Alternatives
Products that do what FactIQ – a realtime econ+finance database for AI agents does
Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
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Parsewise API▲134Hi HN! We're X25 alumni and built Parsewise to analyze large document sets with AI agents. Instead of prompting a single PDF, our agents extract, cross-reference, and reason across thousands of documents in one run. We originally built this for insurance and financial diligence workflows where teams review huge document packs. Curious what the HN community thinks! Check out our public demos: demo.parsewise.ai/insurance-claims-triage demo.parsewise.ai/reinsurance-recovery-optimization demo.parsewise.ai/investment-diligence demo.parsewise.ai/mortgage-underwriting
May 2026 · parsewise.ai
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Hey HN, For the last couple of months, we have been building an AI agent for continuous statistical analysis, and we're looking for feedback while it's still early in development. We call it BIGWIG - an autonomous agent that is specialised, and very good at, performing advanced statistical analysis, through long traces of iteration and reasoning. As it builds statistical models it also "emits" outputs back to the user that you can then interact with, iterate on and schedule for follow up analysis. While we're still in BETA, we've launched a public analysis site that showcases some of the…
2025 · askbigwig.com
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Hey HN, I'm Steve, co-founder of Factor.fyi, a new data platform for querying and visualizing financial datasets using SQL. During the pandemic, I took much more of an active role in managing my portfolio. I wanted to be able to make informed decisions about the investments I was making, and explore financial data in new ways. Market and Econ data are some of the most talked-about and widely-available datasets out there, but I was frustrated by the lack of options to answer questions I had, like, "What would have happened if I had started dollar-cost averaging VTI back in 2013?"[1] Or, "How…
2022 · factor.fyi
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I built Hermes, an open-source Python framework for multi-agent financial research. Most AI “equity research” demos stop at generating text. In practice, real workflows require pulling structured XBRL financials from SEC filings, extracting labeled sections like MD&A and Risk Factors, merging macro and market data, building actual Excel models with formulas, and generating investment memos in Word or PDF. Hermes is designed to handle that full pipeline end to end. It includes 35 financial data tools covering SEC EDGAR (via edgartools), FRED, Yahoo Finance market data, and RSS-based financial…
Feb 2026 · github.com
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Professional-grade stock investing, simplified with AI.
Mar 2026 · accountable.finance
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
Oct 2025 · github.com
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A while back, I built a simple app to track stocks. It pulled market data and generated daily reports based on my risk tolerance. Basically a personal investment assistant. It worked well enough that I kept going. Now, the same framework helps me with real estate: comparing neighborhoods, checking flood risk, weather patterns, school zones, old vs. new builds, etc. It’s a messy, multi-variable decision—which turns out to be a great use case for AI agents. Instead of ChatGPT or Grok 4, I use mcp-agent, which lets me build a persistent, multi-agent system that pulls live data, remembers my…
2025 · github.com
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Hi HN, We’re a small team working on 13Radar.com, which we launched about two weeks ago after 4 months of development. I’m the founder, and together with the team we’re building a platform that tracks hedge fund portfolios in real-time based on SEC Form 13F filings. AI has been a major helper in our workflow. For a single webpage, we often consult multiple AI systems in parallel, generating different versions and comparing them side by side before deciding on the final design or implementation. More than 60% of the research, design, and coding involved AI assistance. For UI design we used…
Nov 2025 · 13radar.com
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Hi HN! I am an undergrad student trying to build interesting things with AI. Recently, I was looking for a dataset I could use for a new project. I realized that it is really frustrating to go through all the government websites (with terrible UX) just to find some usable dataset. I set out to build a GitHub for datasets, named DataHub. Right now, we have more than 1000 datasets from Montréal and New York City, with more cities coming soon (and possible government agencies). All of this is wrapped into a powerful search. It's a breeze to find a dataset to work on. I'd be interested to know…
2017
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Hi HN, We built an AI agent for data analysts that turns the soul crushing spreadsheet & BI tool grind into a fast, verifiable and joyful experience. Early users reported going from hours to minutes on common real-world data wrangling tasks. It's much smarter than an Excel copilot: immutable data steps, a DAG of SQL views, and DuckDB for instant crunching over millions of rows. Our early agent prototype ranked #1 on the Spider2-DBT bench. https://spider2-sql.github.io Try it out and we'd love your feedback! Thanks, Di Wu & the Shadowfax team P.S. Shadowfax is Gandalf's horse from…
Nov 2025 · shadowfax.ai
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2021 · researchfin.ai
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Hey HN, as a former data analyst, I’ve been tooling around trying to get agents to do my old job. The result is this system that gets you maybe 80% of the way there. I think this is a good data point for what the current frontier models are capable of and where they are still lacking (in this case — hypothesis generation and general data intuition). Some initial learnings: - Generating web app-based reports goes much better if there are explicit templates/pre-defined components for the model to use. - Claude can “heal” broken charts if you give it access to chart images and run a…
Mar 2026 · rubenflamshepherd.com
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Hey HN, I just spent the last few weeks building a database for agents. Over the last year I built PostHog AI, the company's business analyst agent, where we experimented on giving raw SQL access to PostHog databases vs. exposing tools/MCPs. Needless to say, SQL wins. I left PostHog 3 weeks ago to work on side-projects. I wanted to experiment more with SQL+agents. I built an MVP exposing business data through DuckDB + annotated schemas, and ran a benchmark with 11 LLMs (from Kimi 2.5 to Claude Opus 4.6) answering business questions with either 1) per-source MCP access (e.g. one Stripe…
Apr 2026 · github.com
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Built a free open source agentic CLI tool for financial modeling & analysis. Hadn't played around with real equity valuation modeling for awhile and wanted to build tooling to get myself back into the game. Bull.sh lets you query & store 10-Qs, 10-K in a local vector store to chat with them, build investment thesis from scratch or build full framework models through the CLI to export into excel. It's open source, just requires your own Anthropic API key and (optionally) AlphaVantage Free API key if you want save some tokens from scraping. Feel free to play around with it. Some ideas I have…
Jan 2026 · github.com
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The AI platform purpose-built for modern finance teams
Mar 2026 · ai.zenstatement.com
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I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!
Jul 2026 · laurentiugabriel.github.io
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I posted this a few weeks ago and the server died under the traffic. Fixed that by adding an in-mem caching layer with Redis/valkey and added CloudFront caching for static content. Also upgraded the server. Also fixed the Firefox bugs, trying again. It's a research tool for US stocks. Financials for ~10k companies pulled from SEC filings. You can chart any metric across companies, filter news by ticker, ask questions in plain English and get a chart back. There's also SQL console against the whole database, which is the part I like to use together with the AI chat (generates an SQL…
Jun 2026 · terminal.tesseractanalytics.ai
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