Singlestore x Pydelhi

[shshkr09]

Talk title

Talk to your Data - Introduction to Singlestore

Short talk description

This will be a 90 min session where we will talk about singlestore in brief and unleash the AI capability of singlestore to demonstrate talking to your data in Natural language

Long talk description

This will be a tailor 90 min session where you will get to know about Singlestore -A modern data platform designed for speed ,scale and simplicity . A Hands-on exercise where we will show how you can ingest 100GB of data within few second and use the dataset to Ask question in natural language to derive insight out of of that.

What format do you have in mind?

Workshop (45-60 minutes, hands-on)

Talk outline / Agenda

25 min - Introduction to Singlestore.
45 min - Hand-on Lab
20 min - Q & A

As a part of Lab you just need a laptop with internet.

High-level steps for HOL

1. Create a Helios Cluster. (15 min)
2. Load data set using Pipelines (15 min)
3. Build a app to talk to data. (15 min)

Key takeaways

Understand the Data platform offering
How to get started with Singlestore.
Concept of Pipeline to perform fast ingestion
Use LLM to send the context and get the insight using Natural language.

What domain would you say your talk falls under?

Artificial Intelligence & Deep Learning

Duration (including Q&A)

25 min - Introduction to Singlestore. 45 min - Hand-on Lab 20 min - Q & A

Prerequisites and preparation

None- you need a laptop with browser and Internet

Resources and references

NA

Link to slides/demos (if available)

NA

Twitter/X handle (optional)

NA

LinkedIn profile (optional)

https://www.linkedin.com/in/kumaasha/

Profile picture URL (optional)

No response

Speaker bio

Ashish Kumar is a Principal Solution Architect specializing in building high-performance data and AI solutions. With extensive experience across real-time analytics, vector search, and generative AI integrations, he helps enterprises design and scale modern architectures using SingleStore, Apache Kafka, and big data ecosystems.

Ashish is also a frequent speaker at AI and data engineering events across the Middle East and India, where he shares practical insights on bridging AI workloads with high-performance data infrastructure.

Availability

08-11-2025

Accessibility & special requirements

None

Speaker checklist

• I have read and understood the PyDelhi guidelines for submitting proposals and giving talks
• I will make my talk accessible to all attendees and will proactively ask for any accommodations or special requirements I might need
• I agree to share slides, code snippets, and other materials used during the talk with the community
• I will follow PyDelhi's Code of Conduct and maintain a welcoming, inclusive environment throughout my participation
• I understand that PyDelhi meetups are community-centric events focused on learning, knowledge sharing, and networking, and I will respect this ethos by not using this platform for self-promotion or hiring pitches during my presentation, unless explicitly invited to do so by means of a sponsorship or similar arrangement
• If the talk is recorded by the PyDelhi team, I grant permission to release the video on PyDelhi's YouTube channel under the CC-BY-4.0 license, or a different license of my choosing if I am specifying it in my proposal or with the materials I share

Additional comments

No response

[Animesh-Ghosh]

Hey @shshkr09, thanks for your proposal!

It would be nice for the session to instead of only being an intro to SingleStore, be an intro to distributed computing, and distributed databases too. You can then introduce SingleStore and mention how it solves certain problems in the domain like distributed joins and transactions, if those are relevant, and then move on to the hands-on demo (which should hopefully be in Python 🙃).

Could you also share a public link to the slides for your session? It doesn't have to be the final version, but just something that'll help us see how you've outlined the content for the session, and to help us give feedback on the slides themselves.

Thanks!