Help founders manage product bets like a gambler — portfolio + experiment analytics

Help founders manage product bets like a gambler — portfolio + experiment analytics targets a $8.0B = 4M product-led SMBs and startups × $2K ACV average for product decision tooling total addressable market with medium saturation and a year-over-year growth rate of 15% CAGR (industry estimates for product analytics + experimentation adoption from market research firms like Gartner/Forrester).

Key trends driving demand: Continuous experimentation is becoming standard practice — as teams adopt A/B testing and feature flags, they need higher-level tools to prioritize and manage many parallel experiments.; AI-assisted decision support is maturing — models can now infer likely lifts from small-sample signals, enabling probabilistic prioritization for early-stage bets.; Product-led growth has expanded to SMBs — smaller teams want lighter-weight, cheaper tools that provide enterprise-grade insights without heavy setup.; Data instrumentation costs are falling — cheaper analytics pipelines and serverless infra lower the friction to run experiments and centralize results, creating demand for portfolio analysis..