About Humantic AI

Humantic AI is a pioneer in the field of predictive behavioral assessment. It combines Machine Learning & AI with Social & IO Psychology, Computational Linguistics, and Psycholinguistics to predict human behavior and personality with industry-grade accuracy, thereby creating one of the most powerful cross-domain applied research systems in the world.

It combines 25+-year-old research done by Prof. James Pennebaker (UT Austin) which establishes strong correlations between linguistics and personality, with work done by Dr. Michal Kosinski (Stanford University) et all establishing correlations between social activity and behavior. It applies a combination of these approaches via a novel 'data recycling' technique to already available data and predicts the behavior, personality, and decision-making style of any individual in less than 15 seconds without requiring the individual to take a test.

Humantic AI currently serves Fortune 500 organizations like Paypal, Caterpillar, and Cognizant. The Wall St. Journal has termed Humantic AI the technology that will reshape the world, Harvard Business Review has written about its global impact and users love what it can do for them.

Beyond providing a psychometric assessment on 16 attributes which include DISC and Big Five, Humantic AI also provides powerful advanced personalization advice for two 'personas' - sales and talent assessment.

Humantic AI For Sales
Humantic AI helps sales teams understand prospects in a manner that wasn't possible earlier. Using Humantic AI's cutting-edge behavior prediction AI, salespeople can know how fast a prospect would make decisions, what factors would sway their decision, what messaging will make them buy from you and what wouldn't, without having to indulge in tedious research every time.

Humantic AI For Talent Assessment
Humantic AI allows Talent Acquisition and People Analytics teams to understand the candidate's/employee's personality and culture fit without requiring them to take a test. It allows organizations to engage talent better via personalized outreach, assess them better via no-test predictive assessments, and analyze better via its talent analytics suite.

Humantic AI API Customers

Humantic AI APIs

Humantic AI APIs open up their cutting edge predictive psychometric analytics to a wide variety of applications that help understand their customers better to provide personalization at scale. The APIs provide a reverse-constructed profile for any individual based on the user's LinkedIn ID, resume, or other authored text.

Humantic AI profile attributes include demographics, socio-digital activity, personality, behavioral factors, interests, and use-case specific 'personas' that include communication advice for various business scenarios. In v1.0, Humantic AI supports ‘Sales’ and ‘Hiring’ personas.

All profile attributes are determined deductively and predictively from a multitude of social or other linguistic data inputs. All attributes part of the response, unless otherwise listed as beta, have an accuracy between 80-100%.

Note: In case of any queries, please contact us at connect@humantic.ai

Resource URL: https://api.humantic.ai/v1/user-profile
Create endpoint: https://api.humantic.ai/v1/user-profile/create
Fetch endpoint: https://api.humantic.ai/v1/user-profile/
Version: 1.0

Create Analysis

apikey
mandatory
Identifies the subscriber making the call to the service as each subscriber is assigned a unique key. Rate limits, identification and quota measurement are governed by this param value
userid
mandatory
User identification is provided using this param value for creating their Humantic profile.
The following are thes types of values this param can accept for creating a profile
  • LinkedIn profile URL - ‘https://www.linkedin.com/in/akhilesh-damaraju/’
  • Email ID - ‘akhilesh@frrole.com’
  • Resume Document
For LinkedIn profile URL, social profile URL and email id based analysis creation
  • Http Method: GET
  • ‘userid’ param value must be the profile URLs or email id of the user.
For resume based analysis
  • Http Method: POST
  • ‘userid’ param should be a unique string. We recommend taking the file hash as the value for param.
  • Only PDF and DOCX format of resume files are supported.
  • The resume file is uploaded in the body of the request, with the key name ‘resume’ and the file as its value.

Request Body:
Type: Form-Data

Body Param:
Key: resume,
Value: <resume_file>

Fetch Analysis

apikey
mandatory
Identifies the subscriber making the call to the service as each subscriber is assigned a unique key. Rate limits, identification and quota measurement are governed by this param value
userid
mandatory
This value is the same as the userid param that is provided when the analysis is created.
persona
optional
This param is used to fetch the Humantic profile of the user for a particular persona type. Multiple persona values can be supported using comma as a delimiter.
Possible Values: sales, hiring

Update Analysis

Currently for profiles created using LinkedIn profile, Humantic supports the ability to add more data to improve the confidence of the prediction.
More data can be either additional text (can be blog, article or post) written by the user or their resume document.

URL to update the analysis is the same as create analysis.
Http Method: POST

apikey
mandatory
Identifies the subscriber making the call to the service as each subscriber is assigned a unique key. Rate limits, identification and quota measurement are governed by this param value
userid
mandatory
Use the same userid used for creating the analysis.

For adding additional text written by the user
Use form-data in the body of the request to add more text


Request Body:
Type: Form-Data

Body Param:
Key: text,
Value: <text by the user>


For uploading resume of user

Request Body:
Type: Form-Data

Body Param:
Key: resume,
Value: <resume_file>


Note: Once the data is successfully uploaded, the analysis state will be changed to ‘processing’. Once it's successfully processed, you can use the fetch API to retrieve the analysis with improved confidence.

Response Structure

first_name
First name of the user.
last_name
Last name of the user.
work_history
The employment history of a user lists out the name of the companies where the user has worked and respective tenures.
photos
Lists out the URLs of the user's photos available on various public social platforms
social_profiles
Social profile details (profile type, URL of the profile, no of followers, etc) of a user.
last_modified
Specifies the last date when the information was fetched for this profile
education
Provides a detailed breakdown of the user's education history- lists out the name of the school, colleges or institutes from where the user has pursued his/her education, with respective tenure.
metadata
’Confidence’: Provides the confidence score with which the system is predicting the scores.
Any profile with confidence score less than 40% will not have any scores, as the social data available for the particular is not enough to compute the scores.
user_name
Social user name
user_id
Social user id
display_name
Name provided on social profile
user_description
Description provided on social profile
user_profile_image
Profile image provided on social profile
social_activity
Social activity: Detailed analysis of the social post patterns and social profile of the user

’Total social posts’: Total social posts by the user in the given period

’User authority’: A metric that provides a measure of the influence that a user has on social media. It takes into account their social posts volumes, reach, the reach of their followers, how widely appreciated and shared their social posts are, the originality of the content they share, etc. It is a scale from 1-10 with 10 being the users with the highest influence.

’Social repost count’: Number of times the user has been reposted

’Original social posts count’: Number of original social posts put out by the user

’Followers’: Number of handles that follow the user

’Favorite count’: Number of times the user has been favorited

’Following’: Number of handles the user follows

’Follower growth’: Daywise growth of followers for the past month and monthwise before that up to the date the analysis was first done on the user.

Note: This attribute is populated when the analysis is created using a social handle
personality_analysis
An in-depth look into the personality of the user:

DISC Assessment

’Dominance’: Dominance reflects how goal and task-oriented a person is and her ability to accomplish results, irrespective of how demanding the circumstances might be. Those scoring high tend to be motivated by winning, competition and success and can be described as direct, demanding and strong-willed.

’Influence’: Influence reflects the degree to which a person prefers to work by influencing or persuading others. Those scoring high tend to be people-oriented, are motivated by social recognition and building relationships and can be described as warm and enthusiastic in general

’Steadiness’: Steadiness reflects the degree to which a person is likely to focus on cooperation, support and taking everyone along. Those scoring high tend to be consistent and calm, are excited about the opportunity to collaborate and partner and could sometimes be indecisive or overly accommodating

’Calculativeness’: Calculativeness reflects the degree to which a person is likely to be cautious, systematic and analytical. Those scoring high tend to emphasize quality and accuracy, enjoy showing off their expertise or challenging assumptions but can sometimes overanalyze things and be overcritical.

Possible values for DISC
  • Very Low
  • Low
  • Medium
  • High
  • Very High

Ocean Assessment

’Openness’: Openness reflects the degree of intellectual curiosity, a desire to seek new experiences and a preference for novelty and variety. Those scoring high tend to be inventive, curious and open to trying new things whereas those scoring low tend to be consistent, cautious and more realistic in their approach.

’Conscientiousness’: Conscientiousness reflects the degree of self-discipline, focussing on doing things in a planned manner and acting dutifully. Those scoring high are usually efficient, organized and focused whereas those scoring low tend to be easy-going, spontaneous and unreliable at times.

’Extraversion’: Extraversion reflects the degree of assertiveness and sociability that an individual exhibits. People scoring high on extraversion tend to be outgoing, energetic and talkative whereas those scoring tend to be reserved, quiet and thoughtful, especially in social settings.

’Agreeableness’: Agreeableness reflects the degree of compassion, cooperation and general friendliness in a person. Those scoring high are mostly even-tempered, pleasant and easy to convince whereas those scoring low tend to challenge and question things and are likely to have a contrarian attitude.

’Emotional Stability’: Emotional Stability refers to the degree to which one can experience unpleasant emotions like anger, anxiety, etc. easily. Those scoring high tend to be calm, stable and are not perturbed easily whereas those scoring low can be passionate, excitable and have low impulse control, especially under stressful circumstances. (Emotional Stability is same as Neuroticism rated on a reverse scale)

Possible values
O Very Closed Closed Somewhat Open Open Very Open
C Very Easygoing Easygoing Somewhat Conscientious Conscientious Very Conscientious
E Very Introverted Introverted Somewhat Introverted Extroverted Very Extroverted
A Very Disagreeable Disagreeable Somewhat Agreeable Agreeable Very Agreeable
EA (N) Very Sensitive Sensitive Somewhat Balanced Balanced Very Balanced
interests
Find out what the user finds interesting on social media:

’Interest’: The area the user is interested

’Count’: Number of entities within the interest area the user follows

’Share’: The Percentage share of this area among the total interests of the user

’Sub Interests’: Subarea within the interest

’Names’: Individual names of entities the user is interested in

Note: This attribute is populated when the analysis is created using a social handle
content_affinity
Find what kinds of content the user shares the most:

’Vocab’: This provides a detailed breakout of various parts of speech the user uses and the relative counts. It provides interjection, discrepancy word, preposition, adjective, verb, adverb, determiner, noun and pronoun counts for the user.

’Entity types’: Provides relative counts of types of entities that the user references most often and instances of each e.g., entity type: 'politician' and entity: 'Barack Obama'. For each entity type, the qualified entities contain instances of the type and also contain count, sentiment and percentage share of the entity within that type.

’Other topics’: Provides counts for other topics the user mentions most often with the count and sentiment numbers for each.

’Categories’: Provides relative counts of categories that the user references most often and sentiment associated with each. For each category, the entities contain the topics mentioned within the category and also contain count, sentiment and percentage share of the topic within that category.

Note: This attribute is populated when the analysis is created using a social handle
demographics
Provides a detailed demographic breakdown of the user including gender, employment status, parental status, marital status, profession and location.

Note: This attribute is populated when the analysis is created using a social handle
tech_usage
Provides a breakdown of apps used by the user as well as the devices owned and the number of instances they were used.

Note: This attribute is populated when the analysis is created using a social handle
social_interactions
Provides other social users that the user interacts with, the count of the interactions and the sentiment associated.

Note: This attribute is populated when the analysis is created using a social handle
persona

Based on the value provided for ‘persona’ in the fetch API call i.e hiring or sales, the value of the attribute is set.

For both ‘hiring’ and ‘sales’ personas, communication advice is provided tuned for the context. ‘communication_advice’ is an object type and has the following attributes

‘Description’: The value describes the user analyzed. For each persona, the description is tuned to fit the persona context

‘Adjectives’: Provides 3 adjectives that describe the user.

‘What to avoid’: For each persona, the response will be tuned to indicate what to avoid while communicating with the user to improve professional relationship

‘What to say’: For each persona, the response will be tuned to indicate what to say while communicating with the user to improve professional relationship.

For ‘hiring’ persona the response will have an attribute called “behavioural_factors“ that provides traits of the user that will be helpful while evaluating the candidate.

  • Teamwork skills Teamwork skills indicate how well a person can work in a team setting and if that person can prioritize the team's interests over her own interests. People scoring high tend to be better team players than those scoring low on a scale of 1 to 10, with 1 being the lowest.
  • Need for autonomy Need for autonomy indicates a person’s work style and how much independence she would expect in her role. High Scorers tend to prefer low oversight whereas low scorers are ok with more oversight or involvement by superiors.on a scale of 1 to 10, with 1 being the lowest.
  • Attitude and outlook Attitude and outlook reflect how one is likely to approach different scenarios and circumstances. People scoring high tend to be more optimistic whereas people scoring low tend to be contrarians or sometimes outright pessimistic. On a scale of 1 to 10, with 1 being the lowest.
  • Stability potential Stability Potential showcases how steady a person would be in a given role and how well she would adjust to the needs of the role. High scorers are likely to stay longer in a given role or company whereas low scorers are likely to hop jobs and roles more actively.on a scale of 1 to 10. 1 being the lowest.
  • General behavior General behavior indicates how a person is likely to conduct herself in a workplace environment. People scoring high tend to be more well behaved and thoughtful about their actions compared to people scoring low who might be more instinctive or otherwise pay less attention to how their actions would be perceived on a scale of 1 to 10, with 1 being the lowest
  • Action orientedness Action Orientedness indicates a person’s decisiveness and her capability in being goal-focused and delivering outcomes irrespective of the challenges in her way. Those scoring high tend to be highly goal and output focused whereas those scoring low do not exhibit as strong a sense of 'ends over means'.On a scale of 1 to 10, with 1 being the lowest
  • Learning ability Learning ability reflects the degree of a person’s curiosity and how much she can learn voluntarily, when prompted by others or when the circumstances so demand. Those scoring high tend to be better learners compared to those scoring low.

For ‘sales’ persona The response will have an attribute called ‘key_traits’’ that provides the prospect’s buying traits relevant during the sales process

  • Risk appetite Tells how likely the prospect takes risk for trying out new solutions
  • Decision drivers Tells what does the prospect consider while making a buy decision
  • Speed Tells how quickly the user is going to make the buy call
  • Ability to say No Tells about the user, if they can say ‘no’

related_entities
Provides a list of the various topics that the given user has conversed about.

’Count’: No. of times a particular topic/user has been mentioned

’Share’: share of voice for a particular topic or user mention

’user_mention/topic’: name of the topic or social handle of the mention

’negative_sentiment’: percentage of negative sentiment towards this topic/user mention

’positive_sentiment’: percentage of positive sentiment towards this topic/user mention

’neutral_sentiment’: percentage of neutral sentiment towards this topic/user mention

Note: This attribute is populated when the analysis is created using a social handle
languages
Lists out the languages used by this user in various postcode: code for a particular language, for ex: en, fr etc.

’Percent’: usage percentage of the language

’Language’: name of the language

Note: This attribute is populated when the analysis is created using a social handle
mood
Depicts the percentage values for four different moods, namely- action, anxiety, calm, depression

Note: This attribute is populated when the analysis is created using a social handle
websites
Lists out the various websites associated with the user

Quota

Developers can find the usage quota of their API key from the ‘usage_stats’ attribute. This attribute will be returned in both ‘create’ and ‘fetch’ API responses

Eg:

"usage_stats": {
    "user_profile": {
        "remaining": 498,
        "limit": 500,
        "consumed": 2,
        "info": "remaining = limit - consumed",
        "remaining_extension": 9979,
        "limit_extension": 9999,
        "consumed_extension": 20,
        "info_extension": "remaining_extension = limit_extension - consumed_extension",
        "subscription_renewal_date": "2020-09-19T06:41:10.000Z",
        "subscription_status": "active"
    }
}
                                        

Rate Limits

The current API version v1.0 supports only 1 create call per minute. API keys making continuous calls without a minimum 1 minute wait will be blocked.

The processing time for any successfully created analysis is 40 secs in API version 1.0. So the fetch calls must be scheduled after 40secs successfully creating the analysis.