ViewtiAI

Artificial Intelligence Serving  Observability

AI Observability Platform
Powered by Viewtinet

Viewtinet delivers a next-generation AI Observability Platform that unifies monitoring, analytics and troubleshooting through advanced Machine Learning, Deep Learning and LLM-based intelligence. It automates dashboards, detects anomalies, explains data, correlates events and performs full AI Root Cause Analysis across any dataset.

 

Transform Observability
With Advanced AI and AIOps

With Viewtinet 7.0, organizations move from traditional monitoring into full AI Observability. Our AIOps-driven engine collects, correlates and analyses any type of data— any log or metric, SNMP, ICMP, topology, Syslog, Netflow, wire data, API events and more—in real time. The platform applies machine learning, deep learning and LLM technology to deliver autonomous insights, intelligent automation and instant explanations.

AI Interaction for next generation observability

LLM-Powered AI Observability
and Natural Language Interaction

Viewtinet integrates Large Language Models (LLMs) directly into its analytics pipeline, enabling users to explore their data with natural-language prompts. Ask questions, generate insights, build dashboards or request troubleshooting guidance—all with an AI copilot that understands your environment.

 

ViewtiAI
Automated Data Analysis at Every Level

  • Card-level Analysis: AI explains spikes, patterns, trends and anomalies directly inside each KPI card.
  • Dashboard Analysis: Complete dashboard summaries, cross-correlation of KPIs and narrative insights generated automatically.
  • Raw Data Analysis: AI processes massive datasets—logs, metrics or flows—and extracts human-readable insights instantly.

Viewtinet Copilot
Autonomous Dashboard & KPI Creation

The Copilot builds dashboards, cards and metrics automatically using natural-language instructions. No need to select data sources, create ETL rules or configure KPIs. The Copilot discovers the right datasets, models them and generates complete observability content in seconds.

Observability Copilot
Root Cause Analysis with AI

AI Root Cause Analysis
RCA Engine

 

Viewtinet’s RCA Engine uses AI to correlate events, isolate symptoms and identify the root cause across any data source. The system evaluates metrics, logs, topologies, flows and wire data to deliver a structured RCA report including evidence, confirmation steps and recommended fixes.

AI Observability with Endless RCA Use Cases
No matter where the data is coming from

AI-powered observability unifies network traffic, logs, metrics, and events to automatically correlate data and pinpoint problems in real time. By transforming complexity into clear, actionable insights, organizations can proactively assure performance, reliability, and user experience across their digital services—some of the use cases we can address include the following:

  • Packet loss and latency diagnosis
  • Link congestion and bandwidth bottlenecks
  • Device failures and hardware issues
  • Misconfigurations and routing issues
  • Security anomalies and DDoS attacks
  • Service-level issues 
    • VoIP
    • Video
    • SaaS
    • Microsoft Teams
    • Zoom
  • Connectivity problems
ViewtiAI Root Cause Analysis
AI Anomalies

AI Observability for Wire Data
automatic anomaly detection

Viewtimon uses Deep Learning to analyse wire data in real time, automatically classifying applications, detecting anomalies and generating KPIs without predefined rules. This provides a new layer of AI Observability for network performance, QoE metrics, application behaviour and security deviations..