Building a Sentiment Analysis Pipeline with Just One API Call
A practical guide to integrating sentiment analysis into your application using Kedata AI/ML API.
Why Sentiment Analysis Matters
Understanding how people feel about your brand, product, or policy is crucial for any organization. Sentiment analysis automates this process by classifying text into positive, neutral, or negative categories.
With Kedata's AI/ML API, you can add sentiment analysis to your application in minutes — no ML expertise required.
How It Works
Our API accepts any text input and returns a sentiment classification along with a confidence score. It supports both English and Indonesian text, making it ideal for Southeast Asian markets.
Available AI/ML API Endpoints
- Sentiment Analysis — Classify text as positive, neutral, or negative
- Named Entity Recognition (NER) — Extract names, locations, organizations from text
- Emotion Classification — Detect emotions: happy, sad, anger, love, fear
- Zero-shot Classification — Classify text by custom labels without training
- Small LLM Models — Run language models locally with Ollama
Use Cases
Our clients use sentiment analysis for:
- Social media monitoring for political campaigns
- Customer feedback analysis for product improvement
- News sentiment tracking for financial markets
- Public opinion analysis for government policy evaluation
Getting Started
Contact our team to get your API key. Integration takes less than an hour for most applications. We provide SDKs for Python, JavaScript, and REST endpoints for any platform.
