# Overview: Companies
Source: https://docs.inop.ai/api-reference/companies/overview

v0.0.1

<Note>
  If you're not looking to build API reference, you can export datasets directly from the dashboard.
</Note>

## Overview

Provides detailed company information, including:

* Basic company data (name, size, industry, location).
* Culture scores & diversity insights.
* ESG (Environmental, Social, Governance) ratings.
* Awards & recognitions.
* Company mission, vision, and values.

#### Example Response

```json
{
  "company_id": "comp_56789",
  "name": "INOP Tech",
  "industry": "Technology",
  "size": "500-1000 employees",
  "culture_score": 88,
  "esg_rating": "A+",
  "awards": ["Best AI Employer 2024"],
  "mission": "Innovating talent intelligence through AI-driven insights."
}

```


# Overview: Compensation Analytics API
Source: https://docs.inop.ai/api-reference/compensations/overview

v1.0.0

<Note>
  If you need any help or would like more information, please feel free to reach out to our support team.
</Note>

## Overview

The **Compensation Analytics API** provides comprehensive, real-time compensation data for strategic job benchmarking and market analysis. Our robust dataset is sourced from verified job postings and compensation data across multiple industries and geographic regions.

### Key Features

* **Real-time Data**: Access to current compensation trends and market rates
* **Comprehensive Filtering**: Filter by location, industry, company size, job level, skills, and more
* **Statistical Analysis**: Get median, percentile distributions, and trend analytics
* **Multi-dimensional Comparisons**: Compare across locations, companies, and market segments
* **Skills Integration**: Compensation data enriched with skills and career taxonomy information

## API Endpoints

The Compensation Analytics module consists of three specialized endpoints, each designed for specific use cases:

### 1. General Compensation Insights API

**Endpoint**: `/api/v1/compensation/insights`

Provides foundational compensation data and analytics for job benchmarking. Perfect for salary research, market analysis, and compensation planning.

**Use Cases**:

* Salary benchmarking for specific roles
* Market rate analysis
* Compensation trend research
* Budget planning for hiring
* Compliance with the [EU Pay Transparency Directive](https://ec.europa.eu/commission/presscorner/detail/en/ip_23_1651)

### 2. Compensation Location Comparison API

**Endpoint**: `/api/v1/compensation/location-comparison`

Extends the general insights with multi-location comparison capabilities. Compare compensation data across different geographic regions to understand location-based pay differentials.

**Use Cases**:

* Geographic pay equity analysis
* Remote work compensation adjustments
* Multi-location hiring strategies
* Cost of living compensation modeling

### 3. Compensation Company Benchmark Tool API

**Endpoint**: `/api/v1/compensation/company-benchmark`

Provides company-specific compensation benchmarking against market competitors. Compare your organization's compensation packages with similar companies in your industry and size category.

**Use Cases**:

* Competitive compensation analysis
* Retention strategy development
* Market positioning assessment
* Executive compensation benchmarking

## Available Filters

All endpoints support comprehensive filtering options:

### Core Filters

* **Location**: Country, city, region, remote work options
* **Industry/Career Area**: Technology, Finance, Healthcare, Marketing, etc.
* **Company Size**: Micro (1-10), Small (11-50), Small-Medium (51-200), Medium (201-500), Medium-Large (501-1000), Large (1k-5k), Enterprise (5K-10K), Mega Enterprise (10K+)
* **Job Level**: Intern, Entry, Intermediate, Mid, Mid-Senior, Senior, Executive
* **Experience Level**: 0-6 months, 1-2 years, 2-4 years, 4-8 years, 8-10 years, 10+ years

### Advanced Filters

* **Skills**: Filter by required technical and soft skills
* **Compensation Type**: Hourly, daily, weekly, monthly, annual
* **Currency**: Multiple currency support with conversion
* **Time Range**: Filter by year and quarter
* **Company Type**: Public, private, startup, non-profit
* **Employment Type**: Full-time, part-time, contract, freelance

## Data Sources & Quality

Our compensation data is sourced from:

* Verified job postings from major job boards
* User-reported salaries
* Publicly available salary data
* Market research and salary surveys
* Government labor statistics
* Professional networking platforms

All data undergoes quality validation including outlier detection and source verification to ensure accuracy and reliability.

## Response Data Structure

### Core Compensation Metrics

```json
{
  "compensation": {
    "base_salary": {
      "min": 120000,
      "max": 180000,
      "median": 150000,
      "percentile_25": 135000,
      "percentile_75": 165000,
      "currency": "USD"
    },
    "total_compensation": {
      "min": 140000,
      "max": 220000,
      "median": 185000,
      "percentile_25": 160000,
      "percentile_75": 200000,
      "currency": "USD"
    },
    "additional_compensation": {
      "bonus": {
        "min": 5000,
        "max": 25000,
        "median": 15000
      },
      "equity": {
        "offered": true,
        "percentage_offering": 85
      }
    }
  }
}
```

### Position & Skills Information

```json
{
  "position": {
    "id": "550e8400-e29b-41d4-a716-446655440000",
    "name": "Senior Software Engineer",
    "short_title": "Sr. Software Engineer",
    "category": "Engineering",
    "career_area": "Technology",
    "position_group": "Software Development",
    "level": "Senior",
    "is_trending": true,
    "similar_positions": [
      "Senior Developer",
      "Senior Backend Engineer",
      "Senior Full Stack Engineer"
    ]
  },
  "skills": [
    {
      "name": "Python",
      "category": "Programming Languages",
      "relevance": "high",
      "market_demand": 95
    },
    {
      "name": "AWS",
      "category": "Cloud Platforms",
      "relevance": "high",
      "market_demand": 88
    }
  ]
}
```

### Location & Company Context

```json
{
  "location": {
    "city": "San Francisco",
    "state": "California",
    "country": "United States",
    "region": "Bay Area",
    "remote_friendly": true,
    "cost_of_living_index": 1.85
  },
  "company": {
    "size_category": "Enterprise",
    "industry": "Technology",
    "type": "Public",
    "employee_count_range": "1000-5000"
  },
  "market_context": {
    "sample_size": 245,
    "data_freshness": "2024-Q3",
    "confidence_level": 95,
    "market_trend": "increasing"
  }
}
```

## Getting Started

To begin using the Compensation Analytics API:

1. **Authentication**: Obtain your API key from the dashboard
2. **Choose Endpoint**: Select the appropriate endpoint based on your use case
3. **Set Parameters**: Configure your filters and comparison parameters
4. **Make Request**: Send your API request with proper headers
5. **Analyze Data**: Process the comprehensive compensation insights

<Tip>
  Start with the General Compensation Insights API to understand the base data structure, then explore the specialized comparison endpoints for more advanced analysis.
</Tip>

For detailed endpoint documentation, parameter specifications, and code examples, refer to the individual endpoint documentation pages.


# Authentication
Source: https://docs.inop.ai/api-reference/getting-started/authentication

Use the INOP Hire dashboard to get your API key.

<Note>
  If you're not looking to build API reference, you can export dataset directly from the dashboard.
</Note>

1. Login in to your [INOP Hire](https://client.inop.ai) account.

2. Click on the bottom left to go to profile settings

3. Click generate API key button under API Credentials tab.

## Using the API Key

Once you have generated your API key, you need to include it in the header of each API request. The API key is passed in the header using the following format:

```
x-api-key: YOUR_API_KEY
```

### Example Request

Here is an example of how to include the API key in a cURL request:

```
curl -X GET https://public.api.inop.ai/talents \
-H "x-api-key: YOUR_API_KEY"
```

#### Header Details

* Header Name: x-api-key

* Header Value: YOUR\_API\_KEY Replace YOUR\_API\_KEY with the actual API key you generated from the client portal.

#### Error Handling

If your API key is missing, invalid, or expired, the API will respond with an error. Below are common HTTP status codes related to authentication:

* 401 Unauthorized: The request was made without a valid API key or the key was incorrect.
* 403 Forbidden: The API key does not have the necessary permissions to access the requested resource.

##### Example Error Response

```json
{
  "status": false,
  "message": "Unauthorized: API key is missing or invalid."
}
```


# Introduction
Source: https://docs.inop.ai/api-reference/introduction



**INOP Workforce Intelligence API**, a powerful AI-driven platform designed to **redefine talent screening, workforce planning, and professional development**. This API allows you to **generate a custom candidate screening profile** by analyzing a candidate’s profile against job descriptions, retrieve **existing applications and AI-driven screening recommendations**, and leverage **compensation analytics, skills intelligence, and career development insights**.

Traditional hiring and workforce planning often rely on **resumes, manual screening, and static job descriptions**, which fail to capture the true potential of candidates or anticipate future talent needs. INOP’s API moves beyond these limitations by offering **intelligent, data-driven recommendations** for hiring, compensation, upskilling, and career growth.

## Base URL

```

https://public.api.inop.ai

```

## Overview

#### 1. Holistic AI-Powered Talent Screening

* Provide a candidate profile and a job description to receive a custom screening profile tailored for the role.
* Get an **AI-generated analysis** of candidate suitability based on Technical and Soft skills, Values and Cultural fit.

#### 2. Compensation Analytics

* Access **real-time global salary data** for benchmarking.
* Compare **industry-standard compensation** based on:
  * Job title, Location, Industry

#### 3. Workforce & Skills Gap Intelligence

* Identify skills gaps at:
  * **Individual level** (for upskilling & training)
  * **Department/Team level** (for project-based hiring)
  * **Organizational level** (for strategic workforce planning)
* Recommend **internal talent mobility** based on future skills demand.

#### 4. Leverage INOP’s Custom Taxonomies. INOP provides structured taxonomies for:

* **Skills** (e.g., Python, Machine Learning, Leadership)
* **Job Titles** (e.g., Software Engineer, Data Scientist)
* **Core Values** (e.g., Integrity, Adaptability)
* **Personality Traits** (e.g., Analytical, Collaborative)
* **Culture Types** (e.g., Support Culture, Result Culture, Caring Culture)

#### 5. Professional Development & Career Pathing

* Recommend **jobs, companies, and networking opportunities** based on a candidate’s:
  * Skills, Values and Interests
* Provide career growth insights, such as:
  * Salary benchmarking
  * Company culture compatibility
  * Career path suggestions

## Data Privacy & Security

At INOP, data security and privacy are top priorities. We adhere to the **highest standards to protect client data, ensuring compliance** with **GDPR** and other relevant regulations [https://inop.ai/privacy-policy/](https://inop.ai/privacy-policy/)

## Data Storage & Processing

* **Data Storage:** All data processed via the **INOP's  API** is stored securely on **AWS infrastructure** within the **European Union**, default, ensuring compliance with **GDPR and other EU data protection laws**. However, we also offer the flexibility to store and process data in other regions based on the **client's specific policy, regulatory requirements, and system architecture**.
* **Encryption:** Data is encrypted at rest and in transit using industry-standard encryption protocols (**AES-256 for storage, TLS 1.2+ for transport**).
* **Access Controls:** We implement **strict role-based access control (RBAC)** and **audit logs to monitor and restrict data access**.

## Over-the-Air (OTA) Screening

For enterprises requiring **full data sovereignty**, **Over-the-Air (OTA) Screening** ensure that AI screens and provides match insights without **compromising data security**. Below is a breakdown of the **technical integration steps** and **security protocols** that govern OTA Screening.

### Key Benefits of INOP.ai's OTA Screening

* **AI Evolves & Screens Without Data Exposure** – Clients stay up to date while maintaining 100% data sovereignty.
* **Secure & Compliant** – All updates follow GDPR, ISO 27001, and enterprise security policies.
* **Customizable Screening** – Clients can configure automatic, manual, or air-gapped screening processes.
* **Minimal Downtime** – OTA Screening is designed for seamless integration without disrupting workflows.

Any questions? reach us at [support@inop.ai](mailto:support@inop.ai), we’ll respond within 6 hours max.


# Overview: Job Posts API
Source: https://docs.inop.ai/api-reference/job-posts/overview

v0.0.1

<Note>
  If you're not looking to build API reference, you can export datasets directly from the dashboard.
</Note>

## Overview

Fetches structured job postings with detailed metadata, including:

* Job title, description, and required skills.
* Compensation details (if available).
* Employment type (full-time, remote, contract).

#### Example Response

```json
{
  "job_id": "job_98765",
  "title": "Senior Software Engineer",
  "company": "INOP Tech",
  "location": "Remote",
  "employment_type": "Full-Time",
  "required_skills": ["Python", "Django", "Cloud Computing"],
  "salary_range": "130000 - 160000 USD",
  "posted_date": "2025-03-10"
}

```


# Get Title By ID
Source: https://docs.inop.ai/api-reference/job-titles/get

GET /titles/{id}
Get a single job title based on the ID supplied



# Get Titles
Source: https://docs.inop.ai/api-reference/job-titles/get-all

GET /titles
Returns job title from the system that the user has access to



# Normalize
Source: https://docs.inop.ai/api-reference/job-titles/normalize

POST /titles/normalize
Normalize a raw job title string to the best matching INOP title

Normalize a raw job title string to the best matching INOP title


# Overview: Job Title API
Source: https://docs.inop.ai/api-reference/job-titles/overview

v0.0.1

<Note>
  Note: By default, all clients are allowed a maximum of 5 requests per second. Contact us here if you need an adjustment
</Note>

## Overview

**INOP Job Titles API** is a powerful and structured job classification system designed to bring consistency and intelligence to job title data. This API provides access to **INOP’s comprehensive library of job titles**, complete with **normalization capabilities**, **curated job title groupings**, and **skill mappings** for each title.

Organizations often deal with inconsistent, ambiguous, or unstructured job titles in hiring processes, job postings, and workforce analytics. **Job Titles API** addresses this challenge by offering a **standardized framework** to:

* **Normalize raw job titles** – Convert unstructured job titles into standardized INOP-defined titles.
* **Group related job titles** – Access curated job title clusters for better role categorization.
* **Map job titles to required skills** – Gain insights into core and associated skills for each title.

### Access the INOP Job Titles Library

* Retrieve a comprehensive list of standardized job titles used across industries.
* Use predefined taxonomies for consistent classification.

### Normalize Raw Job Titles

* Transform **raw, unstructured, or company-specific job titles** into **INOP-defined job titles**.
* Improve data quality in **HR systems, ATS platforms, and workforce analytics**.

**Raw Title → Standardized Title**

* “Sr. Software Eng.” → Senior Software Engineer
* “Frontend Dev” → Frontend Developer
* “AI Specialist” → Machine Learning Engineer

### Retrieve Curated Job Title Groupings

* Identify **hierarchical and related job families** (e.g., Engineering, Data Science, Product).
* Enable **better career pathing and internal mobility insights**.

#### Example

* **Software Engineer falls** under the **Software Development** job family.
* **Machine Learning Engineer** is categorized under **AI & Data Science**.

### Fetch Skill Mappings for Job Titles

* Discover **essential technical & soft skills** required for each job title.
* Get **role-specific skill expectations** to aid in **hiring, training, and skills gap analysis**.

##### Example:

For **Software Engineer**, the API might return:

```json
{
  "job_title": "Software Engineer",
  "skills": {
    "primary": ["Python", "Java", "System Design"],
    "secondary": ["Cloud Computing", "DevOps"],
    "soft_skills": ["Problem-Solving", "Collaboration"]
  }
}
```


# Create Match Insights
Source: https://docs.inop.ai/api-reference/match-insights/create

POST /match-insights
Creates a new match recommendation and returns a unique match ID along with match insights data.

Creates a new match recommendation and returns a unique match ID along with match insights data.


# Get a Matched Candidate
Source: https://docs.inop.ai/api-reference/match-insights/get

GET /match-insights/{match_id}
Get a single skill based on the ID supplied



# Get All Matched Candidates
Source: https://docs.inop.ai/api-reference/match-insights/get-all

GET /match-insights?job_post_id={jobId}
Returns all candidates by job ID

Retrieves all matched candidates for a specific job post.


# Overview: Talent Screening
Source: https://docs.inop.ai/api-reference/match-insights/overview

v0.0.1

<Note>
  If you're not looking to build API reference, you can export datasets directly from the dashboard.
</Note>

## Overview

The INOP Talent Screening API goes beyond traditional resume screening by assessing candidates based on skills, values, cultural fit, and long-term success potential. The API provides endpoints for creating and retrieving match insights, enabling seamless integration with applicant tracking systems (ATS) and recruitment platforms:

* Analyze a candidate's profile against a job description.
* Retrieve existing candidates and AI-generated screening recommendation insights.
* Assess skills, values, cultural fit, and long-term success potential.


# Recommend Candidates
Source: https://docs.inop.ai/api-reference/match-insights/recommend-candidates

POST /match-insights/recommend-candidates
Generates match insights and recommendations based on a given job description and a list of potential candidates. Returns a unique match ID and corresponding recommendation insights data for each candidate.



# Get a skill by ID
Source: https://docs.inop.ai/api-reference/skills/get

GET /skills/{id}
Get a single skill based on the ID supplied



# Overview: Skills
Source: https://docs.inop.ai/api-reference/skills/overview

v0.0.1

<Note>
  If you're not looking to build API reference, you can export dataset directly from the dashboard.
</Note>

## Overview

**INOP Skills API**, a comprehensive and structured skills taxonomy designed to support **skills-based hiring, workforce planning, and talent intelligence**. This API provides access to **INOP’s complete collection of skills**, each uniquely identified and categorized by skill type.

Organizations often struggle with **inconsistent skill definitions** and **unstructured skill data** when evaluating candidates, employees, or job descriptions. INOP Skills API standardizes skill classification, making it easier to integrate **AI-powered skill intelligence** into your hiring and workforce management processes.

For additional details about INOP’s skills taxonomy, reach us at [support@inop.ai](mailto:support@inop.ai)

### Retrieve Complete Skills Collection

* Access a **comprehensive list of skills** across multiple domains, including:
  * **Technical Skills** (e.g., Python, Machine Learning, Cloud Computing)
  * **Transferable Skills** (e.g., Adaptive design, Ad hoc Testing, Agile Methodology)
  * **Soft Skills** (e.g., Leadership, Adaptability, Critical Thinking)
  * **Industry-Specific Skills** (e.g., Financial Modeling, Legal Compliance)

### Fetch Skill Metadata & Classification

* Each skill entry includes:
  * **Unique Skill Identifier** (UUID) for precise referencing
  * **Skill Name** (standardized naming convention)
  * **Skill Type** (e.g., technical, soft, industry-specific)

##### Example Response

```json
{
  "skills": [
    {
      "id": "123e4567-e89b-12d3-a456-426614174000",
      "name": "Machine Learning",
      "type": "Technical"
    },
    {
      "id": "223e4567-e89b-12d3-a456-426614174001",
      "name": "Leadership",
      "type": "Soft Skill"
    }
  ]
}

```


# Find related skills
Source: https://docs.inop.ai/api-reference/skills/related

POST /skills/related
Returns a list of skills that are related to the requested skills



# Overview: Talent Sourcing API
Source: https://docs.inop.ai/api-reference/talents/overview

v0.0.1

<Note>
  If you're not looking to build API reference, you can export datasets directly from the dashboard.
</Note>

## Overview

Provides structured professional data, including:

* Basic professional details (name, role, experience level).
* Education history & work experience.
* Skills, values, and cultural preferences.

##### Example Response

```json
{
  "professional_id": "prof_12345",
  "name": "Jane Doe",
  "current_role": "Software Engineer",
  "education": [
    {"degree": "B.Sc Computer Science", "institution": "MIT", "year": "2018"}
  ],
  "work_experience": [
    {"company": "TechCorp", "role": "Backend Engineer", "years": 3}
  ],
  "skills": ["Python", "Django", "Microservices"],
  "values": ["Innovation", "Collaboration"]
}


```