The BehavioralOperating System

Our API enables your software to make real time decisions about people

Try it now

Used by smart people at

BallinACT House

We think human behavior data
should drive everything about your product

Most systems operate on activity data rather than behavioral understanding to make critical dating, financing, sales, funnel conversion, and many other decisions. We think you should definitely have more to go off of. 

Request

POST/v1/analyze
{
"api_profile_id": "f9f79f95-b86b-4901-9a5b-087322b22522",
"name": "John Doe",
"city": "San Francisco",
"state": "CA",
"systemData": {},
"researchQuestion": "Based on this user's transaction history, what are the primary emotional drivers behind their impulsive spending, and how can we nudge them towards better financial health?"
}

Response

200 OK124ms
{
"status": 200,
"data": {
"id": "req_f9f79f95b86b49019a5b087322b22522",
"status": "completed",
"progress": 100,
"data": {
"behavioralSummary": "Get a 360 summary of who this person is in the context of your product and/or need",
"strengths": [
"Get an intimate understanding of what this person is good at doing, receiving, implementing, reacting to."
],
"challenges": [
"Understand their challenges in a contextual way"
],
"predictions": [
"See what they are like in different scenarios as it relates to your context"
],
"recommendations": [
"Understand what specific things you can do in your product or in your strategy that would impact this person"
],
"contextualInsights": "Get a specific answer to your question"
}
}
"endpoint": "api-retrieve-results",
"method": "GET"
}

How It Works

Step 1

Research Question

Tell us your user's name, location, and what you want to know about them

POST /V1/PROFILE
{
"name": "Johnathan Thorne",
"city": "Austin",
"question": "..."
}
Step 2

Digital Footprint

We find everything about this person—from social media activity to public records

Step 3

13 Dimensions

We analyze behavioral data across 13 key dimensions

13 Dimensions
Step 4

Final Report

We answer your questions in a structured API output

Use Cases

The Decision

"What loan terms should we give this person?"

Our model evaluates behavioral risk tolerance, consistency, impulse control, and stress response to inform credit limits, repayment structure, and constraint design.

Credit Decision Output

Risk Tier

Moderate

Default Probability

18%

Key Drivers

  • High consistency under constraint
  • Low impulsive behavior
  • Loss-averse decision style

Suggested Action

Increase limit gradually / Weekly repayment cadence

Our system API Explorer v1.0

Request

POST/v1/analyze
curl -X POST https://api.generalintent.ai/v1/analyze \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "api_profile_id": "profile_8829",
    "researchQuestion": "What loan terms should we give this person?"
  }'

Response

200 OK124ms
{
"status":200,
"data":{
"id":"req_8829_credit",
"status":"completed",
"progress":100,
"data":{
"behavioralSummary":"Conservative spender with high consistency and low impulsive behavior.",
"strengths":["High consistency under constraint", "Low impulsive behavior"],,
"challenges":["Loss-averse decision style"],,
"predictions":["Risk Tier: Moderate", "Default Probability: 18%"],,
"recommendations":["Increase limit gradually", "Weekly repayment cadence"],,
"contextualInsights":"Likely to maintain repayment even under stress"
}
},
"endpoint":"api-retrieve-results",
"method":"GET"
}