Marketing measurement platform unifying attribution, mix modeling, and incrementality testing
Lifesight is a marketing measurement platform built on causal inference (PyMC, TensorFlow, PyTorch) running on GCP and AWS. The tech stack reveals a research-heavy org: the presence of Vertex AI alongside statistical libraries (PyMC, R) signals investment in productizing econometric and ML models rather than rule-based attribution. Active projects span incrementality testing, multi-touch attribution, and marketing mix modeling — the full measurement stack. Hiring velocity is decelerating while the org remains engineering-forward (7 engineering, 4 data roles open), suggesting mature product development rather than early hiring ramp.
Lifesight helps mid-market to enterprise marketers measure the true impact of marketing across online and offline channels by combining causal attribution, marketing mix modeling, and incrementality testing into a single platform. Founded in 2017 and headquartered in New York City, the company serves omnichannel brands seeking to replace fragmented attribution tools and conflicting data sources with a unified, causal view of marketing ROI. The product architecture integrates end-to-end GTM workflows alongside measurement capabilities. The company operates across the United States and India.
Core: TensorFlow, PyTorch, PyMC, R for causal inference and ML. Infrastructure: AWS, GCP, BigQuery, Kubernetes, Redis. Frontend: React, TypeScript, JavaScript. LangChain and LlamaIndex indicate recent AI experimentation.
Incrementality testing, causal attribution, marketing mix modeling, A/B experiment design, multi-touch attribution, user segmentation APIs, testing infrastructure, and an end-to-end GTM operating system.
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