Show HN: OpenBallot, Aggregated SF/California Voter Guides https://ift.tt/TspkP7q

Show HN: OpenBallot, Aggregated SF/California Voter Guides https://ift.tt/iVz5Qvm October 29, 2024 at 09:46PM

Show HN: Query standup data in natural language https://ift.tt/cjPOXt8

Show HN: Query standup data in natural language Hey HN, I was a PM for ~ 4 years before deciding to ditch everything to learn how to build software on my own. As a PM, I was doing standups every day with our engineers, but whenever I'd need an update I'd still end up pinging them on Slack. Why? - No notes from those standup calls - Folks being unavailable - No solid insight from those standups. We ended up using a Standup tool but it didn't do much apart from converting our calls to text + making standups async. Sadly, there was still no insight. So decided to do build something myself: howsthisgoing - it's an AI-powered standup bot that lets you query team updates using natural language (built with Gemini, Claude, Python/Django, Celery, Tailwind). Demo: https://www.youtube.com/watch?v=9ijCTM3PmaU Technical details: - Set up slack apis for running standups - Use gemini for standup based summaries - embeddings using voyageai - natural language queries handled in 2-parts (first with claude for extraction, then gemini for filtering) - first time setting up RAG pipeline was fun! (let me know if you'd like to know how I did this) Currently exploring integrations with Github/Linear for deeper context on technical updates. Particularly interested in solving the challenge of connecting different data sources (commits, tickets, standups, sales updates) into a queryable knowledge base. Looking for feedback on: - Which data sources would be most valuable to integrate? - Planning to pivot to an "all-in-one updates app with github/linear/hubspot etc. being as source. What do you guys think of this idea? https://ift.tt/dSseZ3F October 29, 2024 at 02:20AM

Show HN: Saasdoor – Glassdoor for Enterprise SaaS price parody https://ift.tt/BCb3eQA

Show HN: Saasdoor – Glassdoor for Enterprise SaaS price parody https://saasdoor.org October 29, 2024 at 01:35AM

Show HN: I made a site to track 2024 U.S. election PAC winners https://ift.tt/8DukGNM

Show HN: I made a site to track 2024 U.S. election PAC winners https://ift.tt/fmDwEJb October 29, 2024 at 12:32AM

Show HN: Trench – Open-source analytics infrastructure https://ift.tt/GaWUnph

Show HN: Trench – Open-source analytics infrastructure Hey HN! I want to share a new open source project I've been working on called Trench ( https://trench.dev ). It's open source analytics infrastructure for tracking events, page views, and identifying users, and it's built on top of ClickHouse and Kafka. https://ift.tt/t9T1Qxb I built Trench because the Postgres table we used for tracking events at our startup ( http://frigade.com/ ) was getting expensive and becoming a performance bottleneck as we scaled to millions of end users. Many companies run into the same problem as us (e.g. Stripe, Heroku: https://ift.tt/JGadNz9 ). They often start by adding a basic events table to their relational database, which works at first, but can become an issue as the application scales. It’s usually the biggest table in the database, the slowest one to query, and the longest one to back up. With Trench, we’ve put together a single Docker image that gives you a production-ready tracking event table built for scale and speed. When we migrated our tracking table from Postgres to Trench, we saw a 42% reduction in cost to serve on our primary Postgres cluster and all lag spikes from autoscaling under high traffic were eliminated. Here are some of the core features: * Fully compliant with the Segment tracking spec e.g. track(), identify(), group(), etc. * Can handle thousands of events per second on a single node * Query tracking data in real-time with read-after-write guarantees * Send data anywhere with throttled and batched webhooks * Single production-ready docker image. No need to manage and roll your own Kafka/ClickHouse/Nodejs/etc. * Easily plugs into any cloud hosted ClickHouse and Kafka solutions e.g. ClickHouse Cloud, Confluent Trench can be used for a range of use cases. Here are some possibilities: 1. Real-Time Monitoring and Alerting: Set up real-time alerts and monitoring for your services by tracking custom events like errors, usage spikes, or specific user actions and sending that data anywhere with Trench’s webhooks 2. Event Replay and Debugging: Capture all user interactions in real-time for event replay 3. A/B Testing Platform: Capture events from different users and groups in real time. Segment users by querying in real time and serve the right experiences to the right users 4. Product Analytics for SaaS Applications: Embed Trench into your existing SaaS product to power user audit logs or tracking scripts on your end-users’ websites 5. Build a custom RAG model: Easily query event data and give users answers in real-time. LLMs are really good at writing SQL The project is open-source and MIT-licensed. If there’s interest, we’re thinking about adding support for Elastic Search, direct data integrations (e.g. Redshift, S3, etc.), and an admin interface for creating queries, webhooks, etc. Have you experienced the same issues with your events tables? I'd love to hear what HN thinks about the project. https://ift.tt/Kb0Uc3J October 25, 2024 at 07:37PM

Show HN: Finstruments - Financial instrument library built with Python https://ift.tt/lNzEFAO

Show HN: Finstruments - Financial instrument library built with Python finstruments is a Python library designed for modeling financial instruments. It comes with the core financial instruments, such as forwards and options, out of the box, as well as position, trade, and portfolio models. finstruments comes with the basic building blocks, making it easy to extend and build new instruments for any asset class. These building blocks also provide the functionality to serialize and deserialize to and from JSON, enabling the ability to store a serialized format in a document database. This library is ideal for quantitative researchers, traders, and developers who need a streamlined way to build and interact with financial instruments. https://ift.tt/B5cbLD6 October 28, 2024 at 10:48AM

Show HN: I built EstateLead AI – lead generator boosting agent productivity 10x https://ift.tt/cNqTBLf

Show HN: I built EstateLead AI – lead generator boosting agent productivity 10x As a former real estate agent, I discovered a critical pain point in early 2023. Every day, I spent 3-4 hours manually copying leads from Zillow - phone numbers, emails, and property details. This tedious process was stealing valuable time I could have spent with clients. I realized this wasn't just my problem. Thousands of agents were stuck in this same time-consuming routine, manually gathering leads one by one. There had to be a better way. Over the next a months, I faced numerous challenges building EstateLead AI: - Ensuring reliable data extraction - Maintaining compliance with data privacy regulations - Creating an intuitive interface for non-technical users - Scaling the system to handle thousands of requests After countless iterations and feedback from 50+ beta testers, I'm excited to launch EstateLead AI with these key features: Key Features: - One-click lead extraction from Zillow listings - Up to 18,000 leads per month with phone numbers - Export to Excel/CSV for easy CRM integration - Coverage for both US and Canadian markets - Built-in compliance with data protection rules - Simple browser extension interface The tool has already helped 600+ agents save 40+ hours per week on lead generation. Early users report a 10x increase in their prospecting efficiency. I'd love for the HN community to try it out and share your thoughts. What features would make this even more valuable for real estate professionals? Try it here: https://ift.tt/DxFr4XJ P.S. First 100 users get 40% off (19 spots remaining), and we offer a 60-day money-back guarantee. https://ift.tt/DxFr4XJ October 27, 2024 at 03:02PM