Production AI for K-12 platforms, after-school tutoring apps, university copilots, and learning operators. Teach-back loops that force active recall, voice-first explain-it pipelines with sub-five-second feedback, kid-safe guardrails by default, and a parent dashboard that turns a sticker chart into evidence.
We have shipped against this shape with K-12 learning apps, after-school tutoring platforms, university student copilots, and corporate L&D operators. The shape repeats.
The fix is not a more polished avatar. The fix is the eval suite underneath, the voice pipeline that does not break for accent-heavy speech, and the parent visibility that turns parents from skeptics into evangelists.
A drilled fact a six-year-old learns becomes a foundational belief. An LLM that confidently says the wrong thing once creates a misconception that costs years to unlearn. The eval bar is unforgiving.
Sticker charts and 'time on app' are not learning. Parents pay for results and need to see what their kid mastered tonight, in plain language, with evidence the AI is not making it up.
Markets outside English-first geographies want the tutor in their language, on their curriculum, with their grade-level pedagogy. Most AI tools fail this on day one and lose the deal.
Eight-week engagements, kid-safe by default, eval-gated releases, and a deployment shape your COPPA reviewer can sign off on.
A Feynman-method teach-back loop that forces active recall. Kid explains, AI evaluates, kid refines, mastery scored.
Curriculum-validated golden sets, hallucination scoring on facts kids will remember, safety red-team on every release.
Kid explains by voice, gets a written + spoken feedback report in under five seconds. Accent-aware STT, grade-tuned TTS.
Input + output guardrails that block PII, off-topic prompts, and any attempt to socialize the AI as a friend. Tutor only, never chatbot.
Per-session learning evidence, weekly summary that names what the child mastered, and weak-area alerts the parent can act on.
One-week audit of your edtech-AI stack. Eval shape, voice pipeline, guardrail posture, parent-visibility data model — all named in writing.
Most engagements bundle two: a tutor build (01, 03) paired with the discipline that keeps it credible (02, 05). Bring the shape closest to your blocker.
Scope your engagement →Want to see the K-Framework discipline behind every item? Read the K-Framework.
Tools that already pass kid-safety reviews. Voice on the edge where latency matters, cloud where flexibility wins.
The store, the index, the search
Embeddings, providers, fallbacks
The eval bar, the cost meter, the drift alarm
Type-safe everything
iOS + Android, native or cross
Whatever your infra already runs
Voice explanation to feedback report
Curriculum-aligned eval coverage
Bilingual voice + UI from day 1
Kid-safety default for production
Eight weeks, fixed scope, eval suite + kid-safety review at handoff. Direct LLM engineering on top of the K-Framework. Two Q3 slots remain.
