Horizon · the decision engine of INO-OS
An organization that learns with every decision.
Horizon comes with a team of Thinkers that puts your decisions in front of synthetic populations before you spend, keeps what you learn in your organization’s memory, and starts the next decision smarter. Thinkers take on the busywork and amplify your judgment. People decide, and people benefit.
Follow one decision
A pet-food brand, one loop.
Illustrative example
- New question · Monday
A signal becomes a question
The Market Thinker notices rising interest in natural dog food in the Mountain West. The team turns it into a New question: "Will pet owners in Denver pay a premium for natural food?" Nodi brings the project's memory: past price tests, what the organization learned about premium buyers, and the Identity Models that matter in the region.
New question · project "Natural line" · 3 past learnings - Simulate · Tuesday
Three prices, one population
Adults in Denver, from the United States genome. The Market Thinker puts $55, $65 and $75 a bag in front of synthetic identities from the relevant Identity Models. The credit cost is approved before the test runs.
Test · 3 alternatives × Identity Models - Analyze · Tuesday
What wins, with whom and why
The report shows $65 leading for the two Identity Models that respond, and the Customer Advocate shows why $75 loses the value-driven buyers. Every finding comes with its evidence and its limits.
One-page report · evidence and limits - Learn · Wednesday
What stays
The team chooses what to keep: the price threshold of value-driven buyers goes to the project's memory, labelled as a simulation result.
Learning saved · labelled as simulation - Decide · Wednesday
A one-page decision
The team had bet on $75. Having read the report, it decides to advance at $65 for the two Identity Models that respond. The decision, the alternatives discarded and the expected result go to the decision log.
Decision logged · expected result set - Learn · when reality arrives
Bet × simulation × reality
When the real result comes in, it is set next to the team's bet and the simulation, and the gap becomes a learning the next New question starts from.
Result vs. expected → memory
The decision engine
One sentence in. A one-page report out.
The question
"Do I launch this product, at this price, for this audience?"
The audience
A synthetic population of the right market, built from census data, personality profiles, industry studies and proprietary data.
The alternatives
Written and reviewed with you before anything is spent.
The test
A simulation with its credit cost approved up front.
The report
Advance, adjust or discard, and for whom.
A filter, not a forecast. Horizon shows what deserves investment and what should be dropped early. It does not replace studies with real people; it makes them better aimed.
Organizational memory
Everything you learn stays, at the right level.
Personal
What a person records for themselves.
Enters directlyTeam
What a team knows together, people and Thinkers.
Enters directlyEveryone
The shared memory of the whole organization.
Enters only with a Guardian's approvalSources: what people bring in, what the Market Thinker monitors, and the learnings from every simulation. Each one is proposed, reviewed and given a date to be reviewed again.
Governance, built in
People in command, by design.
Memory Guardian
An assigned role, the CEO by default. Decides what enters memory, what leaves, and which sources Thinkers may learn from.
Visibility by level
Decisions, populations and projects are private, team or organization-wide. Not even the CEO has a shortcut into what is private.
Human in command
Every Thinker answers to a person. AI spend approved before it happens, learnings approved by people, critical actions confirmed, with an audit trail.
Privacy and cost in the open
Personal data protected before any AI sees it, and the credit cost visible on every operation.
Projects
Every front of work runs its own loop.
A project copies nothing: it connects what already exists, with its own Data Room and the same governance. Agencies organize projects by client; companies by area or campaign.
The Horizon team
Your team of Thinkers is already working.
Nodi facilitates, Klima brings the market’s view, Ward speaks for your customers. You decide.
- AlmaHuman-behaviour specialistComing soon
- KlimaMarket Thinker
- NodiFacilitator
- WardCustomer Advocate
- KoraKnowledge keeperComing soon
The Horizon license
Start with the engine. Grow into the whole system.
- The full decision engine: one sentence to a one-page decision report
- A team of Thinkers: Nodi, the Market Thinker and the Customer Advocate
- 5,000 credits every month; top up from $20, purchased credits never expire
- Concept, launch, pricing, campaign and crisis tests
- Deliberation sessions and hypotheses
- Census-grounded populations: United States, Brazil, Mexico, Colombia, Peru, and more on the way
- Organizational memory with levels and Guardians
- Projects with their own Data Room
- Media analysis
Horizon Plus
$199 a month: more credits, the Board of specialist Thinkers, proprietary synthetic markets and advanced tests and simulations.
Enterprise
The complete INO-OS: proprietary populations and passion tribes, your own AI keys, and governance for the whole organization. Studies designed and run with Wortya, our specialist partner.
Talk to specialistsPartner program
Sell and implement Horizon for your clients, with the free trial as the way in.
Become a partner