For data partners

Real user behaviour.
Consent at source.

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.

The difference

Commanded behaviour vs revealed behaviour.

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.

What's on the market today

Commanded data

  • Paid annotators answering questions in a sandbox
  • Synthetic scenarios reverse-engineered from product hunches
  • One-shot tasks with no follow-through
  • Sources unclear; copyright and AI Act exposure variable

What Parallel World captures

Revealed behaviour

  • Real users in real apps, on real tasks they chose
  • Side-by-side moments across Claude, ChatGPT, Gemini, Perplexity
  • Regenerate, switch, copy out, abandon. Captured cleanly
  • Consented and paid at source, with full audit trail
What's in the data

Behaviour your synthetic stack can't generate.

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.

Cross-model side-by-side

Same person, same task, multiple AI surfaces open. Which one they pick. Why they switched.

Failure moments, labelled

Hesitation, regeneration, abandonment, copy-and-exit, manual takeover. The signal your evaluators currently infer.

Real workflows end to end

Full browser sessions across research, checkout, support and tool-to-tool journeys. Not stitched fragments.

Longitudinal continuity

The same users tracked across months as your models, and the web around them, evolve. Drift becomes measurable.

Data categories at launch

Five categories. Live or imminent.

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.

01
E-commerce behaviour
Retail, DTC and marketplace journeys. Product comparisons, dwell time on price bands, intent scores.
user_id_hashed · category: "Footwear / Running" · price_band: "$80-140" · competitors_viewed: 3 · intent: 0.82
02
App usage patterns
Mobile session frequency, feature engagement, cross-app switching, time-of-day archetypes.
cohort_id · 14 sessions / 7 days · avg_duration: 4m12s · pattern: "commute"
03
Cross-platform journeys
Multi-device attribution and tool-to-tool handoff. The full path from research to choice.
journey: "Mobile → Web → Ext" · outcome: converted · lift: +18%
04
Cross-model AI use
The same user on Claude, ChatGPT, Gemini and Perplexity on the same task. Which they pick. Why they switch.
task_type: "research" · models_tried: [claude, chatgpt, perplexity] · chosen: claude · regenerations: 2
05
Engagement and discovery
Topic affinity, creator follows, content velocity, social engagement archetypes by cohort.
cohort_size: 12,408 · topic: "ai-tools" · follow_rate: 6.4% · velocity: "high"
Two ways to start

A scoped first pilot, not a marketplace pitch.

The first commercial relationship is a small, dated, defined pilot. There are two shapes ready to deliver.

Shape A

Behaviour data pack for AI testing

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.

Best fitEvaluator platforms, agent reliability teams, AI security and red-team partners.
Shape B

Browser session corpus

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.

Best fitBrowser-agent infrastructure, coding agent vendors, enterprise agent platforms.
Who this is for

The teams already buying data of roughly this shape.

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.

Eval & reliability
Judge models, eval calibration, agent trace analysis
Agent infrastructure
Browser agents, coding agents, multi-tool orchestration
Security & red-team
Behaviour-grounded scenarios, runtime policy testing
Insight & intent
MarTech holding companies, insight houses, financial services
Provenance and procurement

Built for the procurement questions you already ask.

Consented at source

Every record begins with the user opting in, at the granularity of data type. Consent is auditable per record.

Paid at source

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.

Differential privacy by default

Hashing, k-anonymity thresholds and differential privacy noise applied before any record leaves our infrastructure. Configurable per category.

EU AI Act compliant

Designed against Article 53 training data disclosure requirements. Hosted in France. Suitable for partners with European deployment exposure.

Delivery and freshness

Live ingestion. Choice of pipe.

Median record age

Under six hours from user activity to partner-accessible record. Continuous ingestion, not batched dumps.

Delivery options

REST API, Snowflake share, or S3 drop. Schema versioned. Webhook events for ingestion-rate partners.

Pilot to production

Pilots scoped to a single category and a fixed volume. Production access opens against signed LOI with a named contract.

Live today

Chrome extension live across the major LLM surfaces. Android mobile in build. iOS in evaluation. First partner pilots scoping for Q3 2026 delivery.

The team

The people behind Parallel World.

Founders and operators with category-defining track records in consumer products, AI infrastructure, regulated finance and digital assets.

Livio Bisterzo
Livio Bisterzo
Founder & CEO
Serial entrepreneur with multiple exits across consumer products, technology and sustainability. Founder of Hippeas (acquired) and Green Park Brands.
Angelo Salvetti
Angelo Salvetti
Chief Strategy Officer
25+ years building and scaling ventures in technology, telecom and entertainment. Created over US$500M in enterprise value through two exits and a Nasdaq IPO. Based in Brazil.
Andrew Morfill
Andrew Morfill
Chief Operating Officer
Senior technology and security executive in fintech, Web3 and digital assets. Former CSSO at Komainu and Global Head of Cyber Defence at Banco Santander.
Rory Anderson
Rory Anderson
Chief Marketing Officer
Experienced company builder who has scaled multiple VC-backed startups globally. Former CGO at Partanna, raised $27M and expanded internationally. Strategist across climate tech, infrastructure and finance.
Arno Frantz
Arno Frantz
Founding Consultant
Digital asset and derivatives specialist with 15+ years in quantitative trading, market structure and risk systems. Co-founder of NimbleAlpha. Deep expertise in perpetual futures, options and DeFi.
Talk to us

Book a 30-minute pilot conversation.

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.