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Case study · EdTech

Mockinto · EdTech · Series A

An AI interviewer that actually adapts to the candidate.

A multi-turn interview agent that adjusts difficulty in real time, scores answers against a rubric, and gives structured feedback in under two seconds.

47%lift in user completion rate

At a glance

Client
Mockinto · EdTech · Series A
Headline metric
47% lift in user completion rate
Deliverables
4 shipped to production
Stack
4+ tools across the build

The challenge, approach & outcome.

  1. Challenge

    Generic mock-interview tools didn't adapt to skill level, drained engagement after 2–3 sessions, and gave shallow feedback. Mockinto needed an interviewer that felt like a senior engineer in the room — not a chatbot answering scripted questions.

  2. Approach

    Built a Claude Sonnet agent with a domain-aware question bank, real-time difficulty adjustment based on answer scoring, and a structured feedback rubric grounded in RAG over their playbook. Shipped on Flutter with streaming responses and a custom eval harness covering 1,200 reference answers.

  3. Outcome

    47% lift in user completion, 3.1× average sessions per user, and the platform's first paid tier crossed $200k ARR within 90 days. Sub-2s p95 from question to feedback.

lift in user completion rate
47%
average sessions per user
3.1×
p95 from question to feedback
<2s

Deliverables

What we shipped.

  • Multi-turn interview agent
  • Custom eval harness
  • Flutter SDK
  • Admin dashboard

Stack

The tools we used.

  • Claude Sonnet
  • RAG
  • Flutter
  • Streaming

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