SignalSea raises $42M to build a conversational analytics engine for streaming data

AI · 6 min read

SignalSea raised $42 million in Series B funding led by DataWave Capital and launched a conversational analytics engine that ingests streaming telemetry from logs, metrics, and traces. The engine allows engineers and product managers to ask natural-language questions like 'Which services see rising latency in EMEA since yesterday' and receive executable queries and visualizations.

The product includes on-prem and cloud deployment modes, differential privacy options, and model grounding to avoid hallucinations. SignalSea emphasized its ability to map natural-language queries to efficient time-series aggregations and alert rules.

Funding will be invested in scaling ingestion pipelines, tightening inference latency for real-time querying, and building integrations with popular monitoring stacks. Investors and early customers see strong demand for low-friction analytics that democratize operational insights across teams.