Decision intelligence · market and customer simulation
Simulatebefore youdecide.
Test what to build, who to sell to and which market to enter — before the decision is made.
TÜBİTAK-backed R&D · KVKK / GDPR addendum
“Who should we sell this product to in Germany?”
01Target parsingDE02Company discovery24703Pre-screening8204Web profiling2005Product match·06Live signals·07Persona simulation·08Fit analysis·09Decision briefing·Packaging manufacturer · DE-04
85 / 100 fit · contact first
Example run. Not a measured result.
412 real-world signals · 25 synthetic personas · 3 scenarios · 1 decision
Prospect discovery and simulation
From thousands of companies to the ones worth selling to.
Example run. The numbers show how a run is assembled, not a measured outcome.
Prospect discovery and simulation · example run
It works out what you sell and who you are looking for.
DE · food packaging
Country, sector vocabulary, buyer profile and the end-customer clue are parsed apart.
It finds the prospects that exist in the market.
247 companies
Real companies are found across company, sector, web and other corporate data sources.
It focuses on the strongest candidates.
82 left
Companies weakly related to your target are dropped; strong candidates go to deep analysis.
It gets to know each company more closely.
20 profiles
The website, product portfolio, field of activity and current company signals are analysed.
Does your product genuinely overlap with their business?
4 matches
The commercial fit between your portfolio and the company’s current products and activities is analysed.
Each company is read together with real-world signals.
5 sources
News, economy, foreign trade, trends and seasonality all enter the same analysis.
The end customer’s likely reaction is simulated.
25 personas
The effect of current market conditions on synthetic consumer profiles is analysed.
Each company’s sales potential is scored on several axes.
85 / 100
Firmographics, product fit, demand signal and reachability, each on its own.
The analysis turns into a sales action.
3 above threshold
Priority company, decision-maker profile, timing and a personalised message draft are delivered together.
Example run. Not a measured outcome.
Strategic questions
One engine. Five decisions.
Prospect simulation
Path to the decision
Future trend and product opportunity
Path to the decision
Portfolio expansion
Path to the decision
Demand at the end of the chain
Path to the decision
Market entry
Path to the decision
From data to simulation
Two realities. One decision.
Synthetic personas are not real people or survey respondents; they are artificial profiles built to simulate how behaviour might shift under different conditions.
Question — German food packaging, 12 months
Prototype a mono-material recyclable food packaging.
- Asian capacity could return and reset the price.
- The recyclability premium is simulated, not measured.
- Two of nine signal sources returned no data.
Example scenario. Not a measured outcome.
Weighted futures
These are scenario weights, not calibrated probabilities.
Future trends and product opportunities
From today’s signals to tomorrow’s product opportunities.
Example run. The numbers show how a run is assembled, not a measured outcome.
Future trends and product opportunities · example run
First it defines which future we are looking at.
DE · 12 months
Horizon of 3, 6, 9 or 12 months. Segment B2B, B2C or a custom definition.
It gathers hundreds of real-world signals.
412 signals
News, regulation, foreign trade, economy and technology sources are swept together while source independence is preserved.
Not the strength of the trend — the density of the evidence.
6 developments
A trend’s lifecycle stage is derived from measurable signal density over time, not from the model’s opinion.
Customs declarations, not inference.
HS 3923 · imports
Real trade data measures the direction and change of demand; periods with no data are never filled in with estimates.
Eight fundamental forces that could move demand are swept together.
8 / 8 swept
Regulation, demand, cost, competition, technology, trade policy, consumer and capital effects are weighed with both supporting and contradicting evidence.
Not a single forecast — evidence-backed possible directions.
Up · medium confidence
Every future inference shows its direction, confidence level, supporting signals, counter-evidence and the conditions that would invalidate it.
There is no single leap from signal to product.
4 opportunities
The emerging change comes first, then the need it creates and the product requirement; only opportunities your production capability supports are kept.
Personas read the product, not the news.
21 / 25 measured
The product hypothesis is tested on synthetic personas from identical starting conditions; behaviour change is measured, real purchase intent is never claimed.
The decision is built in code, not asked of the model.
Prototype · 78
The strategic call is never left to model output alone; measured evidence, simulation results and explicit decision rules are weighed together.
Example run. Not a measured outcome.
Pricing
Pricing fits your work. The credit table is public.
Pricing is shared as a quote.
Your usage volume, user count and data-residency needs set the price. One call is enough for a firm quote.
Get a quote- S1 · Decision-maker simulation
- 30 credits
- S2 · Demand simulation
- 80 credits
- Cohort generation (50 personas)
- 100 credits
- Company discovery (≈25 candidates)
- 10 credits
- Live persona daily tick
- 0 credits
- Failed run
- 0 credits
Enterprise
For decisions that carry weight.
Tenant isolation
Every record inside its own organisation.
Roles and permissions
Access is granted by capability.
Audit trail
Every run, every source on the record.
Single-tenant / on-premise
Installed on your own infrastructure.
SSO and RBAC
Your corporate identity provider.
KVKK / GDPR addendum
TR / EU data residency.
Is a synthetic persona real customer data?
No. It is a model construct; it is not a real person, not a survey respondent, and no answer ever comes from a human.
How accurate are the results?
A simulation is a scenario, not a measurement. We claim no accuracy percentage; we give you the source of every claim, its epistemic type, and what argues against the recommendation.
Where is our data held?
Every record is scoped to its own organisation. At the enterprise tier we offer TR or EU data residency, single-tenant deployment and installation on your own infrastructure.
What happens when credits run out?
You buy a credit top-up; the plan is never auto-upgraded. On a failed run the reserved credit is refunded automatically.
Before you decide in the real world,
simulate it in Personalitic.
hello@personalitic.com
Request a demo