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WeAreDevelopers LIVE • Nov 10, 2023

OpenAI for FinTech: Building a Stock Market Advisor Chatbot

Akmal Chaudhri

Could an AI instantly analyze high-volume stock data without cumbersome ETL pipelines? Learn to build a scalable, hallucination-free financial chatbot using LangChain, OpenAI Whisper, and distributed SQL.

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#1 about 4 min

Introduction to OpenAI and SingleStore for financial bots

Understanding the landscape of artificial intelligence in financial systems requires clear boundaries regarding the use of fictitious synthetic data.

#2 about 3 min

Agenda overview for the stock market advisor chatbot

The technical framework focuses on integrating sentiment analysis pipelines, language chains, and localized speech models.

#3 about 4 min

Core capabilities of SingleStore distributed relational SQL database

Scale-out clustering and universal storage mechanisms streamline analytics workflows by centralizing transactional and historical processing.

#4 about 4 min

Handling vector embeddings and multi-model formats in SingleStore

Native compatibility with document stores and foundational vector engines provides robust persistence for diverse analytical datasets.

#5 about 3 min

Solving real-time analytics challenges in embedded finance applications

Harnessing streaming capabilities minimizes latency constraints during complex risk calculations and peer-to-peer lending operations.

#6 about 2 min

Exploring the AI technology stack for chatbot demos

Combining open-source transformers with analytical agents isolates text classification models for actionable programmatic querying.

#7 about 7 min

Provisioning a free SingleStore workspace and computing cluster

Separating storage from compute via a cloud portal enables scalable infrastructure management without heavy credit burn.

#8 about 5 min

Building database tables and ingesting synthetic Kafka feeds

Mapping real-time tick sources through persistent pipelines automates continuous telemetry ingestion directly into tabular structures.

#9 about 4 min

Producing candlestick visualization charts inside integrated Jupyter notebooks

Executing relational aggregation queries within integrated notebooks rapidly translates raw pricing metrics into graphical trading insights.

#10 about 6 min

Translating natural language into database queries with LangChain

Executing parameterized agents bypasses syntax formulation protocols by dynamically reasoning optimal schema relationships from conversational prompts.

#11 about 7 min

Executing local voice commands through the Whisper agent

Processing audio inferences directly on the workstation bypasses remote API latency while preserving complete command automation logic.

#12 about 2 min

Recap of optimal architectures for financial advisory tools

Architecting independent pipelines connecting streaming interfaces with deterministic processing significantly improves custom virtual assistant iterations.

#13 about 11 min

Discussion on AI hallucinations and practical developer workflows

Balancing automated code generation tools requires mitigating contextual inaccuracies while navigating complex real-world programmatic patterns.

Matching moments

1:39 min

Live demo of AI chat interactions with ClickHouse

Hellmar Becker Hellmar Becker · World Congress 2026 Europe

1:23 min

Developer adoption of integrated AI chat features

Julia Kasper · Coffee With Developers

1:44 min

Summarizing developer experience and artificial intelligence companions

Robert Hoffmann Robert Hoffmann +1 · LIVE

3:50 min

Powering workflows with connected and agentic AI

Christian Voigt Christian Voigt · World Congress 2026 Europe

2:27 min

Introducing conversational queries with AI data agents

Dr. Alexander Wachtel Dr. Alexander Wachtel +1 · World Congress 2025

2:08 min

Demonstrating a conversational AI shopping experience

Benjamin Smith Benjamin Smith · World Congress 2026 Europe

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