Technical Documentation

Everything you need to integrate, implement, and optimize KBAILabs AI solutions. From quick-start guides to advanced configuration, our documentation helps you succeed.

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Quick Start

Get started with our APIs in minutes

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API Reference

Complete API documentation and endpoints

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SDKs & Tools

Libraries and tools for every platform

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Examples

Real-world implementation examples

Quick Start Guide

Authentication Setup

Get API Key

Install SDK

Choose your preferred language and install our SDK

Make First Call

Test your integration with a simple API call

# Install the Python SDK
pip install kbailabs-sdk

# Initialize the client
from kbailabs import KBAIClient

client = KBAIClient(api_key="your-api-key")

# Make your first API call
result = client.analyze({
    "type": "interview",
    "data": "sample interview content"
})

Language Support

SDKs available for Python, JavaScript, Java, C#, Go, Ruby, PHP, and Rust with comprehensive documentation and examples.

Rate Limits

Standard plans include 1000 requests/hour. Enterprise plans offer custom limits and dedicated infrastructure.

Response Formats

All endpoints support JSON responses. XML and custom formats available for enterprise customers.

Error Handling

Comprehensive error codes and messages help you debug issues quickly and implement proper error handling.

API Reference

GetScreened Analysis API

AI-powered interview analysis and candidate screening

Base URL:

https://api.getscreened.in/v1

Available Endpoints

POST /analyze

Analyze interview content

GET /results/{id}

Retrieve analysis results

POST /questions

Generate interview questions

GET /templates

List question templates

LeadSync Prediction API

Lead scoring and conversion prediction engine

Base URL:

https://api.leadsynccrm.com/v1

Available Endpoints

POST /score

Score lead quality

GET /predictions/{id}

Get conversion predictions

POST /sync

Sync with CRM systems

GET /analytics

Retrieve analytics data

Adaptive Learning API

Core adaptive AI and continuous learning platform

Base URL:

https://api.kbailabs.com/v1

Available Endpoints

POST /models

Create custom models

PUT /models/{id}/train

Train existing models

POST /inference

Run model inference

GET /models/{id}/metrics

Get model performance

SDKs & Developer Tools

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Python

v2.1.0

45K+ downloads

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JavaScript

v2.0.8

32K+ downloads

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Java

v1.9.3

18K+ downloads

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C#

v1.8.5

12K+ downloads

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Go

v1.7.2

8K+ downloads

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Ruby

v1.6.1

6K+ downloads

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PHP

v1.5.4

9K+ downloads

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Rust

v1.4.0

4K+ downloads

Implementation Examples

Interview Analysis Integration

Python

Complete example of integrating GetScreened.in into your recruitment workflow

                # Real-time interview analysis
import asyncio
from kbailabs import GetScreenedClient

async def analyze_interview(video_stream):
    client = GetScreenedClient(api_key="...")
    
    result = await client.analyze_stream({
        "stream": video_stream,
        "position": "Software Engineer",
        "real_time": True
    })
    
    return result.insights

Lead Scoring Automation

JavaScript

Automate lead scoring and sync results with your CRM system

                // Webhook handler for new leads
app.post('/webhook/new-lead', async (req, res) => {
  const lead = req.body;
  
  const score = await leadsync.scoreLead({
    data: lead,
    context: 'website_signup'
  });
  
  await crm.updateLead(lead.id, { 
    ai_score: score.value 
  });
  
  res.json({ success: true });
});

Custom Model Training

Python

Train adaptive models on your specific domain data

                # Custom domain adaptation
from kbailabs import AdaptiveTrainer

trainer = AdaptiveTrainer(
    base_model="general-classifier",
    domain="healthcare"
)

# Continuous learning setup
trainer.enable_continual_learning()
trainer.fit(training_data, validation_data)

# Deploy adapted model
model_id = trainer.deploy(
    name="healthcare-classifier-v1"
)

Multi-Modal Analysis

Java

Process video, audio, and text data simultaneously

                // Multi-modal analysis setup
MultiModalAnalyzer analyzer = KBAIClient
    .builder()
    .apiKey("your-api-key")
    .buildMultiModal();

AnalysisResult result = analyzer
    .withVideo(videoFile)
    .withAudio(audioFile)
    .withText(transcription)
    .analyze();

System.out.println(result.getInsights());

Need Help Getting Started?

Our developer support team is here to help you integrate successfully. From implementation guidance to troubleshooting, we've got you covered.

Contact Developer Support Interactive API Explorer