Shaped

Shaped is a purpose-built platform that turns raw, real-time behavioral data—clicks, views, purchases, searches—into high-performance ranking, recommendation and discovery experiences. Instead of generic vector databases or black-box SaaS, it gives product and data teams a single system to connect event streams, automatically build multi-objective models and serve ultra-low-latency, deeply-personalized results anywhere in their application.

Key features
1. Real-time behavioral understanding – ingests Kafka, Kinesis, Segment, Snowflake, BigQuery or S3 events, updates user and item embeddings within seconds and guarantees < 25 ms p99 serving latency through a Rust-based inference core.
2. Multi-objective optimization – combines multiple business goals (CTR, revenue, margin, seller diversity, freshness) in one model and lets teams weight or A/B them on the fly without retraining.
3. No-code + full-code workflows – point-and-click connectors for Shopify, Spotify, YouTube, Netflix-style UIs, plus open Python SDK and declarative YAML configs for custom feature engineering and model architectures.
4. Production-grade MLOps – automates feature stores, cold-start handling, online/offline evaluation, shadow deployments and auto-scaling Kubernetes endpoints so data scientists ship once and never babysit.
5. First-class personalization APIs – drop-in replacement for Elasticsearch, Solr or Postgres ranking; returns ordered rows, JSON or rendered widgets with explainability scores for every recommendation.
6. Enterprise security – SOC 2 Type II, single-tenant VPC, row-level access controls, PII redaction and GDPR delete endpoints.
7. Transparent pricing – usage-based on events ingested and API calls served, with a forever-free developer tier and no hidden model-training surcharges.

Shaped is used by marketplaces, retailers, social apps and media companies to increase conversion 18–35 % and cut engineering time from months to days, all without shipping internal ML infrastructure.