Real Linux labs for colleges, from any laptop.
A real Linux machine for every student, straight from the browser. No lab PCs for faculty to maintain, hands-on practice for students, assessments that mark themselves, and progress you can track.
The Gap
Most colleges have labs. Very few have proof.
- Labs only open during scheduled hours 24/7 browser access — from home, hostel, or campus
- Students carry no verifiable record of skills Projects hosted on real URLs, and scores kept per student
- Faculty are the technical support bottleneck One template per course, so no two setups can differ
- NAAC evidence built retrospectively Progress, scores and events recorded as the work happens
- Expensive lab software with per-machine licensing One bill for the server, not a fee per lab PC or per student
- No visibility into student progress for management Progress per student and per department, in one place
Industry Tracks
Six tracks. Six career outcomes.
One platform.
Learning to code still matters, but typing code is no longer the job: with AI agents, the work is deciding what to build, directing the agent and shipping it. Each track starts from a template and ends with a project on a real URL.
OutcomeAI Engineer / ML Ops role
AI & ML Engineering
n8nJupyterPythonQdrantGPU on demandLLMs
Train, fine-tune and serve models on GPUs taken on demand, and ship them as working AI products.
they build
- A retrieval (RAG) assistant over course material, served as a live API
- A model fine-tuned on a GPU for the hours the job needs, then released
- An n8n workflow where AI agents do a real task end to end
OutcomeFull-Stack Developer role
Full-Stack Development
code-serverPostgreSQLMongoDBValkeyPublic URL
Design an app, direct AI agents to write most of it, then review, test and ship it on a real domain.
they build
- A complete web app with sign-in and a database, live on its own URL
- An API another team’s app actually calls
- The same app rebuilt with an AI agent, and a write-up of what changed
OutcomeCloud Engineer role
Cloud Engineering
Linux machinesManaged databasesObject storageCustom domainsSnapshots
Run services the way a cloud team does: machines, databases, storage, domains and backups, sized to the load.
they build
- A service deployed across its own machine, database and storage
- A custom domain with HTTPS, pointed and certified
- A snapshot taken, the machine broken on purpose, then restored
OutcomeDevOps / Platform Engineer role
DevOps & Platform
DockerGitRouting and TLSScale groupsHealth checksRabbitMQ
Automate how software gets built, shipped and kept running, with AI agents driving the platform over MCP.
they build
- A service that scales out behind one address and back in when the load drops
- A health-checked deploy that takes a failing copy out of rotation
- An agent that deploys and inspects labs through one MCP connection
OutcomeSecurity Analyst / SOC role
Cybersecurity
KaliBurp SuiteExploit labsCTF missionsLinux
Attack and defend real machines in isolated labs, and write up what was found the way a SOC reports it.
they build
- A full CTF mission solved, from recon to flag
- A vulnerable app found, exploited and then patched
- An incident write-up a security lead could act on
OutcomeEmbedded / IoT Engineer role
Embedded & IoT
ESP32ZephyrBuildrootU-BootNode-RED
Build firmware and device software in the browser, and connect devices to dashboards that run in the cloud.
they build
- A Zephyr firmware image built and flashed
- A custom Linux image from Buildroot, booting through U-Boot
- Sensor data flowing into a Node-RED dashboard on a public URL
what learners walk away with
- Live projects on a real domain
- Scores from quizzes, the code arena and CTF missions
- A workspace that holds the whole semester’s work
- Roadmap progress kept per student
- Templates they can fork and take further
- Experience directing AI agents to build, not only typing code
- A portfolio of live projects to open at a placement interview
- Everyday fluency with Linux, Git and the command line
Give Your Faculty Their Time Back
Run Practical Learning at Institutional Scale.
Setup
Zero IT Setup
No lab room to build and nothing for IT to maintain: every lab runs on the platform.
Ready to Launch: Lab environments students open directly from the browser. No hardware to buy.
No Installation: Start learning immediately — no local software, no OS dependencies, nothing to install per machine.
Easy to Scale: Deploy the same template across batches and departments. A new cohort starts in minutes.
Technical specs
- Platform
- 165 s from click to serving
- Workspaces
- Linux with root, SSH and a desktop
- Storage
- Persistent, per student
- Isolation
- A machine per student
In one line
A platform in 165 seconds, and no lab PC to maintain.
Management
One console, every batch
Departments, batches and cohorts are administered from a single place.
Departments: A department per course, with its own admins and its own enforced limits.
Cohorts: Assign a template to a batch, and every learner starts from the same machine.
Limits that hold: Storage, machine and workspace limits are enforced per department, so a batch cannot use more than it was given.
Technical specs
- Hierarchy
- Organization → department → members
- Provisioning
- Template-driven, per cohort
- Quotas
- Enforced per department
- Access
- Your identity provider, your roles
In one line
One department per course, one template per batch.
Evaluation
Assessment that runs the code
Submissions are compiled and run against real test cases, on your own server.
Code arena: Problems run against real test cases, scored the same way for everyone.
Quiz bank: Question banks per subject, marked automatically.
CTF flags: Missions and timed events with a live scoreboard, kept per person and per team.
Technical specs
- Execution
- Isolated per submission
- Languages
- 40+ in the Code Arena
- Scoring
- Identical for every attempt
- Integrity
- Assessment unreachable from MCP
In one line
Marks come from what ran, not from what was pasted.
Reporting
Evidence, not spreadsheets
The record builds itself as the work happens.
Progress per learner: Roadmap progress, quiz scores and arena results, per student and per department.
Data export: The record is yours, exported from the platform whenever you need it.
Per-person history: What each learner built, when, and what it scored.
Technical specs
- Granularity
- Learner, department
- Export
- Built in
- Ownership
- Your data, on your platform
- Retention
- Kept for the whole programme
In one line
Progress is recorded as students work, not assembled afterwards.
Mentoring
AI answers from your own material
With an AI key configured, questions are answered against the institution’s own syllabus and notes.
In the course: Learn answers from your syllabus and notes rather than from the internet in general.
In the forum: Discuss gives each student a feed of what is relevant to them, with AI replies alongside people.
Optional: Without a key those answers are simply unavailable, and everything else still works.
Technical specs
- Needs
- An AI key you configure
- Grounding
- Your syllabus and material
- Where
- Learn and Discuss
- Faculty load
- Fewer repeated questions
In one line
Answers from your own material, when you switch it on.
How a course splits its time: 70% on real machines, 20% with peers, 10% on guided material.
70%
Hands-on Practice on Real Machines
Real skills on real machines, not slides. Every student works on their own Linux workspace, with Git, databases, routing and the tools the course uses.
20%
Collaborative & Peer Learning
Discuss gives each course a forum, and CTF gives it clans and timed events, so students solve problems together.
10%
Guided Learning
Roadmaps and a syllabus lay the course out in order, with AI answers from your own material when you switch them on.
NAAC / NEP Alignment
Evidence your IQAC can use. Recorded as students work.
Progress, scores, events and hosted projects are kept on the platform as they happen — not assembled after the fact — and they support the NAAC criteria below.
Criteria IITeaching-Learning
Workspaces used, roadmap progress, quiz and arena results — recorded per student as the course runs.
recorded as it happensCriteria IIIResearch & Innovation
Hackathons and CTF events, their teams and scoreboards, and the projects students published on real URLs.
recorded as it happensCriteria VStudent Progression
Each student’s scores and hosted projects, kept on the platform and exportable at any time.
recorded as it happensData export is built in, so the record leaves with you whenever the IQAC asks for it. No consultant, no retrospective reconstruction.
Outcomes By Stakeholder
Different leaders. Different wins. Same platform.
Everyone who runs a college gets something different from the same platform — not just the computer science department.
RolePrincipal / Management
- Practical labs for every course, without building a lab room
- Students reach their machines from home, hostel or campus
- CTF events and hackathons on the same platform
- Progress and scores kept per student
- Your own domain and your own sign-in
165 sfrom click to a serving platform
RoleHead of Department
- A department per course or batch
- Limits on members, storage and machines, enforced
- One template per subject, the same for every student
- Faculty as department admins
- Progress per student and per batch
1department per course, with its own limits
RoleFaculty
- Publish a lab once; the whole batch starts from it
- Quizzes and a code arena that mark themselves
- CTF missions with a live scoreboard
- An agent can prepare the lab, but never mark it
- The same machine as the students, for practice
114+templates to start a course from
RoleIT / Finance
- No lab PCs to buy or patch
- Billed by the machine, not per student
- Our bare metal or your own server
- Students sign in with the account they already have
- Data export and erasure built in
0per-student fees
One Platform. Multiple Capabilities.
What you’d buy separately. What you get here.
Everything your institution needs for practical learning, assessment and cloud labs, on one platform.
| What you need | What you’d buy separately | Typical Cost | What you get with our platform |
|---|---|---|---|
| Workflow automation | Separate automation tools (e.g. n8n, cloud services) | Multiple subscriptions | n8n and Node-RED as templates in the store |
| Learning roadmaps | A separate learning management system | Another licence | Roadmaps and a syllabus in the Learn module |
| Coding practice & assessment | External coding practice platforms | Multiple tool licences | Quizzes and a code arena in the Evaluate module |
| Linux labs in the browser | Separate cloud infrastructure | Infrastructure + setup | A persistent workspace per student |
| Progress & scores | Standalone assessment tools | Multiple subscriptions | Progress kept per student and per department |
| Competitions & events | A separate CTF or contest platform | Additional tool costs | CTF missions, clans, events and a leaderboard |
One platform gives your institution practical labs, assessments, progress tracking and events together — one sign-in, one bill, billed by the machine rather than by the student.
Next steps for your college
- Pick the first course and the batch that will use it
- Decide: your own server, or a dedicated machine of ours
- Publish the course template and add the students
Start with one course.
Prove it in one semester.
Start with one course and one batch. Once it is working — students on their own machines, labs published once, progress on record — add departments across the campus, with no per-student fee.