We transcribe your official scheme, map it to real course codes, and author stepped lab practicals that a compiler verifies — not a model. Your students open GroutCode, pick your institution, and work through their own curriculum.
What an institutional curriculum pack actually contains.
We take the official scheme document and transcribe it course by course — codes, titles, semesters, units and topics — and record the source and its checksum so it can be audited later.
Stepped practicals authored against the courses that carry practical work, in the language that course actually uses. Not a generic exercise relabelled.
Every lesson ships with a starter file and a test file. The toolchain decides whether a student passes; the AI reviews the code afterwards and names the input that breaks it.
The lessons, the syllabus and the test runner are bundled in the app. The compile-and-check loop needs no internet, which matters on a filtered campus network.
Faculty see progress per student, and every AI-assisted submission carries a usage report — which models were invoked and how much.
C, C++, Java, Python, Node.js and SQL, assigned per course code rather than guessed from the course title.
Your faculty sign off on the mapping before any lesson is written.
The published syllabus PDF, the regulation year, and which programmes you want covered. One link is usually enough to start.
Every course is transcribed into a structured syllabus file. We identify which course codes carry practical work and which language each one is taught in.
Before a single lesson is authored, your faculty confirm the course list and the language assignments. Getting this wrong puts students in the wrong compiler.
Each practical is written as 8 to 15 stepped tasks with a starter file, a test file, and a reference solution used only by our verifier.
Nothing ships until it builds and its tests pass against the reference. A lesson that does not compile is not a lesson.
Your institution appears in the picker inside GroutCode, and your students select their scheme and start work.
Every institution already has access to an enormous amount of generic programming material. Almost none of it is organised the way a scheme is organised, which is why students still arrive at a lab sheet with no idea which of the thousand tutorials they have seen is the relevant one.
A pack fixes the mapping problem. A student in semester five opens their own scheme, sees their own course codes, and gets a practical written for the syllabus they will actually be examined on — in the language their department teaches it in, which is not something you can infer from a course title. “Data Structures” is C at one university and Java at another.
Give a first-year student a chatbot and a lab sheet and the sheet is done in four minutes, with nothing learned. The design here makes that impossible: the model writes the lesson and the tests before the student starts, the compiler issues the verdict, and the model only sees the student’s code afterwards — to review it, not to grade it.
The result is a lab where using the AI makes a student better at the subject rather than better at hiding. See how a practical runs.
Tell us the institution and the scheme. We reply within two working days.
Transcribing a scheme and authoring its lab lessons is work we take on as part of an institutional licence rather than billing separately for it. Tell us the programme and the scale and we will be specific about what is involved and what a licence looks like for your student numbers.
The transcription of a full scheme is usually days rather than weeks. Authoring lessons is the longer part, because every one is compiled and tested before it ships. A single programme is typically ready inside a few weeks; we prioritise the courses your next term actually needs.
The syllabus is yours — we transcribe what your institution has already published. The lesson material we author around it is ours, and it ships to your students under your institutional licence.
Yes, and it produces better material. Faculty review of the course-to-language mapping is already part of the process, and departments that want to author their own practicals against their course codes can do that.
No. Lessons, the syllabus and the test runner are bundled in the app and run locally. Only the AI review step needs a model, which can be a local one on the same machine.
Schemes get revised, and the pack carries its regulation year precisely so students can tell whether it is theirs. When you publish a new scheme we transcribe it as a separate pack rather than overwriting the old one, so students mid-programme keep working from the syllabus they enrolled under.
GroutCode currently ships 6 packs — KTU (2024 scheme), VTU (2022 scheme), Calicut (CUFYUGP 2024), CHRIST (2021 regulation), CBSE (2026-27 curriculum), ICSE / ISC (2026-27 syllabus) — covering 649 transcribed courses and 378 authored lab lessons.