A Learning Intelligence Platform — outcome metrics for how students think
Pragnya Analytics measures, improves, and proves how well students think — not just what they study. We deliver outcome‑verified learning for schools (Grades 6–10) using learning intelligence diagnostics, mentor‑led cohorts, and retention/transfer measurement over time.
Not a video‑content platform. Not exam‑drill focused. Not self‑paced only. Not a generic AI tutor.
Thesis: learning outcomes need a better unit of measurement
Why content-heavy edtech fails
Content and engagement are weak proxies. Schools need evidence of understanding, retention, and transfer — the capabilities that matter beyond exams.
Why now
With better diagnostics and responsible ML, we can model learning behavior at scale — but outcomes still require mentors to change thinking, not just recommend content.
What Pragnya enables
Pre/post learning intelligence baselines, mentor-led cohorts, and retention checks that prove whether learning stuck and transfers.
Market Opportunity
Initial wedge: progressive schools (Grades 6–10) that want measurable thinking outcomes, not just marks. Expansion: parents of high-potential underperformers and broader education programs where outcome proof drives adoption.
Business Model
Paid school pilots (baseline → cohort → post checks), cohort programs, and annual subscriptions for learning intelligence measurement + reporting.
Traction
- Pilot-ready delivery: diagnostics + cohorts + outcomes reporting
- Early cohorts with mentors and feedback loops to refine interventions
- Assessment library and learning intelligence framework under active iteration
Learning Intelligence metrics (definitions)
Our core innovation is not “AI tutoring”. It’s measuring learning quality, running interventions, and proving uplift with metrics that track durability and transfer.
Concept Transfer Score
A measure of whether a student can apply a concept in a novel context (new wording, constraints, or scenario), without being cued into the pattern.
Retention @ 30/60/90 days
A time-based check that answers: does the learning persist without re-teaching? Retention is treated as a first-class outcome, not a side effect.
Problem‑Solving Depth Index
Tracks reasoning quality: planning, multi‑step structure, justification of steps, and the ability to explain “why”, not just reach an answer.
Learning Velocity Uplift
Measures the rate of improvement after an intervention. It helps distinguish “more practice” from “better learning”, and guides cohort design.
Why this is defensible
Outcome metrics + mentor interventions generate a longitudinal dataset on how misconceptions change, what interventions work, and how retention/transfer evolves. This is a compounding advantage over content-first platforms.
Roadmap
0–6 months
- Standardize the 4-step pilot playbook (baseline → cohorts → post checks)
- Operationalize mentor training and intervention protocols
- Ship school-ready outcome reports (learning intelligence metrics)
6–24 months
- Automate parts of diagnostics and reporting while preserving mentor quality
- Scale pilots across schools with repeatable outcome uplift
- Subscription model for ongoing measurement and improvement cycles
Team & Advisors
Full bios and collaborators are available on the Team page.
Fundraise
We’re raising pre-seed capital to productize learning intelligence measurement, expand mentor-led pilots with schools, and scale go-to-market. Detailed financials available on request under NDA.