Streambased
Industry | Telecoms

Streambased for Telecom

See network behaviour across time, not across systems

Streambased unlocks the full value of your Kafka architecture by unifying real-time network streams with full historical context. That opens up many powerful possibilities such as blocking fraud mid-call, preventing churn before it happens, and optimising your network in the moment.

Streambased exposes Kafka and Iceberg as different time horizons of the same dataset, allowing operators to relate live signalling, CDRs and telemetry to long-term behavioural patterns as they form.

This removes the need for batch replication pipelines and duplicate storage, enabling teams to investigate anomalies, detect fraud and understand customer experience without waiting for data to stabilise in analytical systems.

With Streambased, the boundary between present and past is no longer an obstacle.

You get the business certainty that comes from a single, unified view of your complete data universe where live CDRs meet years of billing history, real-time signalling informs historical fraud patterns and every network event gains instant context.

Let us show you what Streambased can do

Get a demo and discover the impact of Streambased on your business.

The telecoms challenge:

Real-time decisions blocked by ETL lag

Telecom networks generate high-volume, high-velocity data continuously. CDRs, signalling events, network telemetry, and customer usage flow through Kafka in real time.

At the same time, years of billing history, fraud patterns, and network performance baselines live in Iceberg and downstream analytics platforms.

But these two worlds remain disconnected, linked only by slow, expensive ETL pipelines that create critical gaps between insight and action.

Fraud intelligence built on past patterns quickly becomes unreliable without awareness of emerging attacker behaviour.

Network congestion emerges, but historical baselines can't explain whether it's abnormal without sight of current traffic context.

Churn models built on months of behaviour miss sudden shifts without visibility of most recent customer interactions.

Long-term equipment reliability analysis cannot predict imminent failure without awareness of the latest alarm signals.

Retention strategies derived from historical behaviour risk misfiring when they ignore the customer's current experience.

Network capacity planning based on historical traffic patterns loses meaning without understanding present load conditions.

The challenge is not data availability, but timing and architecture. These two worlds are typically connected by ETL pipelines that were designed for batch analytics, not real-time operational decisions. As a result, the contextual data needed to interpret live network events often arrives minutes or hours too late.

Close the gap between what just happened and all that came before

By treating Kafka and Iceberg as different time horizons of the same dataset, Streambased enables analytical applications to operate without temporal blind spots.

The Streambased solution

Certainty, control, visibility

Certainty: Fraud detection and revenue assurance

Wangiri scams, SIM box bypass, subscription fraud, interconnect manipulation... attackers evolve behaviour faster than analytical views adapt. Blacklists and fraud models built on historical activity struggle to explain emerging patterns without visibility into live signalling.

Fraud patterns rarely appear in live streams or historical data alone: they emerge when both are observed together. Streambased enables just that.

Teams can correlate live signalling streams (SS7, Diameter, GTP) and CDRs with months of behavioural history as a single dataset, allowing emerging patterns to be recognised as they form rather than after they stabilise.

What becomes possible: Holistic view of emerging fraud patterns

  • Block fraud mid-call: Evaluate live signalling against the subscriber's behavioural history during call setup - before the connection completes.
  • Behaviour-aware detection: Fraud rules operate on current activity and full historical context simultaneously, not delayed analytical views.
  • Subscriber-level correlation: Interpret suspicious SIM activity by immediately relating it to its long-term usage patterns.
  • Real-time revenue protection: Detect interconnect bypass and premium-rate abuse as behaviour emerges, not during reconciliation cycles.

Zero-copy architecture

for unified access to Kafka and Iceberg

Streambased turns Kafka from a write-only streaming backbone into a directly queryable analytical data source. By exposing Kafka topics as Iceberg-compatible tables and stitching them with existing Iceberg history, Streambased gives query engines a single logical view across real-time and historical data, without continuously copying data or running ingestion pipelines.

Streambased sits alongside your existing warehouse, complementing current ETL processes. The boundary between hot and cold data becomes invisible to your queries: one SQL statement seamlessly returns both real-time data and years of historical records, creating a single source of truth for network operations, customer analytics and financial reporting.

What this architecture enables

Instant data availability

New Kafka topics become instantly queryable in your BI tools, data science platforms and fraud detection systems.

Flexible retention economics

Balance Kafka costs vs. performance needs. Keep 3 days hot for fraud detection, 7 days for operations, historic data in cost-effective Iceberg storage – you choose.

Unified governance

Your Kafka ACLs, schemas and access controls automatically apply to analytics queries, creating a single security model across operational and analytical data.

Standard tool compatibility

Plugs easily into Tableau, PowerBI, Snowflake, Databricks, Spark, Trino – anything that speaks Iceberg.

What becomes possible?

Root cause analysis

Live alarms enriched with complete performance history enable ‘time travel’ debugging and pattern recognition, to distinguish isolated incidents from systemic issues.

Capacity planning

Real-time traffic loads analysed against seasonal/historic patterns to predict congestion before customer impact and inform infrastructure investment planning.

Operational intelligence (AIOps)

Correlate logs and metrics from OSS components (inventory, assurance, orchestration) with network performance to automate incident response and reduce MTTR.

Predictive maintenance

Real-time equipment telemetry compared against historical failure signatures. Vibration patterns, temperature anomalies, performance degradation tracked across months. Maintenance scheduled before critical failures occur.

5G & Open RAN optimisation

Slice performance monitoring with historical SLA baselines and RAN component optimization informed by weeks of operational metrics. Complete operational data informs vendor benchmarking.

Streambased helps your team

Streambased doesn't just help technical teams but can power better intelligence for the whole business.

Fraud & Security, Revenue Assurance

Turn network data infrastructure into strategic advantage

Block Wangiri scams, SIM box fraud and network security threats in real time, not after losses compound. Dynamic threat intelligence continuously updated from historical signalling patterns and network telemetry delivers complete behavioural profiles in milliseconds for real-time decisions.

  • Compare live CDRs against months of activity to detect complex fraud rings.
  • Network security threats (DDoS attacks, data breaches, intrusions) contained instantly through automated telemetry correlation.
  • Fraud prevented mid-call rather than discovered in monthly reconciliation.
  • Reduce false positives through complete behavioural context.
  • Protect interconnect and wholesale revenue in real time.

Platform & Engineering teams

Simplify the stack, free up the team

Erase the complexity of maintaining fragile ETL pipelines. No more 3am failures or weeks-long pipeline development for new data sources. Focus engineering resources on business value and innovation instead.

  • Query optimization and schema evolution handled automatically.
  • New data sources queryable instantly, not after weeks of development.
  • Self-service analytics for business teams reduces support burden.
  • More time for strategic projects like AI/ML model development.

Leadership

CIO, CTO, CDO

Turn network data infrastructure into strategic advantage

Transform regulatory storage from cost centre to value engine. Eliminate ETL overhead, accelerate decision-making from hours to milliseconds, and enable AI-driven operations, all while reducing storage costs and maintaining compliance with open standards architecture.

  • Single source of truth eliminates synchronisation issues.
  • Simplified architecture improves compliance and security.
  • Real-time AI/ML models informed by complete historical context.
  • Future-proof architecture built on open standards (Kafka + Iceberg).

Marketing & CX teams

Drive up Lifetime Value

Stop guessing what customers need. Know their complete context and respond optimally in the moment.

  • Drive down churn through contextually effective interventions.
  • Higher customer lifetime value via relevant, timely engagement.
  • Improved NPS scores from service recovery before complaints.
  • Better marketing ROI – right offer, right customer, right time.
Streambased

Talk to us about your data stack

We'd love to have a chat about data in your telecom network operations and show you how a unified, instantly queryable view of hot and cold data can drive measurable outcomes.