Hello guys, just curious about how can people or systems (computers) detect when a text was written by an LLM. My question is mainly focused to if there is some API or similar to detect if a text was written by an LLM. Thanks!!!
FL score
out of 100
Verdict
high confidence
Competition
9
competitors found, emerging market, funded players
Trend
No signal yet
An AI detection API that aims to improve on the current high false positive rates and inconsistency of existing tools, targeting educators, publishers, and content platforms.
The pain
The gap
Build angle
Strengths
Questions about this idea?
FlyBot reads the scoring and gives you a second opinion on “How do systems (or people) detect when a text is written by an LLM”.
Risks
Next steps
Fly Labs Method
Is the pain real, is there a gap, is it the right time, can one person build it.
High demand for AI detection exists due to clear, severe pain points, and users are willing to pay for solutions. However, the market is crowded with funded incumbents, and building a genuinely superior product that addresses specific complaints with high accuracy is a significant technical challenge for a solo founder.
Value Equation
Dream outcome and how likely it feels, against the time and effort it costs.
Strong market demand and growth potential, but the complexity of achieving a superior, believable solution in a crowded space makes differentiation and solo execution difficult.
One-Person Business
Curiosity pull, identity fit, and a path from free value to paid for a solo creator.
Clear market problem and monetization path, but high technical complexity, intense competition, and lack of a distinct niche make it challenging for a solo builder.
Viral Frameworks
Hook strength, shareability, and how cheaply it can be tested.
Strong value proposition but a lack of specific target audience and a high assumption risk regarding technical superiority make it difficult to validate and launch as a micro-SaaS.
Builder Lens
Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.
Strong underlying demand for AI detection but lacks a desperate, specific wedge and faces high technical hurdles to outperform existing solutions.
Why this verdict
Five lenses, one composite. How scoring works
The angle
This weekend
Who is already there, emerging market
Originality.ai offers a suite of AI tools for writers, students, editors, marketers, web publishers, and educators, including AI detection, plagiarism checking, fact-checking, and grammar checking.
Pricing: Starts at $14.95/month or $30 for 3,000 credits (pay-as-you-go).
GPTZero is an AI detection tool focused on identifying GPT-generated content, offering a free online demo, Chrome extension, and integrations with academic platforms.
Pricing: Free tier for up to 10,000 words per month (5 advanced scans). Paid plans for 150,000 to 500,000 words per month.
Copyleaks provides an AI detection API and plagiarism checker that identifies AI-generated content from various models in over 30 languages.
Pricing: $7.99/month for AI detection only, or $13.99/month for AI + plagiarism bundled. Credit-based system with significant cost implications.
Turnitin is widely used in educational institutions for plagiarism and AI content detection, integrated with LMS platforms.
Pricing: Institutional licensing only; not available for individual purchase.
Winston AI is an AI content detection solution that helps detect AI-generated content from various LLMs with high accuracy, also offering a plagiarism detection tool.
Pricing: Starts at $18/month.
Sapling offers an AI content detection API as part of its broader AI writing and grammar assistant tools, providing overall and sentence-level scores.
Pricing: Free version has short text limits. API access for Team or Enterprise plans.
ZeroGPT is a free and fast AI detector for quick checks on AI-generated text.
Pricing: Free, with unlimited scans without an account.
QuillBot's AI Detector identifies text generated by major LLMs and also text refined with paraphrasers or grammar checkers, providing sentence-level analysis.
Pricing: AI detection is part of premium plans, not a free Turnitin alternative.
Grammarly offers an AI Detection API that allows organizations to evaluate the authenticity of written content by estimating the likelihood it was generated by AI tools.
Pricing: AI detection and plagiarism features are locked behind premium plans.
What they charge
Recent news
SciTechDaily, April 05 2026
PBS News, April 02 2026
The Guardian, March 29 2026
Education Week, March 26 2026
AmpiFire, March 17 2026
Market signals
The AI detector market is experiencing strong growth, valued at approximately USD 0.69 billion in 2025 and projected to reach USD 4.81 billion by 2033, growing at a CAGR of 27.55% from 2026-2033. This growth is driven by the rapid increase in AI-generated content across education, media, publishing, cybersecurity, and enterprises, leading to a high demand for tools that ensure content authenticity, copyright protection, and fraud prevention. North America holds the largest revenue share, with the U.S. market alone valued at USD 0.72 billion in 2025 and growing at a strong 26.4% CAGR.
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
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