du véhicule, nous proposons des technologies utilisant des algorithmes d'apprentissage automatique et créons des outils en ligne complets.
Embedded firmware developed with structured coding, secure boot, firmware updates, testing, debugging, and automotive delivery practices.
Prototype delivery plus HIL and SIL testing to validate functionality, performance, responsiveness, and release readiness before launch.
Porting and optimization for hard, firm, and soft real-time automotive operating systems where responsiveness and fault tolerance matter.
Maintenance and support to keep automotive IT systems current, detect issues early, resolve incidents, and protect long-term technology value.
CHEZ ELINEXT, NOUS DÉVELOPPONS LES TYPES DE PRODUITS LOGICIELS SUIVANTS APPLICABLES DANS L'INDUSTRIE AUTOMOBILE.
Let's discuss your needsLes scanners numériques et les appareils similaires de l'Internet des objets capables d'effectuer des diagnostics embarqués complexes sont extrêmement utiles et populaires dans l'industrie automobile. Les développeurs d'Elinext fournissent des logiciels qui permettent de déterminer l'état de “santé " des systèmes et de leurs composants.
Bien qu'il y ait beaucoup de débats autour des voitures sans conducteur, toute fonction d'aide à la conduite utile qui fonctionne vraiment et contribue à la sécurité sur la route est un avantage indéniable pour la société. Si vous opérez dans cette industrie, Elinext peut vous fournir des solutions personnalisées qui fonctionnent dans les véhicules équipés de caméras et de capteurs.
Les équipes d'Elinext fournissent des apps et des systèmes GPS qui permettent aux conducteurs de déterminer les emplacements géographiques et les coordonnées de la destination. Nous proposons également des solutions logicielles pour les écrans de navigation intégrés et autres affichages à la disposition du conducteur.
Si nous parlons de véhicules contrôlés uniquement par des systèmes logiciels, ils ont besoin de mises à jour. L'envoi en direct (OTA) est l'option qui est souvent incluse dans l'ensemble des fonctions de nos solutions logicielles automobiles.
5G connectivity to improve fleet management, autonomous vehicle reliability, real-time data exchange, and user experience.
Edge computing architectures that process road, pedestrian, traffic, sensor, and vehicle data closer to the source for real-time response.
Blockchain solutions for supply chain transparency, vehicle history, ownership transfers, trusted records, and financial transactions.
Cybersecurity for connected vehicle ecosystems, including segmentation, encryption, RASP, secure boot, authentication, and regulatory alignment.
Elinext est une société de développement de logiciels sur mesure avec une expertise approfondie dans l'industrie automobile.
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"Being a long-term partner to global auto players like Volkswagen, Parrot, and Juice, we understand the disruptive trends reshaping the industry: rapid innovation, stricter sustainability regulations, and rising consumer expectations. With almost 30 years in custom software development, we can deliver end-to-end automotive software services with confidence."
Elinext est une société de développement de logiciels sur mesure avec une expertise approfondie dans l'industrie automobile.
Les constructeurs automobiles ont de nombreux nouveaux besoins informatiques inédits.
Reliable software for customer service, sales optimization, and real-time manufacturing data, workflows, and outcomes.
Systems for vehicle health monitoring, route optimization, expense management, driver safety, and fleet-wide operational control.
Booking, fleet monitoring, payment, navigation, and operational tools for car rental and vehicle hire organizations.
Inventory, procurement, aftermarket supplier, multi-stage sales, and CRM software for dealers and auto parts businesses.
Product lifecycle, production planning, inventory, simulation, supplier relationship, order, and logistics management platforms.
Safety and driving systems with V2X connectivity, lane keeping, driver behavior monitoring, and automatic emergency braking.
Centralized car-sharing platforms for fleets, customers, vehicle inspections, readiness checks, and scanner applications.
Auto insurance apps and platforms for policies, claims communication, estimates, underwriting, auction workflows, and back-office automation.
NOUS ÉNUMÉRONS CERTAINS DES AVANTAGES QUE LE LOGICIEL AUTOMOBILE APPORTE AVEC LES FONCTIONS DE PRODUCTION QUI DEVIENNENT BEAUCOUP PLUS PRATIQUES ET AMÉLIORÉES À L'AIDE DU LOGICIEL.
Dmitriy Golubitskiy
CTO & Head of Technology
Suiver Toutes les Dernières Normes de Conformité
Optimiser la Production
Améliorer la Qualité du Produit Final
Review embedded software, C++, IoT, QA, business analysis, and delivery specialists who can support automotive software initiatives.
Years
GMT+2
C++ Developer
MSc in Computer Science
Wroclaw University of Science and Technology
Elinext a conçu un ERP sur mesure pour un fournisseur de services automobiles en Allemagne, intégrant gestion RH, synchronisation des événements et réservation de réunions.
La société Suisse spécialisée dans la création de solutions innovantes de recharge pour véhicules électriques est venue à Elinext avec l'idée de créer des apps mobiles iOS et Android.
Le projet est une plateforme de vente aux enchères de voitures où les clients B2B peuvent soit vendre leurs voitures directement, soit reconstituer la flotte de voitures mises aux enchères.
The Parrot team is very proud of Elinext`s development, validation, design and management teams for their involvement and willpower to carry out the projects that Parrot entrusts to them. Let`s keep up the good work with more exciting, attractive and innovative projects!
AUTOSAR is an architectural standard for automotive embedded software. It separates hardware from software, improving reuse, portability, and compatibility across vehicle platforms.
AI and machine learning help automotive companies improve autonomous driving safety, manufacturing processes, supply chains, fleet operations, diagnostics, and customer service.
V2X communication lets smart vehicles exchange real-time data with drivers, other vehicles, infrastructure, and the surrounding environment through sensors, cameras, and wireless connectivity.
Elinext supports automotive projects with consultants familiar with AUTOSAR, ASPICE, UN R155, UN R156, ISO 26262, GDPR, FIPS 140, IEC 62443, and related requirements.
Timing depends on product functionality, integrations, platform complexity, team size, engineering seniority, compliance expectations, and the selected delivery model.
Explore mobile app development for the automotive industry with Elinext. Learn how custom apps enhance vehicle performance, customer experience, and more.
In simple terms, RPA in telecom is all about robots using software to handle repetitive work across billing systems, CRM platforms, and network tools. RPA helps carriers, MVNOs, and service teams deal with huge volumes of data every day, so they can focus on their customers instead of admin stuff. Right now, the global telecom sector is huge but under pressure. Worldwide revenues have already reached up to $4.98 billion in 2025, with forecasts to cross $44.56 billion in 2035. At the same time, digital networks are everywhere. 5G coverage, IoT connections, and mobile broadband continue expanding, and demand for speed and quality keeps rising. Key Takeaways According to projections by The Insight Partners, the global RPA market is set for strong expansion, rising from about $4.48 billion in 2024 to nearly $20.83 billion by 2031. A study by Nokia reports that network traffic grows by about 30 to 45% each year, forcing telecom providers to upgrade their infrastructure to keep service stable About 53% of companies have already started using RPA, and another 19% plan to do so within two years, according to the Deloitte Global RPA Survey. What is RPA in the Telecom Industry? RPA in telecom is software that acts like a digital employee, one that clicks, copies, checks, and updates data across systems just like a human would, but faster and without mistakes. Think of it as a tireless back-office assistant that follows clear rules to handle billing, order entry, number porting, or ticket updates. It does not replace core systems. Instead, it works on top of them and connects the gaps. Still rely on manual workflows that slow your team down? Opt for telecommunication software development services that really drive growth. Book A Call How Robotic Process Automation (RPA) Transforms Telecom? RPA transforms telecom by automating core operational flows such as order provisioning, SIM activation, billing validation, and fault ticket routing across OSS and BSS systems. Bots work across multiple platforms at once, which shortens service delivery cycles, reduces revenue leakage, and improves SLA compliance. This helps operators respond faster to network events and customer requests without overloading internal teams. What are the Key RPA Use Cases in Telecommunications RPA in telecommunications covers daily operational pain points across network, billing, and customer service. It handles routine digital tasks that slow teams down and create risk. Below are the core areas where bots deliver clear business impact. Improved Productivity RPA handles repetitive tasks such as data entry, ticket updates, usage checks, and report generation across OSS and BSS platforms. This frees telecom teams from routine admin work and lets them focus on network optimization, customer cases, and revenue-related tasks, which lifts overall operational output. Reduce Turnaround Time Bots process service orders, SIM activation, number porting, and change requests across multiple systems at once. Instead of waiting for manual handoffs, workflows move instantly, which shortens service cycles and helps operators deliver faster responses to customers and partners. Reduce Errors RPA in the telecom industry follows predefined rules when validating invoices, updating customer records, or reconciling usage data. Since bots do not skip steps or overlook fields, data stays consistent across systems, which lowers billing disputes and revenue loss. Reduce Costs Automation reduces the need for large teams to manage high-volume back-office processes such as claims handling or account updates. With fewer manual interventions and less rework, telecom providers cut operational expenses while keeping service quality stable. Improved Margins RPA supports revenue assurance tasks like usage verification, tariff validation, and partner settlement checks. By catching discrepancies early and ensuring accurate billing, operators protect income streams and strengthen profitability without major system upgrades. Easy Mention of Old Customers Bots gather historical data, contracts, past interactions, and usage patterns from different platforms in seconds. This gives service agents a full view of existing customers, which supports smarter retention strategies and reduces churn risk. Attending New Customers RPA automates onboarding steps such as identity verification, account setup, credit checks, and number allocation. The activation process becomes faster and more consistent, which creates a smooth start for new subscribers. Better NPS Automation speeds up issue resolution, keeps customer data accurate, and ensures status updates move across systems without delay. When service works as promised, and problems get solved quickly, customer satisfaction grows, and NPS scores improve. [caption id="attachment_43801" align="alignnone" width="637"] Benefits of rpa in telecom[/caption] "RPA in the telecom industry is not simple because operators run on legacy OSS and BSS systems that rarely integrate well, and processes often change midstream. If you automate chaos, you scale chaos. At Elinext, we first map and stabilize workflows, then deploy bots where they bring real control. The impact is fewer failures, cleaner data, and operations that finally feel manageable." - Alexey Trigolos, expert in telecom software development. Agentic AI vs RPA for Telecommunications RPA and agentic AI solve different layers of telecom automation. RPA follows clear rules and executes structured tasks such as billing checks or order updates across OSS and BSS systems. Agentic AI goes further: it can analyze context, make decisions, and adapt to new inputs. In practice, RPA acts as the execution engine, while agentic AI becomes the decision layer that guides what actions should happen next. Elinext, as an AI software development company , makes the best use of advanced technology to strike the perfect balance between RPA and agentic AI. Right now, agentic AI is still at an early adoption stage in telecom. Many operators run pilots focused on network analytics, predictive maintenance, and smart support. The market grows fast, with a forecast to reach $ 8.74 billion by 2031. Though driven by AI investment and 5G complexity, most companies still rely more on RPA than agentic AI as the stable foundation for large-scale automation. [caption id="attachment_43802" align="alignnone" width="637"] Global ai in telecom market[/caption] Elinext RPA Development Solutions for the Telecom Industry Elinext delivers RPA in the telecom industry solutions tailored for telecom environments with complex OSS and BSS landscapes. Our custom RPA development services combine automation expertise with deep domain knowledge in billing, provisioning, and network operations. We analyze real workflows, design stable bot architectures, and ensure secure integration with legacy systems. The result is reliable automation that supports growth without disrupting core telecom processes. Ready to bring real automation into your telecom operations? Let’s build RPA that works in your environment, and not just on paper. Choose RPA The Benefits of RPA in Telecom RPA in telecommunications strengthens core operations across OSS and BSS by automating provisioning, billing validation, revenue assurance, and fault management flows. Bots move data between legacy systems without heavy integration work, which improves SLA compliance and limits revenue leakage. Operators gain better process visibility, stable audit trails, and the flexibility to scale service volumes without constant headcount growth. What is the Future of RPA in Telecom? RPA in telecom moves beyond simple task automation and becomes part of a broader digital strategy. Operators now look at automation as a long-term capability that supports AI, cloud adoption, and stronger operational control across network and customer domains. Integration with AI & Intelligent Automation RPA will work side by side with AI models that analyze traffic patterns, detect anomalies, and predict churn. AI decides, RPA executes. In telecom, this means smarter fault resolution, automated root cause analysis, and dynamic customer offers based on generative AI development services and above. Cloud & RPA as a Service (RPAaaS) More operators shift automation to cloud environments to scale faster and reduce infrastructure overhead. RPAaaS allows telecom providers to deploy bots on demand, manage updates centrally, and support distributed teams without heavy on-prem setups. Human with Bot Collaboration Future telecom operations rely on mixed teams where bots handle structured flows and employees step in for judgment calls. Agents receive pre-filled cases, validated data, and clear next steps, which improves speed and reduces stress in high-volume environments. Enhanced Security and Governance As automation expands, telecom firms put strong governance in place. Central bot control, access management, and full audit logs become standard. This ensures compliance with industry regulations and protects sensitive customer and network data. "Telecom looks structured from the outside, but inside, you often find dozens of micro-processes built over years of quick fixes. That makes RPA tricky, because bots need clarity and stable logic. At Elinext, we start with process discovery and performance analysis before we touch automation. Once the flow makes sense, bots deliver real gains in SLA control, revenue assurance, and team workload balance." - Alexey Trigolos, expert in telecom software development. Conclusion RPA in telecommunications turns complex, fragmented operations into structured, measurable digital workflows. It does more than cut costs. It exposes weak spots in OSS and BSS chains, reduces revenue leakage, and brings discipline to provisioning, billing, and support. The real challenge is not automation, but process clarity and governance. As networks grow with 5G and IoT, operators that treat RPA as a strategic backbone, not a quick fix, will build faster, leaner, and more resilient telecom businesses. RPA in Telecom: Terms Explained RPA Robotic process automation is software that mimics human actions in digital systems to execute rule-based telecom tasks with speed and accuracy. Bot Orchestration Bot orchestration is the centralized control of multiple RPA bots to manage schedules, workloads, and process dependencies. BSS (Business Support Systems) BSS are telecom platforms that handle billing, customer data, product catalogs, and revenue-related operations. OSS (Operations Support Systems) OSS are systems that support network operations such as provisioning, fault management, and service monitoring. CRM (Customer Relationship Management) CRM solutions for the telecom industry are platforms that store customer data, interaction history, and service records to support sales and marketing teams. Order Management System (OMS) OMS is a platform that tracks and processes service orders from request to activation across telecom systems. It can be a part of ERP software for the telecom industry . RPA as a Service (RPAaaS) PAaaS is a cloud-based automation model where bots run and scale without heavy on-prem infrastructure. API Automation API automation uses system interfaces instead of screen actions to trigger data exchange and execute telecom workflows. AHT (Average Handling Time) AHT measures the average time an agent spends resolving a customer request from start to finish. FCR (First Call Resolution) FCR shows the percentage of customer issues solved during the first interaction without follow-up. SLA (Service Level Agreement) SLA is a contract that defines service performance targets such as uptime, response time, and resolution speed. FAQ What is RPA and why is it important for telecom? RPA is software that automates rule-based digital tasks. It is used to handle billing, provisioning, and support workflows. Telecom companies apply it to reduce errors, protect revenue, and improve service speed. Which telecom processes benefit most from RPA? High-volume rule-based processes benefit most from RPA. Operators use it for order entry, SIM activation, billing validation, and ticket routing to improve accuracy and cycle time. How does RPA improve customer experience? RPA supports faster issue resolution and accurate data updates. Telecom providers use it to reduce wait times and raise service consistency for customers. Can RPA work with legacy telecom systems? Sure. RPA is a technology that works on top of existing systems without deep integration. It interacts through user interfaces or APIs. How does RPA reduce operational costs? RPA in telecommunications reduces rework, billing disputes, and processing time. Telecom operators apply it to lower labor costs and limit revenue leakage. How is RPA combined with AI in telecom? RPA is task execution software, while AI handles analysis and decisions. Telecom companies combine them so AI detects patterns and RPA performs actions such as updates or notifications. What are the common challenges of RPA in telecom? RPA faces challenges when processes lack structure. Telecom environments often have fragmented systems and changing rules. Companies address this with process mapping and governance before automation rollout.
Learn how RPA delivers benefits and use cases in healthcare in 2026, from admin automation to clinical support.
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