One AI engineering team builds four products, each with its own name: Carrier AI inside operator networks, the BroadNet AI platform inside enterprise infrastructure, DialerBee on outbound calls and Smart Waiter in restaurants. The first three share the same fraud engine, multilingual NLP and continuous-learning loop.
Trained on telemetry from 300M+ messages a day on a real network — not a generic dataset. MENA-native by design.
The AI product map
One AI engineering team, four products, each with its own name, page and buyer: Carrier AI for operator networks and BroadNet AI for enterprises are separate products.
Fraud scoring, smart routing, and multilingual intelligence trained on real carrier telemetry — the same models that protect billions of messages a month.
Three deployment surfaces
Three places the brain lives. Each surface has its own deep page; this is the map.
Carrier-grade ML running at line rate in front of operator SMSCs and signalling firewalls. Fraud detection, smart routing, sender-ID anomaly, SIM-box behaviour, intent classification on two-way traffic — all in the same verdict engine, trained on the operator's own labelled ground truth.
Proprietary Graph ML, autonomous agents with persistent memory, MCP tool use and multi-agent orchestration. Voice + chat + vision in one runtime. Deploy in 21 days on your terms — SaaS, private cloud, on-prem, or air-gapped.
Multilingual AI outbound dialler for BPOs, collections, telecom resellers and regulated contact centres. Language-aware AI AMD in 12 languages, BYOC SIP routing, WebRTC agents, and compliance-supporting controls for TCPA / GDPR / TDRA / CST.
The shared brain
These are the models. Where each one runs depends on the surface — but they're the same code, the same retrain pipeline, the same continuous-learning loop.
Transcript-based classification with agent feedback loops and tenant-scoped tuning. The same engine scores grey-route artefacts at the SMSC edge, flags impossible-cadence AIT inside the messaging surface, and decides whether an outbound voice call is reaching a human or a voicemail.
Native models in English, Arabic (Gulf / Levantine / Egyptian / Maghreb), Spanish (LATAM + EU), French, Italian, German, Turkish, Hindi, Urdu and more. Dialect-aware, slang-aware, trained on real MENA-native telemetry rather than generic Western datasets.
Graph ML and retrieval-augmented reasoning over the customer's own corpus. Audits itself for hallucinations. The same engine answers an enterprise support query, classifies an operator's RA dispute, or scores a dialler campaign's sentiment trajectory.
Autonomous agents with persistent memory and MCP tool use. They open tickets, update records, schedule appointments, draft proposals, and hand off to humans when policy says they should. Carrier deployments use the same framework to drive analyst-facing workflows.
Sub-second classification at line rate. Enterprise agent decisions sub-second. AMD detection under 1 second. All on the same inference plane.
Nightly retrain on the operator's / enterprise's / tenant's own ground truth. Analyst overrides feed tomorrow's model. Pin or veto any model version from the dashboard. Static rule-packs were retired years ago.
Why integrated
You can buy a carrier firewall from one vendor, an enterprise AI platform from a second, and an outbound dialler from a third. We've seen the procurement document. Here's what gets lost when you do.
Fraud patterns that show up in carrier traffic feed enterprise agent context. Customer-service intent classifiers improve the dialler's outbound message timing. Three vendors can't share signal across surfaces; one engineering team can.
Model versioning, retrain cadence, A/B evaluation, audit log, drift monitoring — same plane across the three surfaces. Buy three vendors, ship three MLOps stacks; buy from BroadNet, ship one.
GDPR + UAE PDPL + KSA PDPL + TDRA + CST + NTRA + TRC — enforced once at the data-plane boundary, not three times at three integration points. The audit-log story is uniform.
A novel smishing pattern caught at the operator firewall hardens the enterprise inbound classifier and the dialler's spam-detection in the same retrain cycle. One incident, three surfaces protected.
AI governance
Carrier deployments stay inside the operator's data plane. Enterprise deployments run SaaS, private cloud, on-prem, or air-gapped — the customer picks. DialerBee tenant data is per-tenant isolated.
Every model decision is logged with input fingerprint, model version, confidence score and downstream action. Seven-year retention available for regulated industries.
Compliance-supporting controls across every framework BroadNet's customer base operates under. Same posture across all three surfaces.
Prompt-injection defences, output filtering, sensitive-data scrubbing, and the rest of the LLM-specific OWASP discipline applied across the enterprise + dialler surfaces.
Anti-fraud SMS firewall deployed inside operator networks. e& Egypt is the named case study.
Read the case studyGraph ML + Agent Framework + Knowledge Engine, deployable SaaS, private cloud, on-prem or air-gapped on a 21-day enterprise timeline.
Platform detailsMultilingual AMD across English, Arabic, Spanish, French, Italian, German, Turkish, Hindi, Urdu. BYOC SIP, WebRTC agents, multi-tenant white-label.
DialerBee detailsFAQ
One AI engineering team, one shared codebase for the models. Three deployment surfaces with their own commercial structures: Carrier AI inside operator networks, the BroadNet AI enterprise platform inside customer infrastructure (also broadnet.ai), and outbound voice via DialerBee. Smart Waiter, for restaurants, is a fourth product from the same team. You can buy any one of the three. You can buy all three. The brain is the same.
Yes. Each surface stands alone. Enterprise AI runs SaaS, private cloud, on-prem or air-gapped — no telecom relationship required. DialerBee uses BYOC SIP — you can plug in any carrier, not just BroadNet.
Operator-side: the operator's own labelled ground truth (RA disputes, complaint queues, regulator advisories) blended with anonymised global signal. Enterprise: the customer's own corpus with the customer's own knowledge engine. DialerBee: agent corrections feed tenant-scoped tuning. No cross-customer data leakage — that's the firewall the integrated architecture actually exists to protect.
MENA-native, globally deployed. The model is trained on MENA-native telemetry (because that's where BroadNet's data depth is) but the same models perform across the markets BroadNet covers — EU, Americas, APAC. The dialect coverage is the differentiator that nobody else in the space matches.
broadnet.ai is the dedicated product site for the enterprise AI surface — the deeper technical documentation, knowledge-engine demos, agent framework playgrounds, integration guides. /platforms/broadnet-ai on this site is the overview; broadnet.ai has the full technical detail.
Tell us which surface you're evaluating — in your network, in your enterprise infrastructure, or on your outbound voice traffic. We'll scope the integration and stand up a pilot.
