Product
Lira AI, up close.
What we see in the classroom, why current patches fall short and what Lira AI does for each role.
The problem
First: understand it.
- Teachers
- They get home exhausted and, instead of resting or being with their families, keep on grading, planning and working through administrative tasks.
- Students
- They understand less and less: the thinking process weakens, copy-paste grows, and learning turns into repeating answers without thinking.
- Institutions
- They sit in the middle of everything: they need better outcomes, but they decide with thin data, fragmented information and no clarity on what to do first.
- Families
- They were left outside. They find out late and by result: a number at the end of term, or a phone call once the problem is already big. They want to help, but they have nothing to hold on to.
It isn't a lack of commitment. It's a saturated system. Lira isn't here to paper over it: it's here to understand it and fix it at the root.
How it is addressed today
Solutions that relieve, but do not solve.
- Students
- They use ChatGPT and other AI tools to answer fast. The result: assignments get finished, but the mental work is outsourced. They can complete everything and understand almost none of it.
- Teachers
- Today they lean on tools to plan and organize, but the model doesn't change: they still design content and grade results, with no visibility into the student's process. Technology assists, but it doesn't free them.
- Institutions
- Today they run on spreadsheets, dashboards and disconnected reports. There is data, but no trace of the learning process: they see the final result, not how it was built. They act, but late and blind.
- Families
- Today they have the report card, the grade sheet and the absence notice. It all arrives after the fact, and it tells them what the mark was but never how their kid got there. Data about the result, none about the process.
The system isn't standing still: it's full of solutions. But they all share the same limit — they solve parts, not the problem. Tools aren't missing; what's missing is an ecosystem that makes learning stronger.
The proposal
What Lira AI does for each role.
Students
Understand, practice and see the next step.
Lira supports the work with questions and hints, builds practice from the course material and shows where the person stands: no percentage, a next step.
- A hint ladder: it starts with the smallest hint and goes up if needed.
- The direct answer can be requested; it is not hidden.
- Tailored practice from the task or the teacher's notes.
Example · fictional data
Teachers
Create materials and support processes.
Materials, activities and assessments from the syllabus, which the teacher reviews before publishing. And a view of where the group got stuck, not only of who turned things in.
- Drafts that are reviewed and edited before reaching the class.
- The teacher keeps the judgment and the final say.
- Visibility into the process, not only the final result.
Example · fictional data
Families
The context the institution enables.
Families access their student's process with the scope each institution defines. It is not an individual door: it is linked through the school.
- How they are working, not only the grade.
- The institution defines the scope.
- Access is enabled through the link with a student.
Example · fictional data
Institutions
School operations and learning signals together.
Attendance, grades and signals per class in the same place where learning happens, with roles and scopes for everyone on the team.
- Attendance from the phone, with no intermediate spreadsheet.
- Grades entered once, available to whoever needs them.
- Signals with a denominator: "3 of 24", not "3".
Example · fictional data
Want to try it?
We are forming a first cohort of students and teachers aged 18 or over.