The startup develops artificial intelligence observability software that utilizes unsupervised machine learning algorithms to automatically identify and diagnose IT issues by analyzing performance metrics and textual log files. This technology enables IT personnel to predict anomalies and root causes of deviations, allowing for proactive measures to minimize the impact of potential outages.
Funding
$16.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Modern IT and AI systems are increasingly complex, making it difficult to proactively identify and resolve issues like model drift, data quality problems, and infrastructure failures before they impact users. Existing monitoring tools often lack the intelligence to correlate data across diverse sources and provide actionable insights for remediation.
Solution
InsightFinder provides an AI observability and IT observability platform that uses unsupervised machine learning to automatically detect, diagnose, and predict incidents across enterprise-scale AI models, IT infrastructure, and applications. The platform's Unified Intelligence Engine (UIE) ingests log, metric, trace, and dependency graph data from various sources, applying patented anomaly detection algorithms to identify root causes and predict future incidents. By providing real-time insights and automated remediation recommendations, InsightFinder enables ITOps, DevOps, SRE, and AI/ML teams to reduce MTTD/MTTR, ensure system reliability, and optimize AI model performance.
Target Audience
The primary target audience includes ITOps, DevOps, SRE teams, data scientists, ML engineers, AI platform engineers, and Chief AI Officers responsible for maintaining the reliability and performance of complex IT and AI systems.
Features
- Real-time anomaly detection using patented unsupervised machine learning algorithms
- Automatic root cause analysis and incident prediction
- Support for log, metric, trace, and dependency graph data
- Threshold-less alerting to reduce false positives
- Unified health view across all services, applications, and infrastructure
- Automated remediation playbook creation
- Integration with leading observability platforms like Datadog, Prometheus, and Splunk
- LLM-driven Operation Co-pilot generates root cause summaries and action recommendations in natural language
- IFTracer SDK for collecting streaming prompt data (traces and spans)