Observed Signal · Apr 16, 2026 · Funding · Source: techcrunch · Impact: 2/5 · Sentiment: Neutral
InsightFinder Raises $15M for AI Observability
InsightFinder AI, an observability startup founded by Helen Gu, raised $15 million in a Series B round led by Yu Galaxy to expand its AI agent reliability products. The company, which has applied machine learning to infrastructure monitoring since 2016, launched a new offering called Autonomous Reliability Insights that combines unsupervised ML, proprietary large and small language models, predictive AI and causal inference to detect, diagnose, remediate and prevent AI model and infrastructure issues. InsightFinder counts enterprise customers including UBS, NBCUniversal, Lenovo, Dell, Google Cloud and Comcast. The company says revenue grew more than threefold in the past year, has under 30 employees, has now raised $35 million total and will use the new capital to hire its first sales and marketing staff and scale go-to-market efforts. InsightFinder positions itself against incumbents such as Grafana Labs, Datadog, Dynatrace, New Relic, Fiddler and BigPanda.
Startup funding for an AI observability provider signals investment in infrastructure for agentic AI and adds competition to the APM/observability market, but it is not industry-shifting on its own.
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Key Takeaways & Evidence Grounding
- InsightFinder AI raised $15 million in a Series B round led by Yu Galaxy.
- The company’s new product is called Autonomous Reliability Insights and targets AI agent observability.
- InsightFinder was founded by CEO Helen Gu, a computer science professor at North Carolina State University who previously worked at IBM and Google.
- Customers include UBS, NBCUniversal, Lenovo, Dell, Google Cloud and Comcast.
- InsightFinder has raised $35 million in total, reported revenue growth of over threefold in the past year, and has fewer than 30 employees.
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Revefi Unveils AI Observability for Enhanced LLM Performance
Revefi announced AI Observability and Agentic Observability capabilities to extend its platform for enterprise LLM and AI agent workflows. The new features provide benchmarking, cost attribution, traceability, and reliability metrics across multi-vendor model deployments including OpenAI, Anthropic’s Claude, Google Gemini, and Google Vertex AI. Capabilities include model benchmarking (GPT, Claude, Gemini), throughput metrics (tokens per second), failure-rate tracking, searchable activity logs capturing prompts and responses, and end-to-end attribution from user interaction through agent execution to model response. Revefi positions these features to help data, AI, and engineering teams inspect, troubleshoot, audit, and manage production AI deployments. The announcement coincides with Revefi exhibiting at the Gartner 2026 Data & Analytics Summit in Orlando (Booth 206).
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