Codeset, Lda
Codeset provides one-to-one AI-tutored learning through complete, ordered syllabi. Learners apply each concept in a project or their own work, with assessments and, for coding courses, an in-browser editor and sandbox.
At a Glance
- Individual learners and self-directed programmers
- Beginners and early learners seeking structured programming foundations
- Intermediate developers refreshing practical skills
- Students learning software development, machine learning, DevOps, data science, and web development
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AI Tools by Codeset, Lda
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codeset
AI Tutor for Learning to Code
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Products & Services
One-to-one AI tutoring that plans lessons, explains concepts, answers questions, sets and marks assessments, and tracks progress through a complete syllabus.
A public catalog of 27 courses and 1,044 lessons, including programming, software development, machine learning, DevOps, cloud, databases, web development, and related subjects. Examples include Python Beginner Foundations, Intro to Rust, C Programming Foundations, Intro to Machine Learning, Kubernetes: From Container to Production, and React fundamentals/refresher courses.
Learners can describe what they want to learn and generate a complete syllabus/course of their own.
For code-oriented courses, the lesson opens an in-browser editor, terminal, starter files, and a sandbox so the tutor teaches through the learner's project.
Market Position
Codeset positions itself as a structured alternative to general-purpose chatbots: it provides a full syllabus in order, observes the learner's files and outputs, teaches missing concepts rather than simply handing over answers, remembers progress, and ends lessons with unaided checks. Its differentiator is combining AI tutoring with project-based practice and a browser coding workspace.
Leadership
Founders
André Silva
PhD student at KTH Royal Institute of Technology and researcher focused on coding models and machine learning for code. He has worked on program-repair fine-tuning, executable code benchmarks including RepairBench, and code-dataset tooling, and is a Google PhD Fellow.
Nuno Saavedra
PhD student at INESC-ID and Instituto Superior Técnico whose research focuses on software reliability and verification, especially infrastructure and configuration code. He developed the GLITCH infrastructure-as-code code-smell framework, has full-stack software-development experience, and has been a teaching assistant at IST.
Executive Team
André Silva
Co-Founder and CEO
KTH PhD student and machine-learning/software-engineering researcher focused on coding models, program repair, executable benchmarks, and code datasets.
Nuno Saavedra
Co-Founder and CTO
INESC-ID/Instituto Superior Técnico PhD student and software-reliability researcher; previously a full-stack software developer and IST teaching assistant.
Founding Story
Codeset was started by researchers in machine learning/software engineering and software reliability to provide structured learning rather than the open-ended, forgetful interaction of a general chatbot. Its initial vision is to teach a complete syllabus one concept at a time through a learner's own project, while checking unaided understanding.
Business Model
Revenue Model
Freemium, usage-metered subscriptions, and one-time credit top-ups. Paid plans provide monthly credits; courses, tutor messages, speech, and workspace usage consume credits. A Campus plan is sold per seat to schools, bootcamps, and teams.
Pricing Tiers
2,000 credits once; full catalog and syllabi, custom course generation, tutor, and coding workspace; no card and no trial clock.
5,000 credits per month; unused credits roll over for up to two months.
11,000 credits per month; includes speech and workspace without rationing; unused credits roll over for up to two months.
38,000 credits per month; intended for all-day use and multiple courses; unused credits roll over for up to two months.
Per-seat plan for schools, bootcamps, and teams; includes custom syllabus courses, cohort progress, invoicing/purchase orders, and human support.
Target Markets
- Individual learners and self-directed programmers
- Beginners and early learners seeking structured programming foundations
- Intermediate developers refreshing practical skills
- Students learning software development, machine learning, DevOps, data science, and web development
- Schools, bootcamps, and software teams
- Learning programming from beginner through intermediate level
- Refreshing practical skills in Python, C, Java, JavaScript, Rust, React, Git, SQL/PostgreSQL, TypeScript, DevOps, and testing
- Building a usable project while learning, such as a game, scraper, command-line tool, web app, or data workflow
- Learning machine learning, computer vision, NLP/transformers, RAG, and data wrangling
- Structured learning for schools, bootcamps, and teams through the Campus plan