Problem Statement PhonePe, as a payments platform, has an essential feature that allows users to check all past transactions. When payments are made to businesses/merchants, users have access to a historical view of all such transactions. For peer to peer transactions, however,…
What is Feed Re-ranking? Online shopping platforms face intense competition, where the ability to deliver the most relevant products to customers is crucial. A well-organized and relevant product feed, which inherently is a list of products, forms the backbone of any E-commerce…
Supercharging ShareChat ML Feature System with Flink DataStream
At ShareChat, our in-house ML feature system powers personalized feed recommendations across the platform.Built on Apache Flink, it serves as a feature-as-a-service platform for scalable computation
Building Meesho’s ML Platform: From Chaos to Cutting-Edge (Part 1)
The Genesis: How a Friday Night Roast Sparked Meesho’s ML Platform It all started in early 2022, over a casual Friday evening catch-up. Like many great origin stories, this one began with friendly banter between a group of backend engineers and data scientists. As the…
Scaling Seamless Communication: How Meesho Powers 10B+ Messages Daily with Multi-Tenancy
Revolutionizing Communication at Scale At Meesho, seamless communication is at the heart of our user experience. Whether it’s an OTP for login, an order update, or a personalized shopping recommendation, our platform ensures timely and reliable messaging across multiple…
Scaling Seamless Communication: How Meesho Powers 10B+ Messages Daily with Multi-Tenancy
Revolutionizing Communication at Scale At Meesho, seamless communication is at the heart of our user experience. Whether it’s an OTP for login, an order update, or a personalized shopping recommendation, our platform ensures timely and reliable messaging across multiple…
Building WebRTC Recording Infrastructure using GStreamer and Temporal
Our recording infrastructure focuses on WebRTC video and audio. The goal is to allow moderation teams to access clean, archived footage—composite or individual—for compliance, post-production, or analysis.
The Journey to Faster Android Builds: How We Slashed Our Build Times at slice
As an Android developer at slice, watching our app evolve from a simple financial product to a full fledged bank has been exciting. But this growth came with a challenge familiar to many developers: increasingly painful build times. What started as a minor inconvenience…
In the early days of PhonePe, we started with just one application. Our pace was fast, almost like a race against time, and our initial engineers managed to keep things tidy. Colors, typography, and size constants were well-organized, ensuring a cohesive look and feel. Our small…
Android Network Observability: Shedding Light on Performance Blind Spots
Introduction In Android development, network performance issues can be notoriously hard to debug. While tools like Firebase Performance Monitoring provide high-level insights like error rates and latency, they fall short in providing granular visibility into each stage of the…
Data access layer: Unlocking the full potential of financial data
The final piece of the puzzle: Data access layer In the previous installments of this series (part 1 [https://hasura.io/blog/escaping-the-data-doom-loop-in-financial-services], part 2…
Time-traveling through your data architecture: Using data agents to understand change
Learn why tracking the evolution of your data architecture in Hasura's Data Delivery Network (DDN) isn't just nice to have – it's essential for robust governance and intelligence.
Data products, data contracts: A new model for data management in financial services
In Part 1, we covered the data doom loop [https://hasura.io/blog/escaping-the-data-doom-loop-in-financial-services] – the cycle of complexity, inefficiency, and eroding trust in financial data that persists despite massive investments. The solution isn’t another sweeping…
How PromptQL achieves 100% accuracy for AI on enterprise data
PromptQL addresses the limitations of traditional approaches like RAG, Text-to-SQL, and Tool Calling. PromptQL provides measurable improvements in accuracy (with a clear path to reaching 100% accuracy) when connecting LLMs to enterprise data.
How ShareChat built a scalable cost efficient ML Feature system
At ShareChat, Machine Learning models form the backbone of our recommendation system, playing a pivotal role in delivering the most relevant and engaging content to our users.
Across industries – and especially in highly regulated sectors like healthcare, financial services, and government – MongoDB has been a preferred database solution for organizations handling large volumes of sensitive data that require strict compliance adherence. In such…
Building a powerful customer support AI assistant with PromptQL in 5 minutes
In today's data-driven world, connecting AI to your organization's data remains a significant challenge. What if you could build AI assistants that can query databases, access customer support tickets, and even take actions—all using natural language?
Integrate real-time web search and enrich your private data with PromptQL
By integrating web search in PromptQL, you can enrich your private data – stored in any systems like Snowflake, BigQuery, PostgreSQL, MongoDB, or accessed through APIs – with current real-time details from the web.
The primary goal of a recommendation system is to identify and deliver the most relevant content for a user. To achieve this, it must not only identify high-quality content but also ensure diversity
Seamlessly Migrating from MongoDB to PostgreSQL: Leveraging Data Platform for Scalable Success
Freaking hard Migration from MongoDB to PostgreSQL: Leveraging Data Platform for Scalable Success Introduction In today’s fast-paced digital landscape, selecting the right database technology is a crucial decision for any organisation’s success. Initially, MongoDB’s flexible…
Navigating data governance with Hasura: Building trust, streamlining operations, and powering AI
Hasura’s metadata-based approach is a data governance solution, acting as a semantic layer for your data, preserving clear lineage and robust governance.