Network Management Systems (NMS/OSS)
Custom operations support systems and network management platforms for monitoring, fault detection, configuration management, and performance optimization across physical and virtual network infrastructure.
Years of Experience
Experts in Our Team
Happy Customers Worldwide
Projects Delivered Successfully
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Solvios is a telecom and IT software development company building custom BSS and OSS platforms, network management systems, telecom billing and revenue management tools, customer self-service portals, and AI-integrated operations software for mobile operators, ISPs, VoIP providers, and telecom infrastructure companies. We work across the full telecom technology stack web, mobile, cloud, and AI with the integration depth, real-time performance architecture, and compliance controls that telecom operations demand.
Custom operations support systems and network management platforms for monitoring, fault detection, configuration management, and performance optimization across physical and virtual network infrastructure.
End-to-end billing platforms, revenue management systems, and mediation layers that handle complex rating logic, multi-service bundles, real-time charging, and PCI-DSS-compliant payment processing for telecom operators at scale.
Web and mobile customer portals for account management, service configuration, usage monitoring, billing access, and support reducing call centre volume while improving customer satisfaction and self-sufficiency.
Business support systems and telecom-specific CRM platforms that manage the subscriber lifecycle from acquisition through service delivery, retention, and churn management with the integration depth that BSS/OSS connectivity requires.
Custom VoIP platforms, unified communications tools, real-time messaging infrastructure, and communication API integration for telecom companies building or modernizing their voice and messaging product stack.

Telecom software is some of the most operationally critical software that exists; a billing error affects every subscriber on the platform simultaneously, a network management failure can mean service outages across thousands of sites, and a customer portal that goes down during a peak service period generates support volume that overwhelms the call centre. We have built in this category and we know where the problems actually live.
Most telecom operators are running BSS and OSS infrastructure that was designed for a simpler service environment: fixed-line voice, basic broadband, straightforward billing. The product catalogue has grown, 5G and IoT services have been layered on top, and the original architecture is now a constraint on how fast the business can launch new services, modify pricing, or respond to competitive pressure. Modernising the BSS/OSS layer without disrupting live operations is one of the most complex software challenges in the industry.
Telecom billing is genuinely complex: convergent billing across voice, data, and content services, real-time charging for prepaid and hybrid subscribers, wholesale settlement with interconnect partners, regulatory reporting, and tax treatment that varies by service type, jurisdiction, and customer category. Systems that cannot handle this complexity accurately produce billing errors that result in revenue leakage, customer disputes, and regulatory exposure all of which are expensive to remediate after the fact.
Network operations centres at mid-size operators typically run five or more separate monitoring tools one per network domain, one per vendor, one for the transport layer none of which share a common data model or alert correlation engine. The result is that fault detection depends on engineers manually correlating alerts across screens, root cause analysis takes longer than it should, and MTTR is limited not by the speed of the fix but by the time it takes to identify what is actually broken.
Telecoms consistently rank among the lowest-satisfaction industries in customer experience surveys, and the software is a significant contributor. Self-service portals that do not work on mobile, billing portals that require a phone call to interpret, service change workflows that take days when they should take minutes, and chatbots that cannot resolve the queries they are deployed to handle. Churn in telecoms is expensive acquiring a new subscriber costs significantly more than retaining an existing one and poor digital experience is a leading driver.
Telecom networks are high-value targets both because of the communications data they carry and because of the critical infrastructure status that makes a successful attack on a large operator a national security event. SS7 vulnerabilities, SIM-swapping attacks, fraudulent international settlement, and increasingly sophisticated attacks on the BSS layer represent real and evolving threats that telecom software needs to be designed to resist rather than remediated after a breach.
Every telecom software engagement starts with the network architecture, the service catalogue complexity, and the integration landscape not with a feature list. The software is built to handle real operational load, integrate with existing network infrastructure, and support the subscriber volume that telecom platforms actually serve.
The telecom industry spans mobile network operators running national infrastructure at one end and niche VoIP providers serving a specific business segment at the other. The technical requirements, the regulatory obligations, and the competitive context are different at each point. We have built for organisations across this spectrum.

We will map your integration landscape, identify the architecture decisions that matter most for your network environment, and give you an honest path forward before any code is written. Response within 24 hours.

These are the capabilities that telecom software requires to operate reliably at carrier scale, integrate with network infrastructure, satisfy regulatory obligations, and support the subscriber volumes that communication platforms serve.
Multi-domain fault detection, event correlation that identifies root cause from alarm cascades, severity classification, automated escalation workflows, and the alerting architecture that pages the right engineer with the right context rather than triggering a flood of undifferentiated alarms.
Multi-service rating across voice, data, SMS, content, and IoT, with real-time charging for prepaid subscribers, bundle management, promotional logic, and the mediation layer that collects and normalises usage events from heterogeneous network elements.
End-to-end subscriber lifecycle management from onboarding through service activation, plan changes, and deactivation with bidirectional provisioning integration to network elements and the audit trail that tracks every service change against the subscriber record.
Web and mobile self-service with account management, usage monitoring, billing access, payment processing, and service request workflows designed to deflect contact centre volume while genuinely improving the customer experience rather than just adding another digital channel that does not work.
Automated reconciliation between network usage and billed revenue, discrepancy alerting, leakage investigation workflow, and the reporting that gives revenue assurance teams the visibility to close the gap between what the network delivered and what the billing system charged.
IRSF, SIM swap, wangiri, and PBX fraud detection using real-time call pattern analysis, ML-based anomaly scoring, and the automated blocking workflows that contain fraud losses before they accumulate to significant financial impact.
Northbound API exposure for BSS/OSS integration, southbound connectivity to network elements, partner API management, and the API gateway and security layer that controls access while providing the integration surface that modern telecom ecosystems require.
Lawful interception interface compliance, data retention management to regulatory requirements, universal service obligation reporting, interconnect settlement reporting, and the audit trail architecture that satisfies both internal governance and external regulatory obligations.
AI in telecom software is not about adding a chatbot to the customer portal. It is about building systems where machine learning improves network reliability, predicts subscriber churn before it happens, detects fraud in real time, and automates the network operations tasks that currently require engineers around the clock. The telecoms with the best operational economics in the next five years will be the ones that invested in AI-integrated BSS and OSS platforms now rather than treating it as a future initiative. Every telecom platform we build is architected with AI capability as a first-class consideration from the first sprint.

ML models trained on network element performance data, failure history, configuration changes, and environmental signals that identify components approaching failure, traffic patterns indicating capacity exhaustion, and configuration drift that correlates with historical fault types. Network operations centres using predictive maintenance reduce unplanned outages and extend the useful life of network infrastructure by addressing issues during planned maintenance windows rather than during service-affecting failures.
Highlights:

ML models trained on network element performance data, failure history, configuration changes, and environmental signals that identify components approaching failure, traffic patterns indicating capacity exhaustion, and configuration drift that correlates with historical fault types. Network operations centres using predictive maintenance reduce unplanned outages and extend the useful life of network infrastructure by addressing issues during planned maintenance windows rather than during service-affecting failures.
Highlights:
Telecom software projects fail most often not because the engineering is beyond the team's capability, but because the integration complexity with existing network infrastructure was underestimated, the data volume requirements were not designed into the architecture, or the operational impact of a cutover was not properly sequenced. Our telecom software development services follow a structured, integration-first delivery methodology designed to surface those problems at discovery before they become production incidents.
Here's exactly how it works.
We map your existing BSS/OSS landscape, network infrastructure, integration dependencies, data volumes, regulatory obligations, and operational constraints. Output is a project scope with integration architecture, data volume estimates, compliance requirements, and a phased delivery plan that accounts for the operational risk of changes to live telecom systems.
Technical architecture finalized with the integration depth, real-time processing requirements, and operational reliability constraints of the telecom environment. UI/UX design for customer-facing portals and operations interfaces reviewed before development begins because telecom operational tools need to be designed for the engineers who use them under pressure, not just for a product demo.
Two-week sprints with working software delivered at the end of each cycle. Network integration, real-time data processing, and security controls are addressed in the first two sprints not deferred to later phases where timeline pressure prevents getting them right. Integration with live network elements begins in a test environment in the first sprint.
Integration testing against real or representative network elements, performance testing at production-realistic data volumes, security testing covering the telecom-specific threat surface, and operational readiness validation. Telecom software QA must include the failure mode testing network element disconnection, high-volume event bursts, partial integration failures that expose reliability issues before they occur in production.
Phased cutover with parallel running of old and new systems during transition, rollback procedures tested before cutover begins, network operations team training, and post-cutover monitoring. Telecom platform cutovers are among the highest-risk software transitions that exist; careful sequencing and tested rollback are non-negotiable.
Post-launch monitoring, performance tuning as traffic volumes grow, integration maintenance as network infrastructure evolves, and feature development. Most telecom clients maintain a long-term development retainer telecom networks and business models evolve continuously and the supporting software needs to keep pace.
Telecom software projects range from a targeted customer portal build to a multi-year BSS modernisation programme. The right engagement model depends on your integration complexity, your operational risk tolerance, and how well-understood the requirements are before the engagement starts.
You are running a multi-quarter telecom platform build or BSS/OSS modernisation, scaling an existing platform to support new services or geographies, or augmenting your in-house engineering team with telecom-specific expertise without the cost and lead time of full-time hires.
Hand-picked engineers with telecom software experience, a QA specialist, and a technical lead working exclusively on your platform. Sprint planning and operational demos run on your calendar. Network integration, billing architecture, fraud detection, and AI network analytics modules are all handled in-house.
Monthly retainer. No surprise invoices, no scope-creep billing. Team composition flexes as your telecom roadmap evolves.
3–10 engineers
6-month minimum
Scales with 30-day notice
Building telecom software requires a development team that understands the integration complexity of network infrastructure, the operational risk of changes to live systems, and the reliability standards that communication services demand. Here is what makes the difference in practice.
BSS/OSS Integration Experience
We understand the BSS/OSS integration landscape, the data models, the protocol dependencies, the vendor API quirks, and the operational constraints of making changes to systems that support live subscriber services. That experience shapes every architecture decision we make in a telecom engagement and avoids the integration problems that surface six months into a build when a team without that background discovers what the network element APIs actually behave like in production.
Real-Time Data Processing at Telecom Scale
Billing mediation, network monitoring, fraud detection, and subscriber management all require real-time data processing at volumes that most enterprise software never encounters. We design for the data volume from day one message queue architecture, database partitioning, caching strategy, and horizontal scaling patterns that keep telecom platforms performing under the event rates that production network operations generate.
AI-Integrated Telecom Operations from Day One
Predictive network maintenance, intelligent fault correlation, churn prediction, and real-time fraud detection all require a data architecture designed for ML workloads from the start. We address the AI architecture strategy in discovery so that the intelligence layer is a core component of the telecom platform rather than a feature that requires rebuilding the data infrastructure to implement.
Operational Risk Management for Live Network Changes
Deploying changes to telecom infrastructure that is supporting live subscriber services carries operational risk that most software development methodologies do not adequately account for. We plan cutovers carefully, require tested rollback procedures before any live network change, and operate parallel running periods where the risk justifies the cost. We treat operational continuity as a delivery requirement, not a nice-to-have.
Communication Platform Integration Depth
Twilio, Vonage, Sinch, SIP, WebRTC, DIAMETER, SNMP, NETCONF we have integrated with the communication protocols and platforms that telecom software depends on. The integration work in telecom is where the complexity actually lives and where development teams without specific experience discover problems late. We find those problems in discovery and design for them upfront.
US-Based Communication, Global Engineering Capacity
Project management and client communication run on US business hours. Telecom software projects involve operational decisions, network cutover timing, production incident response, compliance deadline management that require fast, clear communication when they arise. The timezone alignment matters for telecom more than for most software categories.

Honest answers to the questions every CTO, head of IT, and network operations director asks before choosing a telecom software development company. If something is not covered here, our solution architects will walk you through it on a discovery call, no sales pitch, no fluff.
Cost depends on scope and integration complexity. A customer self-service portal with account management, billing access, and service request workflows typically starts at $40,000–$90,000. A custom telecom billing module or mediation layer ranges from $80,000 to $200,000 depending on the complexity of the rating logic and the number of network element integrations. A full BSS platform build or OSS/NMS system is typically a multi-phase engagement starting at $200,000 and scaling significantly with the size of the network and the number of integrations. We provide detailed estimates after an integration and architecture discovery phase.
A customer self-service portal takes 3–5 months. A telecom billing module with mediation and rating engine takes 5–9 months. A network management system covering a single network domain takes 6–10 months. A full BSS or OSS platform build is typically a multi-year programme delivered in phases, with the first production phase typically 9–18 months. The biggest variables are legacy BSS/OSS integration complexity and the operational risk management requirements of deploying changes to live network infrastructure.
Yes. BSS/OSS integration is one of our core competencies for telecom software development. We integrate via standard interfaces NETCONF, SNMP, DIAMETER, REST and via vendor-specific APIs where standard interfaces are not available. We map the integration landscape during discovery, identify the integration points where the documentation does not match the actual API behaviour, and design the integration architecture before development begins. The integration discovery phase is where telecom software projects are either set up for success or set up for expensive surprises.
AI-integrated telecom software development means building platforms where machine learning capabilities are core components of the system architecture not add-ons. In telecom this includes predictive network maintenance that identifies failing components before they cause outages, intelligent alarm correlation that surfaces root cause from alarm cascades, ML-based churn prediction that scores subscriber churn risk before the subscriber decides to leave, real-time fraud detection that identifies IRSF and SIM swap patterns as they develop, AI customer experience tools that resolve high-volume self-service contacts accurately, and network traffic analytics that feed capacity planning with predictive accuracy. These capabilities require a data architecture and streaming infrastructure designed for them from the start.
We treat operational continuity as a delivery requirement with the same weight as functional correctness. For changes to live telecom systems, we require tested rollback procedures before any cutover begins, implement parallel running periods where the risk warrants the cost, sequence changes to minimise the blast radius of a failed deployment, and coordinate cutover timing with network operations teams to choose windows that minimise subscriber impact. We have managed this across multiple telecom engagements and have never delivered a change to a live network that caused an unplanned service outage.
Yes. We build SIP-based VoIP platforms, WebRTC communication tools, unified communications infrastructure, and communication API integrations. Voice communication software has specific technical requirements: real-time media processing, low-latency signalling, codec management, and quality monitoring that distinguish it from standard web application development. We understand the signalling architecture, the media infrastructure requirements, and the operational monitoring that keeps VoIP quality at a level subscribers accept.
Telecom fraud requires a layered approach combining real-time rule-based controls with ML-based pattern detection. Rules handle the known fraud signatures velocity limits, destination number patterns, known bad actor lists. ML handles the evolving patterns that rules alone cannot catch IRSF activity that stays below individual velocity thresholds across many SIMs, SIM swap sequences that look like legitimate account activity in isolation, wangiri campaigns that adapt their calling patterns to avoid detection. We build both layers and operate them together with monitoring for false positive rates, because blocking legitimate calls while catching fraudulent ones is a customer experience problem.
Three models: Dedicated Telecom Development Team for long-term BSS/OSS platform builds and multi-quarter programmes; Time and Material for iterative development where integration complexity is still being scoped or the network environment is itself evolving; and Fixed Cost for well-defined telecom software projects where the integration requirements, data volumes, and operational constraints are clearly established before the engagement starts. We recommend the right model honestly based on the integration maturity and scope clarity of your project.
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