InsightFinder

InsightFinder: the AIOps platform that predicts incidents instead of paging you after them

InsightFinder is an AI-driven reliability platform born from academic research — founder Dr. Helen Gu is a computer science professor at NC State with prior work at IBM Research. Its Unified Intelligence Engine applies patented unsupervised machine learning plus fine-tuned, domain-specific small language models to metrics, logs, traces, and events, detecting anomalies and predicting business-impacting incidents up to six hours before they land.

The platform increasingly covers AI systems themselves: model drift detection, LLM and agent reliability monitoring, and root-cause analysis for production AI workloads. In 2026 it launched ARI, an operational reliability agent that accelerates incident response and learns business context over time. Enterprise users include Comcast, FedEx, Dell, UBS, Visa, and TD Bank; deployment is cloud or on-premises.

Key Features

• Incident prediction up to 6 hours before impact via unsupervised ML
• ARI operational reliability agent for automated incident response
• Model drift detection and root-cause analysis for production AI and LLM workloads
• 90% alert-fatigue reduction through event correlation, with 99.9% log compression
• Composite AI: fine-tuned domain-specific small language models, not just a GenAI wrapper
• Cloud or on-premises deployment across traditional infrastructure and AI stacks

Ideal Use Case

SRE, platform, and DevOps teams at enterprises drowning in alerts from Datadog-class monitoring — and AI engineering teams that now also have to keep models and agents reliable in production. InsightFinder sits on top of existing telemetry, correlates it, and shifts the team from reacting to incidents to preventing them.

How InsightFinder differentiates

Most AIOps tools cluster alerts after something breaks. InsightFinder's research pedigree shows in the prediction claim — up to six hours of advance warning, from unsupervised models that do not need labeled training data — and in the unusual coverage of AI-system reliability (drift, LLM behavior) alongside classic infrastructure. A $15M Series B in April 2026 (Yu Galaxy, with Comcast NBCUniversal LIFT Labs and Eight Roads; $31M total raised) and Fortune 500 logos back the credibility.

FAQ

What is InsightFinder? An AI-driven reliability (AIOps) platform that uses unsupervised machine learning to detect anomalies, diagnose root causes, and predict IT and AI-system incidents up to 6 hours before impact.

How much does InsightFinder cost? Published pricing starts at $2.50 per core per month with a $250/month minimum, plus custom enterprise pricing. There is a 30-day free trial and a free sandbox.

Does it monitor AI models as well as infrastructure? Yes — model drift detection, LLM/agent reliability, and root-cause analysis for production AI workloads are first-class features.

Who uses InsightFinder? SREs, platform teams, and AI engineers at enterprises including Comcast, FedEx, Dell, Visa, and TD Bank.

tl;dr

InsightFinder turns telemetry into forecasts: unsupervised ML that predicts incidents hours ahead, cuts alert noise 90%, and extends reliability engineering to production AI systems.