Most behavioural data on the market is paid annotators answering questions in a sandbox. Parallel World captures the opposite. Real people on real apps, with consent and a payout at source.
Every major data supplier in the AI training and evaluation market sells the same shape of input: structured responses from paid annotators. Useful, but not what users actually do. Parallel World captures the opposite.
Parallel World captures the moments where a user actually makes a choice. Across models, across sessions, across months. The training, evaluation and reliability signal your team has been inferring indirectly.
Same person, same task, multiple AI surfaces open. Which one they pick. Why they switched.
Hesitation, regeneration, abandonment, copy-and-exit, manual takeover. The signal your evaluators currently infer.
Full browser sessions across research, checkout, support and tool-to-tool journeys. Not stitched fragments.
The same users tracked across months as your models, and the web around them, evolve. Drift becomes measurable.
Each category ships with sample records, a schema, k-anonymity thresholds, and a median record age. Partners can scope a pilot against one category or across several.
user_id_hashed · category: "Footwear / Running" · price_band: "$80-140" · competitors_viewed: 3 · intent: 0.82cohort_id · 14 sessions / 7 days · avg_duration: 4m12s · pattern: "commute"journey: "Mobile → Web → Ext" · outcome: converted · lift: +18%task_type: "research" · models_tried: [claude, chatgpt, perplexity] · chosen: claude · regenerations: 2cohort_size: 12,408 · topic: "ai-tools" · follow_rate: 6.4% · velocity: "high"The first commercial relationship is a small, dated, defined pilot. There are two shapes ready to deliver.
A consented dataset around one workflow family. Steps, tool context, outcomes, and a short taxonomy of failure points (hesitation, abandonment, correction, retry, takeover). Designed to slot directly into your evaluator calibration or judge training pipeline.
Full web sessions across research-to-decision and tool-to-tool journeys. Designed for benchmarking browser agents, measuring policy compliance, or fine-tuning agent memory and planning layers.
If you sell software that tests AI systems, builds browser or coding agents, secures runtime AI, or supplies behavioural data to the labs, Parallel World is a clean upstream source for the inputs you already need.
Every record begins with the user opting in, at the granularity of data type. Consent is auditable per record.
The user is compensated for the data you buy. No scraping. No silent collection. Cleaner than the alternative routes when procurement asks where the data came from.
Hashing, k-anonymity thresholds and differential privacy noise applied before any record leaves our infrastructure. Configurable per category.
Designed against Article 53 training data disclosure requirements. Hosted in France. Suitable for partners with European deployment exposure.
Under six hours from user activity to partner-accessible record. Continuous ingestion, not batched dumps.
REST API, Snowflake share, or S3 drop. Schema versioned. Webhook events for ingestion-rate partners.
Pilots scoped to a single category and a fixed volume. Production access opens against signed LOI with a named contract.
Chrome extension live across the major LLM surfaces. Android mobile in build. iOS in evaluation. First partner pilots scoping for Q3 2026 delivery.
Founders and operators with category-defining track records in consumer products, AI infrastructure, regulated finance and digital assets.





Tell us what you're testing, training or evaluating. We'll come back with a scoped pilot shape and a sample slice within 48 hours.