Mind of People · Outcome Machines for Movements 🌞

Drive the outcome.
Move the people.

The Outcome Machine for societal movements.

Mind of People plugs into the ad accounts, CRM, donor platforms, field tools, and surrogate playbooks you already pay for — and runs a closed loop on every dollar you spend until the number you own moves the way you need.

Own one number →
  • Vote share
  • Turnout
  • Donations
  • Approval
  • Sentiment
  • Volunteer signups

Mind of People runs on DatacentrIQ (Driver) and SimPopuli (Predictor). Use responsibly.

01 / Two Modes, One Platform

One platform. Two modes.

Start with Driver — immediate ROI on every campaign dollar you already spend. Level up with Predictor — agent-based simulation that sees further than next week.

Driver · DatacentrIQ

Make every dollar earn its outcome.

Wires into the campaign systems you already run — ad accounts, CRM, donor DB, field tools, surrogate scripts. Owns one metric — vote share, turnout, donation rate, approval — and optimizes every dollar until it moves. ROI on day one.

  • Ad platforms
  • CRM
  • Donor systems
  • Field tools
  • Surrogate ops
Explore Driver →
Predictor · SimPopuli

See the future before you ship.

Advanced agent-based simulation of your electorate. Test message arcs, score influence cascades, model backlash, look weeks ahead. The polling replacement — built into the same platform that drives your spend.

  • Message arcs
  • Scenario sim
  • Backlash modeling
  • Long-arc forecasting
Explore Predictor →

First vertical: Campaign Operations. More verticals on the roadmap.

02 / Driver · DatacentrIQ

Own the number.
Drive it.

Driver runs a closed loop on every campaign dollar — monitoring, explaining, recommending, executing, and learning — until the number you own moves the way you need.

  1. 01 — Monitor

    Track the metric you own.

    Vote intent, sentiment, turnout, donor flow — in near real time, fed by polls, social, news, and field data.

  2. 02 — Explain

    Know why it moved.

    Agent-based causal simulation surfaces which message, event, demographic shift, or influencer cascade actually shifted the number.

  3. 03 — Recommend

    Rank what to do next.

    Message arcs, channels, timing, spokespeople, micro-targeting — ranked by simulated lift on the metric you own.

  4. 04 — Execute

    Push the playbook.

    Ad creative, organizer scripts, SMS / email sequences, surrogate briefings — into your campaign stack, with human approval at every step.

  5. 05 — Learn

    Sharpen the twin.

    Realized lift feeds back into SimPopuli. The model recalibrates. Your next run starts smarter.

Plugs into the stack you already pay for
  • Ad platforms
  • CRM
  • Donor systems
  • Field tools
  • Surrogate ops
  • + your sources
Always on

The loop never stops scanning.

Driver watches the metric you own from every angle, every minute. Monitor. Explain. Recommend. Execute. Learn. Repeat — until the number moves the way you need.

  • 01 — Monitor
  • 02 — Explain
  • 03 — Recommend
  • 04 — Execute
  • 05 — Learn
03 / Predictor · SimPopuli

A living twin
of the people you move.

SimPopuli powers Predictor mode — a living, agent-based digital twin of the constituency, electorate, or movement you're trying to move. The polling replacement for campaigns who need to see further than next week.

Built from aggregated, anonymized, publicly available data. Never PII. Always auditable.

1M+
simulated agents per run
alternative futures
0
personal records used
SIMPOPULI
04 / Beyond the Polls

Beyond the Polls.

Traditional election polls offer snapshots of public opinion, capturing voters' preferences at specific moments. However, these methods often struggle to account for the dynamic and complex nature of voter behavior, especially in an era of rapid information dissemination and shifting societal norms.

Mind of People transcends these limitations by employing advanced agent-based modeling to simulate and predict the evolution of public sentiment over time.

Agent-based · time-aware modeling
05 / Predictor vs Traditional Polling

Predictor vs
Traditional Polling.

Traditional
Predictor
Category
Traditional
Predictor
Sampling Method
Small, manually curated samples via phone, SMS, or online panels
Full-spectrum, agent-based simulations of entire populations using demographic & behavioral data
Speed
Days to weeks to collect, clean, and analyze responses
Near real-time insights using pre-built population models and instant scenario simulation
Cost
High per poll; especially expensive for national or multilingual campaigns
Initial build cost for AI, but low marginal cost for unlimited scenarios
Bias & Error Sources
Susceptible to self-selection, social desirability, and demographic non-response
No self-reporting; behaviors emerge naturally through rules and interaction dynamics
Scenario Testing
Limited to "if you voted today…" or single variable hypotheticals
Can simulate cascading effects of complex, multi-factor campaign strategies or policy changes
Behavior Modeling
Measures stated intent, not real behavior
Models actual behaviors, influence chains, and cultural dynamics recursively
Temporal Scope
Static snapshots of opinion
Evolving, time-aware modeling across days, weeks, or election cycles
Accuracy
Limited by sampling error and polling screens (e.g., likely voters)
Accuracy improves over time via recursive model tuning and agent learning
Adaptability
Must be rebuilt or re-polled to assess new questions
Easily run new simulations with modified parameters, campaigns, or shocks
Strategic Insights
Provides current sentiment, but hard to predict downstream effects
Reveals tipping points, backlash dynamics, long-tail influence effects, and movement spread
Best Use Cases
Tracking popularity, testing simple messages
Designing entire campaign strategy, messaging arcs, and voter mobilization paths
Granularity
Often generalized across states, regions, or large demos
Highly granular—can simulate small segments, niche populations, or hyperlocal dynamics
Message Testing
Can test individual messages via surveys
Can simulate the long-tail impact of message arcs over time—narratives, cascading influence, backlash
Real-Time Adaptability
Static once collected; new polls must be fielded to reflect changes
Can ingest fresh data and run new simulations in near-real-time
Privacy Risk
Collects personally identifiable data if not handled carefully
Uses agent-based models and synthetic populations—no need for tracking individual identities
Emotional Response Capture
Usually misses emotional or unconscious drivers
Can model emotional response dynamics (fear, hope, identity alignment) across agents and networks
Ethical Design
Depends on the firm and sponsor; can be used manipulatively or transparently
Designed to be privacy-first and scenario-based, ethical use depends on user intention and transparency
Predictive Power
Polls predict short-term preferences
Predictor simulates trajectories, not just moments, forecasting how opinions evolve and spread
Reusability
Data is historical and must be re-collected each time
Simulation models can be refined and reused for multiple scenarios, elections, or message environments
06 / Ethical Usage of Mind of People

Ethical Usage of Mind of People.

  1. 01

    Privacy-First by Design

    Mind of People does not require or use personally identifiable information (PII). Instead, it operates on synthetic populations constructed from aggregated, anonymized, and publicly available data.

  2. 02

    Transparency of Purpose

    All uses of Mind of People should be declared openly: Who is running simulations, What scenarios are being tested, How results will be used.

  3. 03

    Beneficial Use Only

    Mind of People is designed to help understand and empower human systems, not to deceive or exploit them.

  4. 04

    Explainability and Auditability

    Models and outputs must be explainable to the stakeholders they affect, whether voters, customers, or citizens.

  5. 05

    No Use for Coercion or Surveillance

    Mind of People must never be used for authoritarian surveillance, predictive policing, or suppression of dissent.

  6. 06

    Equity in Representation

    Simulation inputs must reflect the diversity and complexity of real populations.

  7. 07

    Stewardship of Influence

    Mind of People grants its users an unprecedented ability to model cascading influence and collective behavior.

Mind of People is not just a tool to predict what people will do.
It's a tool to help you do right by them.

Mind of People
🌐 Driver · Predictor · Ethical

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