AI built for learning design.
Lira Studio helps instructional design, eLearning, and curriculum teams translate project goals into clear, connected learning plans so the instructional direction is established before authoring and production begin.
The hardest work happens before authoring.
Teams have to turn goals, learner needs, source material, and subject-matter expertise into a clear learning plan. The decisions behind that plan are easily lost across people, meetings, documents, and tools. Generic AI tools can generate content, but they do not understand the learners, the project, or the decisions you have made.
People make the instructional decisions together.
Lira gives those decisions structure and gives the team one shared place to build, review, and refine the work. Guided AI supports the process while keeping the project context connected through to production.
1. Input Context
Goals, learners, requirements, source material, delivery context.
2. Build Structure
Components, approach, objectives, content, activities, competencies/standards.
3. Design Learning
Human judgment, guided AI, team feedback, quality checks.
4. Export Learning Plan
Structured exports for authoring, development, and delivery.
Our AI is governed by learning science.
Lira uses learning goals, learner readiness profiles, instructional strategy guidance, delivery context, and adaptations for specific learner populations to govern AI generation and review. This guidance is built from peer-reviewed research and trusted educational sources, and users can review the evidence behind it.
Grounding the AI in this shared context helps reduce unsupported or inconsistent outputs, improve the quality and coherence of the work, and cut the time teams spend rewriting and reconciling content across a project. Your team remains in control of the design decisions throughout the process.
OPENING IN BETA
Be among the first to use Lira Studio
Lira Studio is inviting instructional design, eLearning, publishing, and curriculum teams to preview the platform and test emerging workflows.