Overview

Sectors has been used as an equity research tool by Indonesia’s top financial institutions, and has also been used as a data source for academic research. The depth of our data puts it head and shoulders above any comparable market intelligence tool, and is readily available through a simple developer experience with Sectors API.

Beginners can start with our Quickstart guide, while more experienced developers can dive into our API Reference for a comprehensive list of endpoints and examples.

We also have longer-form tutorial series and recipes for those looking to build financial analysis workflows and automations by example.

Tutorial Series

Generative AI series

Ongoing (Q4 '24):

5-part Generative AI Series

Create RAG systems and AI agents with Sectors Financial API, LangChain and state-of-the-art LLM models -- capable of producing fact-based financial analysis and financial-specific reasoning. **Continually updated** to keep up with the latest major versions of the tools and libraries used in the series.

Generative AI Series: Table of Contents

1

Generative AI for Finance

An overview of designing Generative AI systems for the finance industry and the motivation for retrieval-augmented generation (RAG) systems.
2

Tool-Use Retrieval Augmented Generation (RAG)

3

Structured Output from AIs

From using Generative AI to extract from unstructured data or perform actions like database queries, API calls, JSON parsing and more, we need schema and structure in the AI's output.
4

Tool-use ReAct Agents w/ Streaming

Updated for LangChain v0.3.2, we explore streaming, LCEL expressions and ReAct agents following the most up-to-date practices for creating conversational AI agents.
5

Conversational Memory AI Agents

Updated for LangChain v0.2.3, we dive into Creating AI Agents with Conversational Memory

API in Spreadsheets

Work with live financial data that refreshes automatically directly in Excel, Google Sheets and other Business Intelligence tools. No coding required.