https://pardonned.comInspired by the videos of Liz Oyer, I wanted to be able to verify her claims and just look up all the pardons more easily.Tech Stack: Playwright - to sccrape the DOJ website SQLite - local database Astro 6 - Build out a static website from the sqlite dbAll code is open source and available on Github.
FL score
out of 100
Verdict
high confidence
Competition
5
competitors found, emerging market, funded players
Trend
No signal yet
A searchable database of US pardons that fills a significant data gap for journalists, legal professionals, and researchers.
The pain
The gap
Build angle
Strengths
Questions about this idea?
FlyBot reads the scoring and gives you a second opinion on “Pardonned.com – A searchable database of US Pardons”.
Risks
Next steps
Fly Labs Method
Is the pain real, is there a gap, is it the right time, can one person build it.
A highly promising idea for a solo builder, addressing a clear, specific, and severe pain point in the legal research space with a strong market gap and good buildability.
Value Equation
Dream outcome and how likely it feels, against the time and effort it costs.
This idea has strong potential due to clear pain, a valuable solution, and a growing legal tech market, though distribution and continuous data maintenance pose challenges.
One-Person Business
Curiosity pull, identity fit, and a path from free value to paid for a solo creator.
A promising niche idea with a clear problem and good monetization potential for a solo builder, leveraging transferable skills and data asset.
Viral Frameworks
Hook strength, shareability, and how cheaply it can be tested.
A solid micro-SaaS candidate with a clear value proposition for a specific, reachable audience and a viable subscription business model.
Builder Lens
Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.
A strong YC candidate with clear user pain, a well-defined target, and a narrow buildable wedge, addressing a growing need for data transparency.
Why this verdict
Five lenses, one composite. How scoring works
The angle
This weekend
Who is already there, emerging market
The official US Department of Justice website allows searching for federal clemency cases by name, case number, or BOP register number.
Pricing: Free
A law firm (Brandon Sample PLC) offering legal assistance for state and federal clemency, pardon, commutation, and amnesty petitions.
Pricing: Requires attorney consultation for pricing, not publicly available.
Helps individuals clear Pennsylvania criminal records through pardons, expungements, and the Clean Slate program.
Pricing: Offers free attorney evaluations, flat-rate fees, and flexible payment plans (actual numbers not specified on site).
Connects individuals with local Pardon Projects and volunteers to assist with Pennsylvania pardon applications.
Pricing: Information and assistance are likely free through their associated projects, but specific legal services may have costs.
Provides a searchable docket for pardon and parole cases in Oklahoma by month, year, last name, and county.
Pricing: Free
What they charge
Recent news
Hacker News, April 11 2026
Reddit (r/legaltech), January 08 2026
Business Insider, December 01 2025
PYMNTS.com, October 24 2025
Crunchbase News, September 23 2025
Market signals
The legal technology market is large and experiencing significant growth, projected to reach between $63.59 billion by 2032 and $83.8 billion by 2035, with a CAGR of around 9.4% to 10.4%. North America holds a substantial share of this market, driven by investments in AI and automation. Recent funding rounds in the broader legal tech space, particularly for AI-driven solutions, have been substantial, with over $2.4 billion in 2025, indicating a strong investor interest in technologies that improve efficiency and automate legal processes. However, standalone AI legal research tools may struggle without integration into existing workflows.
What frustrates people
Last summer we faced a conundrum at my company, Tiger Data, a Postgres cloud vendor whose main business is in timeseries data. We were trying to grow our business towards emerging AI-centric workloads and wanted to provide a state-of-the-art hybrid search stack in Postgres. We'd already built pgvectorscale in house with the goal of scaling semantic search beyond pgvector's main memory limitations. We just needed a scalable ranked keyword search solution too.The problem: core Postgres doesn't provide this; the leading Postgres BM25 extension, ParadeDB, is guarded behind AGPL; developing our own extension appeared daunting. We'd need a small team of sharp engineers and 6-12 months, I figured. And we'd probably still fall short of the performance of a mature system like Parade/Tantivy.Or would we? I'd be experimenting long enough with AI-boosted development at that point to realize that with the latest tools (Claude Code + Opus) and an experienced hand (I've been working in database systems internals for 25 years now), the old time estimates pretty much go out the window.I told our CTO I thought I could solo the project in one quarter. This raised some eyebrows.It did take a little more time than that (two quarters), and we got some real help from the community (amazing!) after open-sourcing the pre-release. But I'm thrilled/exhausted today to share that pg_textsearch v1.0 is freely available via open source (Postgres license), on Tiger Data cloud, and hopefully soon, a hyperscalar near you:https://github.com/timescale/pg_textsearchIn the blog post accompanying the release, I overview the architecture and present benchmark results using MS-MARCO. To my surprise, we were not only able to meet Parade/Tantivy's query performance, but exceed it substantially, measuring a 4.7x advantage on query throughput at scale:https://www.tigerdata.com/blog/pg-textsearch-bm25-fu
AI
Hi HN!I recently switched from a Fedora/GNOME laptop to a MacBook Air. My old setup served me well as a portable workstation, but I’ve started traveling more while working remotely and needed something with similar performance but better battery life. The main thing I missed was a simple taskbar that shows the windows in the current workspace instead of a Dock that mixes everything together.I built boringBar so I would not have to use the Dock. It shows only the windows in the current Space, lets you switch Spaces by scrolling on the bar, and adds a desktop switcher so you can jump directly to any Space. You can also hide the system Dock, pin apps, preview windows with thumbnails, and launch apps from a searchable menu (I keep Spotlight disabled because for some reason it uses a lot of system resources on my machine).I’ve been dogfooding it for a few months now, and it finally felt polished enough to share.It’s for people who like macOS but want window management to feel a bit more like GNOME, Windows, or a traditional taskbar. It’s also for people like me who wanted an easier transition to macOS, especially now that Windows feels increasingly user-hostile.I’d love feedback on the UX, bugs, and whether this solves the same Dock/Spaces pain for anyone else.P.S. It might also appeal to people who feel nostalgic for the GNOME 2 desktop of yore. I started my Linux journey with it, and boringBar brings back some of that feeling for me.
AI
### Describe the project you are working on Godot C# bindings ### Describe the problem or limitation you are having in your project For the past weeks, I've been discussing with several Unity users intending to move to Godot C# regarding dealing with the C# garbage collector. The most common complaint I hear from users is that, in Unity, allocations can trigger unexpected GC spikes into the game. In Godot, we target to make all of the high performance APIs (those that intended to be called every frame) not allocate any memory, so theoretically the GC should not be a problem. Additionally, Godot starting from 4.0, uses the Microsoft CoreCLR version of .net, which also supposedly has a better garbage collector than Unity. But in all, after several discussions with Unity users, neither is enough reassurance for them, and they would really feel safer if Godot exposed a zero allocation API. ### Describe the feature / enhancement and how it helps to overcome the problem or limitation The idea of this proposal is that Godot exposes zero allocation versions of many functions in the C# API, that users can use if they desire. Technically, this could be done from the binding generator itself, without breaking compatibility, and without doing any modification to Godot itself. ### Describe how your proposal will work, with code, pseudo-code, mock-ups, and/or diagrams **WARNING** I am not familiar with C#, so take this as pseudocode. Imagine you have two functions exposed as to C#: ```C# void MyClass.SetArray( Vector2[] array); Vector2[] MyClass.GetArray(); ``` This works and is pretty and intuitive. However, it has two problems: * GC is allocated on return * Memory is copied to Godot native formats every time there is a call. The idea is to add NoAlloc versions, which can be generated directly by the binder automatically when required: ```C# void MyClass.SetArrayNoAlloc( Godot.Collections.PackedVector2Array array); void MyCl
AI