TELECOM
Network-scale analytics, without the cluster.
One engine for traffic, billing and network data, running on your own infrastructure.
Fast by design
Full network data reconciled in hours, not days.
Data stays put
On-premise or private cloud. Subscriber and network data never leave your infrastructure.
Built for scale
Processes billions of records a day on a standard server.
Our approach
Built for what industry actually needs.
Anatella | Data prep engine
Connect to any sources
Call records, billing systems, network logs and CRM data, from any operator or vendor, in whatever format they’re in.
Processes at network scale
Billions of call and transaction records reconciled and aggregated, without sampling.
Real-time and batch, natively
Native MQTT support streams network telemetry as it’s generated, alongside scheduled batch processing.
Modeler | Predictive Engine
Automatic variable selection
Thousands of candidate variables, reduced to the ones that actually predict churn, fraud or demand.
Algorithms competing mathematically
Several models benchmarked against each other, the best retained on statistical merit.
Built-in Drift Report
Flags a model losing accuracy as usage patterns or network conditions shift.
SOLUTIONS
What it looks like in production.
150B transactions processed per month
Snype certifies traffic, revenue and fraud for a national telecom network, on a single standard server.
Churn detection accuracy up from 45% to 57%
MTN analyzed 12.1 billion records across 21.4 million subscribers to catch churn earlier.
Fraud recovery costs cut in half, €1.7M net gain
VOO flags suspicious subscriptions from month one, before losses compound.
Inbound sales up 20% within the 300-second SLA
27 real-time models tell VOO agents who to target and what to pitch, live.
Problems solved
What telecom operators fix with TIMi.
Slow reconciliation
A revenue figure that takes days to reconcile across operators and sources, and still gets challenged by a regulator.
Invisible fraud
Losses that surface only once the invoice cycle closes, after the booking is already done.
Stale churn models
A model retrained once a quarter, on a subscriber base that turns over every month.
Blind inbound calls
No real-time signal on what to offer the customer on the line.
FAQ
Common questions.
What is TIMi used for in telecom?
Telecom operators use TIMi to certify network and revenue data, detect fraud before it’s booked, model subscriber churn, and support real-time sales. Deployments include Snype (national network data certification), MTN (churn analysis across 21.4 million subscribers) and VOO (fraud detection and inbound sales).
Can TIMi run on-premise for a telecom operator?
Yes. TIMi runs on-premise or in a private cloud, on standard server hardware, with no cluster required. Subscriber, billing and network data stay on the operator’s own infrastructure.
How fast can TIMi process national-scale telecom data?
For Snype, TIMi processes 150 billion monthly transactions across 7 operators and over 200 data sources into certified traffic, revenue and fraud figures in 5 to 7 hours.
How much does TIMi improve churn detection accuracy?
For MTN, TIMi raised churn detection accuracy from 45% to 57%, analyzing 12.1 billion records across 21.4 million subscribers in under 5 days, using Social Network Analysis and 657 variables.
Can TIMi detect fraud before it affects revenue?
Yes. For VOO, TIMi flags suspicious subscriber behavior from the first month after activation, cutting recovery costs by 50% and preserving revenue on 36% of at-risk accounts.
Does TIMi integrate with existing billing, CRM or network systems?
Yes. TIMi connects natively to existing billing, CRM and network systems, and feeds predictions into them directly, without requiring a migration.
SEE FOR YOURSELF
Don’t take our word for it.
Run TIMi on your own data with a free trial or request a live demo.
