Alternatives
Products that do what ChessInsights.ai does
Analyse chess positions from any website, book, and video.
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2021 · chrisbutner.github.io
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We built ChessBoss at the TechCrunch Disrupt hackathon this week. It didn’t make the top 10 but I thought Hacker News might think it’s pretty cool. https://devpost.com/software/chess-boss There are these really cool smart chessboards that can suggest moves and track your games... but they’re $400 and weigh 19 pounds. And of course there are apps that can analyze games but tracking and inputting games by hand is a huge pain. Or fully-digital chess apps... but board games are way more fun in real life! We wondered: “why can’t you just do that in software and bring the best…
2019 · devpost.com
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Prompt analytics and citation mapping for AI search
Jul 2026 · search-console.ai
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I built over the last two years a human-like neural network chess engine that tries to predict your rating from a single game. It automatically adapts to your play and tries to play like a human at your level would play, giving you a balanced game. At the core I’m using an AlphaZero / Leela Chess Zero style neural network that I have trained on 1 billion human games from the lichess.org open database. Around this network I have built a chess engine in Rust with algorithms that use the outputs from the NN to produce human-like moves at a given rating from beginner to world champion, as…
2022 · noctie.ai
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2023 · chessmonitor.com
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For no specific reason, I trained a neural network to generate random chess positions that look similar to positions from actual games (from lichess db). I also made it so you can condition it on some fixed pieces, and adjust the number of pieces. It turned out to be quite effective and I find it surprisingly fun and instructive to generate e.g. endgame positions with a certain pawn structure (set low temperature, place some pawns and position the kings, adjust number of pieces to get an endgame), and then figure out how to win vs. the computer in those positions. I hooked it up so that you…
2024 · chessdream.ai
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2024 · louisabraham.github.io
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I built 1e4.ai - a chess web app where you play against neural networks trained to mimic human Lichess players at specific Elo ranges. There's a separate model for each 100-point rating bucket from ~800 to 2200+, and the bots not only choose human-like moves but also burn clock time, play worse under time pressure, and blunder in human-like ways. Live demo: https://1e4.ai Code: https://github.com/thomasj02/1e4_ai A few things that might be interesting: - Trained on almost a full year of Lichess blitz games, around 1B total games - Architecture is an a small…
May 2026
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2020 · chessboardimage.com
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I built this because I got tired of Stockfish giving me evaluations (+0.5) without explaining the actual plan. Most opening explorers focus on statistics (Win/Loss/Draw). I wanted a tool that explains the strategic intent behind the moves (e.g., "White plays c4 to clamp down on d5" vs just "White plays c4"). The Project: Comprehensive Database: I’ve mapped and annotated over 3,500 named opening variations. It covers everything from main lines (Ruy Lopez, Sicilian) to deep sidelines. Strategic Visualization: The UI highlights key squares and draws arrows based on the textual…
Jan 2026 · atlaschess.me
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