New!
NetoAI Partner of AWS for Telecom Specific LLM →
NetoAI Frontier Models: Building the Future of Enterprise Intelligence
From the industry’s deep reasoning to decisive action, from static text to human-like voice – step into the breakthroughs shaping the future of AI.
Trusted by visionary
global partners
AI-Powered Enterprise Transformation
An ecosystem of pretrained industry models – spanning LLMs, SLMs, ML, and voice – to fast-track AI innovation into business outcomes
TSLAM 
The world’s first telecom-specific Large Language Model, establishes a new industry benchmark by delivering Telecom SME Intelligence with precise reasoning and contextual intelligence at scale across customer and network life cycle
T-VEC
The World’s first Telecom-trained vectorization model that understands industry jargon and nuances, with 93% accuracy, enabling precise retrieval, advanced correlation, and enterprise-grade decision support
Ethical AI
Embedding trust and governance into the AI fabric through a structured framework of 7 categories and 11 sub-categories to ensure fairness, accountability, and responsible deployment remain integral to every conversation
ML Hub
Leveraging 20+ machine learning models to drive predictive and adaptive capabilities, enabling organizations to forecast, optimize, and automate operations with scalability, precision, and transparency
Voice Model
Elevating Human-like conversation through T-Synth TTS, engineered for immediacy, clarity, and multilingual reach. The Enterprise ready voice agent provides frictionless and contextual experiences with sub-600 ms latency
Scalable, Cost-Effective, Enterprise Ready
Accelerate your business with industry-specific LLMs (TSLAM). Get smarter outcomes at lower cost and enhanced sustainability—all while maintaining complete control over your data. Our flexible deployment options, from on-premise to the edge, ensure you meet all security and compliance requirements.
Open Source on Hugging Face
Oct ’25
TSLAM – 4B
For Edge Computing – Retrieve runbooks and telemetry,
ground responses with RAG.
Request Access →
Mar ’25
TSLAM -1.5B
For Laptop & Desktop – Triage tickets, extract intents,
summarize diagnostics.
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July ’25
TSLAM – Mini 2B
For Laptop & Desktop – Assist field ops with checklists,
commands, context.
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Enterprise Models
May ’25
TSLAM – 8B
For Cloud & On-prem (GPU Infra) – Operate agent
workflows, call tools, enforce policies.
Request Access →
Aug ’25
TSLAM – 18B
For Cloud & On-prem (GPU Infra) – Reason across layers;
propose root cause and remediations.
Request Access →
What Makes Our Models Different
Cross-Domain Telecom Reasoning
Delivers reasoning across customer and network life cycle – with deep knowledge of vendor specifications, industry standards, configurations, and regulatory requirements.
Enterprise-Grade Governance
Policy guardrails, RBAC, and audit trails – plus evidence-backed safety, bias, and robustness checks – for security, compliant, transparent, trustworthy AI by design.
Proven Domain Accuracy
Validated at ~93% domain intelligence on telco workflows and terminology, outperforming general-purpose LLMs in operator contexts.
Low-Latency, Efficient Inference
Optimized decoding and quantization enable real-time agent conversationwith high throughput – even on constrained compute.
Cloud Ready, On-Prem Capable
Deploy on-prem, at the edge, on mobile, or across private and public clouds – built for portability, control, and compliance.
Multi-modal & Multi Lingual Capability
Built with multi-modal understanding and multi-lingual fluency, our models interpret customer needs across voice, text, and documents – powering seamless interactions
Model Que
Model Que transforms a generic base LLM into an industry-specific powerhouse. It automatically converts any type of document – PDFs, reports, manuals, or logs into a structured query-answer dataset for fine-tuning. With built-in optimization capabilities, Model Que ensures the adapted LLM is not only domain-trained but also efficient, accurate, and ready for real-world deployment.
Faster Fine-tuning from months to weeks
%
Reduction in Model Fine-tuning cost
%
Coverage on Domain, Ethical & Technical Benchmarking
T-VEC: Telecom-Specific Embedding Model
Deeply fine-tuned with a triplet-loss objective on curated telco corpora, it is the first open-source telecom tokenizer and leads benchmarks (MTEB avg 0.825; 0.938 on an internal telecom triplet test vs <0.07 for generic models).
%
AI Accuracy in Telecom Domain
%
Hallucination Reduction - RAG Faithfulness Improvement
%
Pass Rate Across Policy Governance and Security Checks
Predictor
Predictor simplifies the journey from raw data to powerful insights. It streamlines the entire ML lifecycle – from data pre-processing and visualisation to model selection, training, and evaluation. With built-in accuracy tracking and deployment capabilities, Predictor can create, optimise, and scale ML models for actionable intelligence.
Faster Fine-tuning from months to weeks
%
Reduction in Model Fine-tuning cost
%
Coverage on Domain, Ethical & Technical Benchmarking
AI Models Trained Across Customer and Network Life Cycle
20+ Models Supporting Forecasting & Prediction across Sales, Marketing, Billing and Network
Network Alarm Management
- Alarm Correlation
- Network Outage Prediction
- AI driven Root Cause Analysis
Troubleshoot Network Faults
- Network Fault Prediction
- Guided Fault Troubleshooting
- Closed Loop Automation
Network Planning
- Capacity Forecasting
- Automated Plan and Build
- Digital Twin - Simulation
Sales & Marketing
- Personalisation Model
- Sales Forecast Model
- Recommendation Engine
- Lead Scoring
- Dynamic Pricing Model
Intelligent Customer Service
- Customer reliability analysis
- Sentiment Analysis
- Customer Lifetime Value Analysis
- Churn Prediction
- Customer Feedback Analysis
Service Delivery
- Intent-driven Service Fulfilment
- Automated Optimal Path Selection
- Quote to Order Conversion Assistant
Next-Gen Voice AI for Human-Centric Enterprise Conversations
NetoAI’s Voice AI Agents redefine enterprise engagement with low-latency, multilingual, and human-centric interactions – built for effortless deployment across every customer channel, and engineered to scale with unmatched intelligence and flexibility.
Faster time-to-build from design to deployment
Cost-effective with on-prem optimized pipeline vs APIs
multilingual support out-of-the-box - Spanish, Arabic, French, Hindi, and more
Key Features
Human-Centric Conversations
Intelligent interruption handling with multilingual fluency and regional dialect adaptation – making every interaction natural and effortless
Unified Omnichannel Experience
Seamlessly connect across channels – calls, apps, IVR, or digital platforms – ensuring consistency everywhere customers engage
Voice Cloning & Personalization
Create realistic, brand-aligned voices that adapt to your enterprise identity and customer expectations
Real-Time Responsiveness
Delivering end-to-end responses in under 600ms, enabling real-time, natural, fluid conversations
Flexible Enterprise Deployment
Built for any environment – mobile, on-prem, or cloud – with enterprise-grade portability and control
Enterprise-Grade Security & Governance
Designed with built-in governance, compliance, and enterprise security to protect data and ensure trust at scale
NetoAI’s Ethical AI Framework
(Bias Mitigation, Robustness Validation, Privacy Protection)
Comprehensive Evaluation: Thousands of prompts across categories rigorously test and ensure robust, ethical, and reliable AI performance.
Top Resources for You
TSLAM 1.5B is a telecom-specific Small Language Model (SLM) that provides a strong foundation for telecom service lifecycle automation, a domain-focused alternative to general-purpose LLMs and SLMs.