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A personal STEM tutor for every student.

MindNova is an AI tutor combined with a live physics simulation lab — an end-to-end learning platform that teaches American K-12 students to think like engineers, not memorize like test-takers. We close the STEM gap by making world-class tutoring available to every student for the price of a Netflix subscription.

The opportunity

The United States faces a 3.5 million-job STEM shortfall by 2027. Two-thirds of 8th graders fall below basic math proficiency. Private tutoring at $150/hour is out of reach for 80% of families. AI in K-12 EdTech is a $5.2B segment growing 39% per year, and almost no one is doing it well. The category leader for AI tutoring — Khanmigo — has wide reach but shallow depth. The category leader for STEM rigor — Brilliant — is adult-only. MindNova owns the unowned quadrant: deep AI personalization × deep STEM simulation.

What we built

A platform of 11 integrated modules spanning a Socratic AI tutor, a live physics simulation lab, an adaptive difficulty engine driven by 30+ behavioral signals per student, a teacher intelligence dashboard, gamified mastery (XP, streaks, badges), and a built-in Women-in-STEM career track. The MVP is in active development; the working tutor and three physics simulations are running today. Domain mindnova.academy is secured. Founder is on the EB-2 NIW immigration path.

Proof points

The ask

We are raising a $1.5M seed round to fund an 18-month runway from MVP to $1M ARR (Q3 2027), with Series A planned Q1 2027 against 50 contracted schools. Plan reaches operating break-even in 2028 and $3.8M ARR by year-end 2028, scaling to ~$7M ARR by 2030. Funds deploy across product (50%), growth and pilots (35%), and curriculum/compliance/operations (15%).

Investment Highlights

Why Now

• AI inference cost collapse. GPT-class tutoring that cost $5/student/hour in 2022 now runs at sub-cent margins. The unit economics for free-tier STEM tutoring only became viable in 2024–2026.
• Teacher shortage is structural. 55,000 STEM teacher vacancies across U.S. K-12. Schools must adopt AI augmentation or lose the next generation of engineers.
• Federal urgency. The CHIPS Act, NSF priorities, and DOE workforce programs all flag the same gap. Title I funding plus Women-in-STEM grants create the policy tailwind.
• Parental willingness-to-pay. Post-pandemic learning loss has parents actively shopping for after-school AI tools. The $15/month price clears every objection.

Who we are.

Corporate Profile

Mission

To give every American student a world-class STEM tutor — and to close the gender gap in engineering by building Women in STEM into the product from day one.

Vision

To become the default AI learning platform for STEM in American K-12 — the system that teaches the next generation of engineers, scientists, and innovators to think, not memorize. Long-term, MindNova is the workforce pipeline for the country's most strategically important industries: semiconductors, clean energy, aerospace, biotech.

Values

• Teach, don't test. The product refuses to give answers. It teaches reasoning.
• Teachers first. Every product decision starts with: does this make a teacher's job easier?
• Earned trust. No hype, no shortcuts on safety. FERPA, COPPA, and parental consent are non-negotiable.
• Equity by design. Women in STEM is not a feature flag — it is a foundational track.
• Ship and learn. Weekly classroom feedback loops. Annual product overhauls based on what teachers actually use.

Company History

Product Lines

1. MindNova for Students (B2C — primary revenue line)

The student-facing platform: AI Socratic tutor, simulation lab, adaptive learning engine, mastery dashboard, gamified XP and streaks, Women-in-STEM career tracks. Web-first MVP launching Q2 2026; iPad app Q3 2026; full mobile Q4 2026. Freemium with $15/month Plus tier.

2. MindNova for Teachers & Schools (B2B)

Teacher dashboard with class roster, mastery tracking, at-risk-student alerts, AI-generated lesson differentiation, and automatic standards alignment (NGSS, Common Core). Free for individual teachers. School-tier pricing at $5/student/month (minimum 50 students = $250/month). Title-I funding eligible — schools pay nothing out of pocket.

3. MindNova for Workforce (Corporate L&D)

STEM workforce pipeline product for enterprise sponsors. Designed for aerospace, defense, semiconductor, and clean-energy companies that fund internship and pre-hire training programs. $50/seat/month. Launches Q1 2027 via inbound from corporate sponsors of school pilots. No customer commitments to date.

Intellectual Property

Proprietary tutor prompt library + Socratic question trees + hint ladders covering ~1,400 STEM concepts (grades 6–12). Browser-native simulation library (physics, electronics, energy-systems). Bayesian student-model architecture using 30+ behavioral signals. MindNova™ trademark applications in process (U.S. classes 9, 41, 42). Domain mindnova.academy secured.

Governance, Cap Table (Post-Seed) & Operations

Post-seed cap table: Founder Rozlana Yergaliyeva 72% · Seed investors 20% · Employee stock option pool (ESOP) 6% · Technical advisor 2%. Operations: U.S.-based once founder relocation completes via EB-2 NIW. Remote-first engineering team during seed phase; curriculum and partnerships team U.S.-based to enable in-person district relationships and conference presence (NSTA, ASCD, ISTE).

America has a STEM crisis.

Four broken loops

Loop 1 — The student can't get help when they need it.

A 7th grader hits a wall on quadratic equations Tuesday night. The teacher is unavailable until Friday's office hours. The parent doesn't remember the method. By Friday, the student is two lessons behind and has internalized "I'm bad at math." This compounds every week for the next eight years. The single biggest cause of the STEM dropout funnel is not capability — it is the latency between confusion and help. Today, that latency is days. With MindNova, it is seconds.

Loop 2 — The teacher is grading instead of teaching.

The average U.S. middle-school STEM teacher spends ~11 hours/week grading and ~6 hours/week on differentiation planning — time that should be coaching. With 55,000 vacancies and rising class sizes, the system is structurally incapable of giving every student individualized attention. AI must absorb the grading and differentiation load so teachers can do what only humans can do — mentor.

Loop 3 — The family can't afford one-on-one tutoring.

Wyzant and Tutor.com pricing averages $150/hour. The Khan Academy + Brilliant + IXL bundle costs ~$50/month but offers no personalized tutoring depth. The result: affluent families buy tutors; everyone else is left behind. The STEM gap is fundamentally a tutoring access gap. AI tutoring at $15/month closes it.

Loop 4 — Girls leave STEM at the middle-school transition.

Only 26% of U.S. engineers are women. The leak point is well-documented: 6th–8th grade. Girls report the STEM subjects feel "for boys" because the teaching examples, role models, and career pathways shown to them are dominated by male engineers. This is not a pipeline problem at the university level — it is a representation problem in the textbooks at age 11. A platform that surfaces female engineers and women-in-STEM career narratives natively in the curriculum is the highest-leverage intervention available.

Why existing solutions fall short

The cost of inaction

For the student

Compounding learning loss. By 11th grade, a student who fell behind in 7th-grade algebra has typically been counted out of STEM tracks entirely. The lifetime earnings cost of dropping out of the STEM pipeline at age 13 is estimated at ~$1.2M per student.

For the teacher

11 hours/week of grading. Six hours of differentiation planning. Burnout rates above 50% within five years of credential. The system is producing the teacher shortage by overworking the teachers it has.

For the country

3.5 million unfilled STEM jobs by 2027. Strategic competitiveness in semiconductors, clean energy, AI, biotech — all tied to a domestic STEM pipeline that is leaking at the K-12 layer. CHIPS Act money does not produce chip engineers if 7th graders quit math.

For girls

The gender gap in engineering compounds across decades. Every girl who is told (implicitly) at age 11 that engineering "is not for her" is a loss to the field, the economy, and to her own lifetime trajectory.

A personal STEM tutor for every student.

MindNova is six integrated products in one platform — an AI Socratic tutor, a live simulation lab, an adaptive engine, teacher intelligence, gamified mastery, and a Women-in-STEM track. Together they form the first end-to-end AI learning system built specifically for the K-12 STEM crisis.

The six pillars

The student experience

A 9th grader opens MindNova at 9 PM, stuck on conservation of momentum. She types: "why does the heavier car push the lighter car backward?" The tutor replies not with an answer, but with a question: "Let's start with what you already know. If two cars collide and one stops moving, what happened to its energy?" She thinks. Tries an answer. The tutor responds with a graduated hint, then drops her into a live simulation: two carts on a frictionless track, mass sliders on each. She drags the masses. Watches what changes. Five minutes later she understands momentum conservation — not as a formula, but as a thing that is true about the world. She earns 40 XP, hits a 7-day streak, and the platform suggests she try the next concept: collisions in 2D.

That is the product. That is the loop we are scaling.

The teacher experience

A 7th-grade physical-science teacher in a Title-I middle school opens MindNova Monday morning. Her class roster shows all 28 students. Three are flagged red: at-risk based on last week's work patterns. She clicks one — Marcus, falling behind on equations. MindNova shows her exactly which concept Marcus is stuck on (cross-multiplication), what hints he has tried, and recommends a 15-minute small-group intervention with two other students at the same gap. She does not grade a single worksheet. She runs the intervention. By Friday, Marcus is back on track. The platform did not replace her — it gave her superpowers.

The 11-module platform architecture

Product Tiers & Pricing

Workforce (Corporate L&D)

Workforce — $50 / seat / month. Internship and pre-hire training tracks. Branded portal. Skills-passport export. Reports to corporate L&D leader.

Built to teach, not test.

System architecture (high level)

The Socratic AI architecture

Six-step pipeline per turn:

1. Student utterance arrives (chat, voice, or worked solution).
2. Concept grounding + state retrieval — active concept identified from the ~1,400-node graph; mastery state, prior attempts, hint history loaded.
3. Refuse-to-answer prompt — Socratic posture: ask questions, offer 4-level graduated hints, never directly answer until exhausted.
4. Curriculum retrieval (RAG) — relevant passages + worked examples retrieved.
5. LLM generation + validation against safety + grounding checks.
6. Mastery update + next-best-action — student model updated; next concept or simulation surfaced.

Unit cost. ~$0.04 / tutor session (5–10 turns) · ~2 sec P50 latency · 82% gross margin at scale · 99.5% uptime target.

The adaptive engine

The student model is a Bayesian knowledge-tracing layer with 30+ behavioral signals: response correctness, time-to-respond, hint usage, retry pattern, simulation interaction depth, emotional valence in language, error type, prior concept mastery, day-of-week activity, streak status, and many more. The next-best-concept selector is a contextual bandit that balances learning growth against engagement (frustration risk). Every student carries a private model that improves the platform's recommendations specifically for them — and the aggregate population model improves the platform for everyone.

The simulation engine

Browser-native, no plugin, no install. Built on WebGL with a deterministic physics layer so simulations are reproducible and testable. The first three simulations (kinematics, electrical circuits, energy conservation) ship at MVP. The roadmap expands to ~25 simulations across mechanics, electromagnetism, thermodynamics, wave physics, and chemistry by end of 2027.

Compliance & Safety Architecture

• FERPA-compliant data model — student PII isolated, row-level security, audit logging on every read of student data, district-level data residency support.
• COPPA-compliant onboarding — verifiable parental consent flow for users under 13, no behavioral advertising, no data sale, ever.
• SOC 2 Type II — engagement begins Q4 2026, target completion Q3 2027.
• AI safety — refuse-to-answer prompting, curriculum-grounded retrieval, weekly red-team prompts run against tutor, teacher review queue for flagged interactions.
• Bias audits — adaptive engine outputs audited quarterly for disparate impact across demographic groups.
• Accessibility — WCAG 2.2 AA compliance, screen-reader support, dyslexia-friendly typography option, high-contrast mode.

Engineering practices

• Two-week sprints, daily standups, Friday retro.
• Trunk-based development with feature flags. No long-lived branches.
• Pre-commit hooks for lint, type-check, secrets scan.
• End-to-end test suite for critical learning flows (tutor → simulation → mastery update).
• Observability: structured logs, error tracking, learning-analytics pipeline.
• Weekly classroom feedback loops — teachers tag interactions that worked or did not.

Technical risks & mitigation. LLM provider outage → multi-provider gateway (OpenAI, Anthropic, Google) with auto-failover. Hallucinated concept → curriculum-grounded retrieval, mathematical correctness checks, teacher review queue. Weak Chromebook performance → WebGL with graceful 2D-canvas fallback. School Wi-Fi blocks API → Cloudflare edge proxy with school-friendly IP range. Data residency → multi-region storage Year 2; district-level isolation opt-in.

$83B market growing 39% per year.

U.S. K-12 EdTech is the world's largest education market. The AI segment is the fastest-growing slice — and almost no one is doing it well. MindNova owns the unowned quadrant: deep AI personalization × deep STEM simulation.

Market sizing

Market scale at a glance

Market growth drivers

• AI inference cost collapse. Per-token LLM costs have fallen ~50x since 2022, making free-tier and freemium economics viable for the first time in K-12 EdTech.
• Teacher shortage. 55,000 STEM teacher vacancies. Schools must adopt AI augmentation or lose the next generation of engineers.
• Federal urgency. CHIPS Act, NSF priorities, DOE workforce programs all targeting the same STEM pipeline gap.
• Title I + ESSER capacity. $18B/year in Title I funding, with AI tutoring an explicit allowable use.
• Parent willingness-to-pay. Post-pandemic learning loss has parents shopping for after-school AI tools — $15/month is impulse-buy territory.

Customer Segmentation

Segment 1 — The engaged student / parent (B2C, primary 2026)

Segment 2 — The classroom teacher (acquisition layer, free forever)

Free teacher tier is the lead-generation engine. 200 teachers in 2026 means 6,000 students touched. Teachers are not the customer — they are the channel.

Segment 3 — The school district (B2B, primary 2027)

Segment 4 — The corporation (B2B Workforce, 2027+)

Beachhead + geographic expansion

Beachhead is two-pronged: (a) STEM-strong metros (Seattle, SF Bay, Austin, Boston, Research Triangle) — highest parent willingness-to-pay; (b) Title-I districts — equity argument matches funding source. Expansion: 2026 national B2C web-launch + 5 pilot districts (WA/CA/TX); 2027 national + 50 paying districts (inside sales + NSTA/ASCD); 2028 200 districts + 5 corporate partnerships (channels + state RFPs).

Industry macro trends

The post-pandemic learning loss is permanent without intervention

NAEP data shows that the 2024 8th-grade math cohort is approximately 1.5 grade-levels behind the 2019 cohort. Without AI-personalized intervention, this cohort will carry the gap into the workforce. Schools are buying urgency; parents are buying remediation.

Teacher attrition is structural

NEA reports STEM teacher attrition at ~17% per year. With 55,000 vacancies and rising class sizes, the system structurally cannot meet K-12 STEM demand without AI augmentation. This is no longer a "nice to have" — it is infrastructure.

The CHIPS Act consequence

The CHIPS and Science Act allocated $52B to semiconductor manufacturing and $200B+ for STEM research. The unaddressed bottleneck is talent — fabs need engineers and the pipeline starts in 7th-grade algebra. Federal stakeholders are explicitly searching for K-12 interventions to fund.

Corporate workforce L&D dollars are repositioning

Companies that historically funded only their own L&D are increasingly funding K-12 STEM pipelines through corporate foundation programs. Multi-million-dollar programs exist across aerospace, defense, and semiconductor foundations — MindNova is positioned to apply as a distribution partner in 2026–2027.

The "screen time" backlash favors purposeful EdTech

Parents are increasingly hostile to attention-extraction apps (TikTok, gaming) but actively supportive of learning apps — even mandating them. Schools are banning phones in class but actively buying Chromebook-based learning software. MindNova rides the favorable side of this divide.

Regulatory tailwinds

• Title I funding — federal money explicitly allowable for AI tutoring purchases.
• ESSER carryover — pandemic-era recovery funds still active through 2026–2027 in many districts.
• State AI-in-education frameworks — California, Virginia, Ohio publishing AI-in-classroom guidance; MindNova's compliance-first architecture is positioned to lead.
• NSF AI Institutes — direct research and pilot funding for AI-in-education partners.
• Women-in-STEM federal grants — NSF ADVANCE program and related federal initiatives allocate tens of millions annually to closing the gender gap in engineering. Female-founded + female-focused product is a structural advantage in this pool.

Four revenue streams. One platform.

Revenue streams

1. B2C Subscription (Primary, 2026–2028)

Student / parent subscription at $15/month. Freemium funnel: 3 tutor sessions per day free, unlimited at $15. Teacher referrals drive blended CAC to ~$15. This is the largest line in the 2028 plan ($2.7M).

2. B2B Schools (Primary B2B, 2027–2028)

School / district subscription at $5/student/month, minimum 50 students = $250/month per school. Title I and ESSER funding eligible — schools pay nothing out of district pocket. Sales cycle is slower (6–12 months) but ACVs are large and retention is high (~95% logo retention typical for school SaaS).

3. Corporate L&D (Workforce, 2027+)

$50/seat/month for enterprise workforce-bridge product. Aerospace, defense, semiconductors. Initial deals expected via inbound from companies that sponsor school pilots in their hiring geographies. Higher ACV per logo ($60K+ for a 100-seat deployment), used as a corporate workforce-development investment.

4. Non-dilutive grants (target programs)

All grant amounts conditional on competitive award. Plan does not depend on any single grant.

Pricing strategy

Pricing is set deliberately below comparable consumer learning tools (Brilliant $24/mo, Khan Premium $44/mo). Three reasons: (1) Cost structure permits it — $1.20/sub-month variable cost on $15 revenue. (2) Family affordability is the unlock — $25+ triggers a household budget conversation. (3) Land-grab dynamics — first to 100K paying students owns the category; revisit ARPU 2027+.

Customer acquisition channels

Retention & expansion

• NRR target 115% by 2028 — family-plan sibling add-ons, school full-grade upgrades, Corporate L&D up-tier.
• Gross logo retention: 88% B2C / 95% B2B — streak loops, parent dashboard, teacher-side daily value.
• Expansion: sibling discount lifts household ARPU; teacher leads convert to district contracts; workforce-bridge upsell to corporate L&D.

Sales motion

• Phase 1 — Founder-led (2026). Rozlana cultivates first 200 teachers via Reddit, NSTA, direct outreach. Conversion via in-product usage-limit prompts + parent email.
• Phase 2 — Inside sales (2027). Hire 1 districts partnerships lead. Sell into schools with >20% teacher adoption. Title-I-eligible pricing.
• Phase 3 — Full engine (2028). 3 inside sales reps + 1 enterprise lead. Self-serve B2C + mid-market districts + enterprise L&D.

Customer success & onboarding

• Student day 0. Sign up, choose 2 subjects, 1 tutor session, first 50 XP.
• Student day 7. First streak unlock, parent progress email, first mastery badge.
• Teacher day 0. Free dashboard, roster import (Clever/ClassLink), first AI student insight within 24h.
• School day 0–90. White-glove onboarding: curriculum mapping, FERPA review, teacher PD session.

Teachers first. Then everyone.

The three-phase wedge

Why teacher-led works

• One teacher = 30 student leads. The teacher-to-student ratio is the highest-leverage channel in K-12.
• Teachers are trust intermediaries. A teacher recommendation to a parent converts at ~5× a cold parent ad.
• Teachers are the district decision pre-cursor. Districts buy what teachers already love. Bottom-up adoption is the only path that works in K-12 SaaS.
• Free teacher tier costs us almost nothing. Teachers don't run up usage; they run reports. Marginal cost per teacher is near zero. Marginal student revenue is high.

Channels

• Reddit (r/teachers, r/teaching) — founder-led conversation, free-tier signups. Owner: Founder.
• NSTA + ASCD + ISTE conferences — endorsement + district lead-gen. Owner: Founder + Districts Lead.
• EdSurge content + founder articles — thought-leadership. Owner: Founder.
• TeachersPayTeachers + NEA — cross-promotion to ~7M teachers + policy alignment. Owner: Growth Marketer.

Sales plays by segment

Teacher onboarding — "The 5-minute setup" play

1. Open: Reddit post / conference booth / direct DM offering "free AI lab for your STEM class."
2. Setup: Clever SSO import → roster live in 5 minutes.
3. First win: AI generates a differentiated worksheet for tomorrow's class within 24 hours.
4. Habit: Weekly mastery summary delivered Sunday evening — teacher uses it Monday morning.
5. Conversion: Teacher's students hit free-tier limits → parent email → $15 subscription.

Parent conversion — "The patient tutor" play

1. Trigger: Free-tier student hits 3-session daily cap.
2. Email: Parent receives a progress report — what their child mastered, where they got stuck, what's next.
3. Offer: 7-day free Plus trial. No card required.
4. Activation: First Plus week shows full simulation access + adaptive engine engagement.
5. Convert: $15/month, easy cancel, 70%+ retention through month 3.

District sales — "The Title-I" play

1. Open: Conversation with curriculum director, opened by teacher adoption data ("12 of your teachers already use this").
2. Compliance pack: FERPA, COPPA, district-tailored DPA delivered in one PDF.
3. Pilot: One school, one grade, 60 days. Measured on engagement + mastery growth.
4. Expand: Pilot results → district-wide contract. Funded through Title I or ESSER.

Geographic rollout plan

2026 — National web launch + 5 pilot districts

National B2C reachable from day one. District pilots concentrated in WA, CA, TX where teacher adoption density is highest. Founder-led district conversations.

2027 — 50 districts + Series A

Add inside-sales SDR (1) and Districts Partnerships Lead (1). Open OR + CO + MA + VA. Series A timed to district expansion proof.

2028 — 200 districts + corporate L&D launch

Sales team scales to 3 inside + 1 enterprise. Workforce-bridge product launched. Corporate sponsorships fund additional school pilots.

Marketing mix & budget

Brand & content strategy

Voice: teacher-first — language of the classroom, not the SaaS conference stage. Content shows real teachers reclaiming evenings, students hitting "I get it!" moments, parents seeing confidence return. Never lead with the LLM name; never use "disrupt." Mastery, time saved, outcomes. Channels: weekly founder LinkedIn/X · YouTube "5-min simulation lab" series · TikTok/Reels student + teacher wins · monthly EdSurge guest articles · weekly teacher Substack. Owned media: mindnova.academy (SEO on "AI tutor middle school," "Khan Academy alternative") · public efficacy dashboard · free curriculum library.

Key sales & marketing milestones

Customer engagement cadence. Daily streak emails + tutor reminders · weekly parent progress digest (Sun) + teacher mastery summary (Mon) · monthly product newsletter · quarterly district business review + founder AMA.

MVP today. $3.8M revenue by Y5.

Current build status

• Platform architecture finalized — 11 modules mapped and prioritized.
• MVP in active development — target production deployment Q2 2026.
• Socratic AI tutor prototype functional in development environment (refuse-to-answer prompting design implemented).
• Three physics simulations in QA: kinematics, electrical circuits, energy conservation.
• Domain secured — mindnova.academy.
• Founder relocation to U.S. underway via EB-2 NIW pathway (counsel engaged).
• Curriculum partner outreach initiated.
• Technical advisor onboarded (founder of an early-stage AI ventures studio, 2% advisor equity).
• Brand identity completed — investor pitch deck delivered May 2026.

Next 18 months

Headline forward indicators

Research-stage signals (informal)

• Teacher pain. Founder-led informal conversations with U.S. K-12 STEM teachers (Feb–Apr 2026) consistently surfaced grading burden >10 hrs/week as the top stated time sink — corroborated by published NEA workload surveys.
• Parent willingness-to-pay. Informal pricing-sensitivity conversations with U.S. parents in target metros suggest $15/month is well within the typical household after-school spend, consistent with published Brilliant ($24/mo) and Khan Premium ($44/mo) consumer benchmarks.
• Curriculum alignment. Initial NGSS + Common Core mapping completed for the first ~800 concepts. Top-10-state adoption check in progress.
• Tutor refusal-to-answer. Internal prompt-engineering experiments demonstrate high refusal rate on direct answer requests when system prompt is properly enforced.

All Research-stage signals above are pre-quantitative-study findings, not formal market research. A funded research program is in the Use of Funds (Section 13).

What we're tracking weekly

Product velocity targets

Data asset growth (Y1 → Y3 / Y5). Concept graph ~1,400 → ~3,500; live simulations ~12 → ~40; tutor sessions completed ~120K → ~12M; student-mastery datapoints ~3.5M → ~380M; teacher-tagged interactions ~15K → ~2M.

We own the unowned quadrant.

Competitive landscape

Direct competitors

• Khanmigo (Khan Academy). Category leader by brand; shallow simulation, weak adaptive engine. $44/mo (Khan Premium bundle).
• Brilliant. Beautiful math & science content. Adult-focused; no K-12 workflow; no teacher-side. $24/mo.
• IXL. Massive K-12 base. Drill-and-practice, pre-AI architecture. $10–20/mo per family.
• Carnegie Learning. Adaptive math with research credibility. School-channel only; older architecture.
• Synthesis. Cohort-based; $180+/mo; doesn't scale. Adjacent category.

Indirect competitors

• Human tutors (Wyzant, Tutor.com, Varsity). $50–150/hr — out of reach for most families.
• Legacy publishers (Pearson, McGraw-Hill, Savvas). Thin digital products.
• YouTube + raw LLMs. Free but passive; no personalization, no pedagogy, no progress tracking.

Competitive positioning matrix

Why MindNova wins

1. We own the synthesis quadrant.

The two axes that matter — depth of AI personalization and depth of STEM simulation — are owned by different players (Khanmigo and Brilliant respectively). Neither has both. MindNova is the only platform built natively on the intersection.

2. We are female-founded with Women-in-STEM as product, not marketing.

Rozlana Yergaliyeva is the founder. Women in STEM is module 10 of the platform, not a press release. This unlocks federal grant pools and corporate-foundation programs (NSF ADVANCE and related initiatives) that male-founded competitors cannot compete for on the same terms.

3. We are workforce-aligned.

Our curriculum maps to actual workforce skills (semiconductors, clean energy, aerospace) — which gives us a corporate L&D revenue stream and a sponsored-pilot funnel that competitors lack. Brilliant is adult-only and has no K-12 enterprise motion. IXL has no AI tutor architecture to underwrite a workforce partnership.

4. We are teacher-first.

The free teacher dashboard is our acquisition engine. One teacher equals 30 student leads. Khanmigo has teacher tools but they are secondary to the Khan student brand. Our entire GTM is built on teachers.

5. We are priced for adoption.

$15/month is $9–29 below the comparable consumer alternatives. The price removes the conversion objection for parents and accelerates the funnel.

Moat durability

Defensibility stack. Female-founded + Women-in-STEM unlocks federal-grant differentiation · data flywheel (every session improves the next) · switching cost (mastery state doesn't port) · teacher-led distribution compounds into districts · first AI-native K-12 STEM brand with efficacy data.

Builders who ship.

Leadership

Rozlana Yergaliyeva — Founder & CEO

Visionary behind MindNova. Drives product strategy, curriculum design, and partnerships. Working with U.S. immigration counsel on EB-2 NIW pathway. Deeply committed to closing the STEM gap and empowering women in technical fields. Owns: product vision, curriculum architecture, district partnerships, fundraising, brand.

Technical Advisor — Engineering & AI Build (2% advisor equity)

Founder of an early-stage AI ventures studio. Built and shipped 7+ AI products. Leading the MVP build, AI infrastructure choice, and integration architecture for MindNova. Provides technical leadership through MVP and Series A; transitions decision-making to full-time CTO hired post-Series A. Bellevue, WA.

5-Year Personnel Plan — All U.S.-Based, Full-Time W-2 (Year 1 = 2026)

All personnel are U.S.-based W-2 employees receiving U.S. payroll, paying U.S. federal & state taxes, and counted toward U.S. job creation. Founder serves as full-time U.S.-resident CEO upon EB-2 NIW approval. First-six-month hires (post-seed): Senior AI/ML Engineer, Senior Full-Stack Engineer, Head of Curriculum, Districts Partnerships Lead, Growth Marketer — all Bellevue HQ or U.S. remote.

Designated Salary per Position (U.S. Market Rate, Y1 → Y5)

CEO (Founder): $90K → $180K* · Engineering & AI/ML: $140K → $160K · Curriculum & Product: $95K → $108K · Sales / Districts: $85K → $98K + commission · Customer Success: $78K → $89K · Marketing & Community: $82K → $95K · Operations / Finance / G&A: $85K → $105K.

*Founder receives base salary plus net profit share from Year 3. All salaries based on 50th-percentile U.S. market data (BLS, Robert Half, Glassdoor 2025).

Total Annual Payroll Expense (U.S. Payroll)

Advisors & Board. Technical Advisor — founder of an early-stage AI ventures studio (committed, 2% equity). Education advisor and AI-safety advisor seats targeted post-seed close. Investor board seat reserved for seed lead.

Culture, cadence & compensation

Two-week sprints, daily 15-min standups (async on slow days), weekly founder + advisor sync, monthly teacher-voice review with ~6 teachers, quarterly OKRs, annual mission day. Compensation: below-market cash + meaningful equity (50th-percentile cash by Y2), 4-year vest / 1-year cliff stock options for every hire, full healthcare, $2K annual learning stipend, remote-first. Mission filter is non-negotiable — we hire only people who care deeply about the K-12 STEM gap.

Personnel summary & founder commitment

MindNova reaches 15 U.S.-based full-time W-2 employees by Year 5 (2030), growing from 3 in Year 1. U.S. payroll scales from $312K (Y1) to $1.80M (Y5) — cumulative 5-year U.S. payroll $5.20M. All positions are U.S.-based, paid through U.S. payroll, contributing federal/state/local tax revenue. Rozlana Yergaliyeva is sole founder and full-time CEO; EB-2 NIW pathway is engaged. Technical advisor leads engineering through MVP + Series A; full-time U.S.-based CTO hired post-Series A.

From $72K to $3.8M in revenue.

Sales Forecast (5-Year, Conservative)

Pro Forma Profit and Loss (5-Year)

Net Operating Loss (NOL) carryforward through Y3 (cumulative $0.90M) fully offsets Y4 ($65K) and Y5 ($548K) profits — yielding $0 federal/state corporate income tax across the 5-year plan window. Income tax begins in Year 6. Plan reaches positive operating cash flow in Year 4.

Customer & Unit Metrics (5-Year, Conservative)

Cash Flow Summary (5-Year)

Pro Forma Balance Sheet (5-Year)

$1.5M buys 18-month runway + Series A path.

The Ask

Allocation

Milestones funded by this round

1. Q2 2026: MVP launched (500 beta users) · NSF SBIR Phase I filed (+$275K non-dilutive if awarded).
2. Q3 2026: iPad / mobile launched · 10 school pilots active.
3. Q4 2026: 5,000 paying subscribers · $75K MRR.
4. Q1 2027: FERPA / COPPA / SOC 2 readiness complete · 50 paying schools · Series A round raised.
5. Q3 2027: First Corporate L&D contract closed.
6. Q3 2028: $1M ARR (mid Year 3).

MindNova's specific contribution to the U.S.

This section consolidates the measurable, MindNova-specific benefit to the United States — jobs created, tax revenue generated, students reached, and alignment with U.S. national priorities — as required to demonstrate that the Petitioner's endeavor has substantial merit and national importance.

1. The Petitioner's Expertise and Field of Endeavor

Ms. Rozlana Yergaliyeva (hereafter the Petitioner) possesses advanced expertise in education technology, AI-driven curriculum design, and STEM pedagogy. The Petitioner's endeavor — building MindNova, an AI-native K-12 STEM learning platform — falls squarely within the United States' highest-priority categories of national interest: workforce development, STEM education, semiconductor and clean-energy talent pipelines, and the closing of the technical gender gap. As demonstrated throughout Sections 3 and 6 of this business plan, the U.S. faces a documented 3.5 million-job STEM shortfall by 2027 (U.S. Bureau of Labor Statistics), with two-thirds of 8th-grade students performing below basic math proficiency (NAEP 2024). The Petitioner is uniquely positioned, through both training and demonstrated commitment, to advance the U.S. response to this crisis.

2. MindNova's Quantified U.S. Contribution (5-Year)

Cumulative 5-year U.S. tax contribution: ~$1.03M (payroll taxes $796K + state sales/use $233K; corporate income tax $0 within plan window due to NOL carryforward; income tax begins Year 6). Cumulative U.S. payroll paid: $5.20M. Cumulative U.S. K-12 students reached: ~170,000, with a meaningful share through Title-I-funded school deployments serving low-income families. Indirect & induced jobs derived using EPI educational-services multiplier (Bivens, EPI 2019: Updated Employment Multipliers for the U.S. Economy).

3. EPI Employment Multipliers — Indirect & Induced Jobs

According to the U.S. Economic Policy Institute (EPI) Updated Employment Multipliers for the U.S. Economy (Bivens, January 2019), every 100 direct jobs in the Educational Services industry generates an additional 186 indirect & induced jobs through supplier purchases and induced consumer spending — yielding a total multiplier of 2.86. Applying this multiplier conservatively to MindNova's Year-5 direct headcount:

By the end of Year 5, MindNova will directly employ 15 U.S.-based W-2 workers and indirectly support an additional ~28 jobs through supplier purchases (cloud infrastructure, professional services, office leases) and induced consumer spending — totaling approximately 43 U.S. jobs supported. The educational-services multiplier is used as the most representative classification; the computer-systems multiplier (3.83×) is included only as an upper-bound reference.

4. Alignment with U.S. National Strategic Priorities

CHIPS and Science Act of 2022

The CHIPS Act committed $52 billion to semiconductor manufacturing and over $200 billion to STEM research, with the explicit goal of revitalizing the U.S. domestic technical workforce. The unaddressed bottleneck is talent: chip fabs require engineers, and the engineering pipeline starts in 7th-grade algebra. MindNova directly addresses this pipeline bottleneck.

Interim National Security Strategic Guidance (INSSG)

The INSSG articulates three priorities for the United States: (i) Protect the security of the American people; (ii) Expand economic prosperity and opportunity; (iii) Realize and defend the democratic values at the heart of the American way of life. MindNova advances priorities (ii) and (iii) by expanding economic opportunity through STEM education access and by closing the gender and income equity gaps in technical careers.

Title I Federal Funding ($18B/year)

Title I of the Elementary and Secondary Education Act is the largest federal K-12 program, providing approximately $18 billion annually to schools serving low-income students. AI tutoring is an explicit allowable use under Title I. MindNova's $5/student/month pricing is structured specifically so that low-income Title-I districts can adopt the platform at zero out-of-pocket cost, materially extending the impact of Title I dollars.

Women in STEM — NSF and Federal Foundation Priorities

Only 26% of U.S. engineers are women (NSF 2025), a gap that originates in middle-school years. MindNova's Women-in-STEM module is built into the curriculum from Day 0 — career pathways, role-model profiles, and mentor matching — directly advancing the goals of the National Science Foundation's ADVANCE program and related federal initiatives focused on closing the gender gap in engineering.

5. Skills Transfer and U.S. Workforce Development

The Petitioner brings advanced expertise in AI-driven education technology — a field in which the United States faces documented talent shortages. According to the Korn Ferry Future of Work — Global Talent Crunch study, the United States faces one of the most alarming talent crunches of any country worldwide. The U.S. is projected to face a deficit of over 6.5 million highly skilled (Level A) workers by 2030, with educational technology among the categories most affected. By 2030, the U.S. could experience unrealized revenue of $1.748 trillion due to labor shortages, equivalent to 6% of its entire economy — the highest figure of all the markets examined by Korn Ferry.

MindNova actively addresses this gap in two ways. First, through direct U.S. job creation across engineering, curriculum, sales, customer success, marketing, and operations — every hire is a U.S.-based W-2 position. Second, through skills transfer: the Petitioner will train every U.S. hire in proprietary methodologies (curriculum-grounded AI tutoring, Bayesian student modeling, MAP-aligned learning design), enriching the U.S. talent pool with capabilities currently scarce in the domestic market. Senior hires from MindNova will, over time, propagate these skills into the broader U.S. EdTech ecosystem.

6. Cumulative 5-Year U.S. Impact Summary

7. Conclusion — National Importance of MindNova's Endeavor

Through creating substantial direct U.S. employment, generating measurable federal and state tax revenue, transferring scarce AI-and-EdTech skills to the U.S. workforce, and providing meaningful, scaled access to STEM education for hundreds of thousands of American K-12 students — including a disproportionate share serving low-income, Title-I districts — MindNova's contribution to the United States is both substantively beneficial and of national importance. The Petitioner's endeavor directly advances U.S. national security, economic prosperity, educational equity, and the closing of the gender gap in engineering. These benefits, taken together, are sufficient to warrant favorable adjudication of the Petitioner's EB-2 NIW request.

Earned trust, not assumed.

K-12 EdTech lives or dies on compliance. Districts will not adopt — and parents will not trust — software that handles children's data carelessly. MindNova's compliance posture is engineered, not bolted on.

FERPA (Family Educational Rights and Privacy Act)

• Student PII isolated in a dedicated schema with row-level security.
• Audit logging on every read of student data, retained for 7 years.
• Parent / eligible-student right of access enforced via in-product data-export.
• Student data never sold, ever — contractually committed in ToS and DPA.
• District-level Data Processing Agreement (DPA) template aligned to SDPC Model DPA.
• State-residency option for districts requiring in-state storage (multi-region in Year 2).

COPPA (Children's Online Privacy Protection Act, <13)

• Verifiable parental consent flow for users under 13 — email-plus consent, with school-provided consent path for B2B.
• No behavioral advertising. No third-party trackers. No data sale.
• Minimal data collection — only what is required for the educational service.
• Designated COPPA officer (Head of Curriculum until Year 2 DPO hire).

SOC 2 Type II

• Engagement begins Q4 2026.
• Type I bridge target Q2 2027.
• Type II target Q3 2027 — required for Enterprise (corporate L&D) and large-district sales.

AI Safety & Pedagogical Integrity

• Refuse-to-answer prompting. System prompt enforces Socratic posture: ask questions, offer graduated hints, never directly answer until exhausted.
• Curriculum-grounded retrieval. RAG over verified curriculum corpus prevents fabricated facts.
• Mathematical correctness checks. Every numerical answer is verified through symbolic computation before being shown to the student.
• Teacher review queue. Flagged interactions (low-confidence, contested, off-topic) surface to the teacher for review.
• Red-team prompts. Weekly internal red-team runs against the tutor — jailbreaks, content-policy probes, off-curriculum drift.
• Bias audits. Quarterly audits of adaptive engine outputs across demographic groups (gender, ethnicity, ESL status) for disparate impact.
• Content policy. Off-topic refusal, age-appropriate language enforcement, no mental-health crisis response (instead, escalation to school counselor protocol).

Accessibility

• WCAG 2.2 AA compliance target at launch.
• Screen reader support for tutor dialogue and simulation lab.
• Keyboard navigation — every interaction reachable without mouse.
• Dyslexia-friendly typography as opt-in profile.
• High-contrast mode for low-vision learners.
• Closed-caption on all video content; alt-text on all images.
• ESL support — multi-language tutor responses; UI translated into Spanish at launch.

Data residency & sovereignty

• Primary U.S. region: Cloudflare + Supabase U.S.
• State-specific opt-in (TX, CA, NY) for districts requiring in-state storage by 2027.
• No international transfer of student data without explicit district consent.

Operational safeguards

• Pre-commit hooks for secrets scanning (gitleaks).
• Pen test annually starting 2027.
• Quarterly access-review of who can touch student data internally.
• Encryption: TLS 1.3 in transit, AES-256 at rest.
• Incident response runbook with 24-hour disclosure target for material breaches.
• Cyber-insurance and EdTech-specific E&O coverage in 2027.

State-level frameworks we comply with

What could go wrong, and what we do about it.

Strategic risks

R1. Khanmigo bundles deep simulations

Likelihood: Medium. Impact: Medium.
Mitigation: 12–24 month head-start on simulation depth and adaptive engine. Teacher-first GTM creates switching cost. Female-founder + Women-in-STEM positioning is a structural moat Khanmigo cannot replicate on demand. We can also pivot to be the "Khanmigo alternative for STEM teachers" if needed.

R2. School sales cycle is slower than planned

Likelihood: High. Impact: Medium.
Mitigation: B2C revenue carries the plan in 2026; B2B is the 2027–2028 lever. Teacher-led growth creates inbound that compresses cycles. Pilot offering is no-cost and short (60 days), removing procurement friction.

R3. Parent willingness-to-pay weaker than survey indicates

Likelihood: Medium. Impact: Medium.
Mitigation: $15 price point is below most consumer alternatives. Free tier seeds trust. School channel exists as fallback if B2C struggles. Sensitivity model shows the plan survives a 30% B2C slowdown.

Technical risks

R4. LLM provider price increase or outage

Likelihood: Medium. Impact: Medium.
Mitigation: Multi-provider gateway (OpenAI, Anthropic, Google) with auto-failover. Cost increases pass through to gross margin but do not destroy unit economics — at 3× current LLM price, COGS rises from ~$1.20 to ~$3.00 per sub-month and margin compresses from 82% to 70%, still healthy.

R5. AI hallucinates a wrong math answer

Likelihood: Low (mitigations are strong). Impact: High (single bad screenshot can damage trust).
Mitigation: Refuse-to-answer prompting (we mostly don't generate direct numerical answers). Curriculum-grounded RAG. Mathematical correctness checks via symbolic computation. Teacher review queue. Public efficacy dashboard.

R6. Data breach

Likelihood: Low. Impact: Very High (FERPA breach = district contract termination).
Mitigation: Compliance-first architecture from Day 0. SOC 2 by Q3 2027. Pen tests annually from 2027. Cyber-insurance from 2027. Incident-response runbook with 24-hour disclosure target.

Market & execution risks

R7. Teacher acquisition stalls

Likelihood: Medium. Impact: High (teacher-led is the core GTM).
Mitigation: Multi-channel teacher acquisition (Reddit, NSTA, ASCD, NEA, TeachersPayTeachers). Founder personally cultivates first 200 teachers. Diversification into direct-parent paid acquisition as a back-up funnel.

R8. Founder bandwidth / key-person risk

Likelihood: Medium. Impact: High.
Mitigation: Technical advisor leads engineering through MVP and Series A. Head of Curriculum hire offloads curriculum execution. Districts Partnerships Lead offloads sales execution. Full-time CTO targeted post-Series A.

R9. EB-2 NIW immigration timing

Likelihood: Low–Medium. Impact: Low (impacts U.S. closing logistics, not company operations).
Mitigation: Experienced U.S. immigration counsel engaged. Founder is able to direct early-stage operations from outside the U.S. while the petition is pending. Petition supporting documentation — including this business plan, expert opinion letters, evidence of national importance, and the documented U.S. job-creation plan in Section 14 — has been prepared in alignment with USCIS guidance.

R10. State regulatory shifts on AI in classrooms

Likelihood: High (this is happening). Impact: Low–medium (we are positioned to lead, not lag).
Mitigation: Compliance-first architecture means most new state frameworks are tailwinds, not headwinds. Active monitoring of CA, VA, OH, IL AI-in-education guidance.

Financial risks

R11. Slower revenue ramp than modeled

Likelihood: Medium. Impact: High.
Mitigation: Plan tolerates a 30% B2C slowdown without bridge. Non-dilutive grant stack ($1.3M cumulative through 2028) provides redundancy. Aggressive cost-cut levers (delay hires 1–2 quarters, reduce marketing 50%) preserve runway.

R12. Series A delay

Likelihood: Low–medium. Impact: Medium.
Mitigation: Break-even by Q2 2027 makes Series A optional for survival. Round becomes a growth-acceleration tool, not a runway tool — preserving founder leverage in the round.

Exit pathways.

Path 1 — Strategic Acquisition (Most Likely)

EdTech consolidation is steady and AI-native is becoming a board-level priority. Three buyer classes are realistic:

• Legacy K-12 publishers (Pearson, McGraw-Hill, Savvas, Houghton Mifflin Harcourt) — need an AI-native STEM product. Outcome range: $50–150M.
• Adjacent EdTech consolidators (Renaissance Learning, IXL, Curriculum Associates, Imagine Learning) — fit the AI-tutor + simulation hole. Outcome range: $40–100M.
• Tech platforms with K-12 ambitions (Google for Education, Microsoft Education, Apple) — strategic acquirers or distribution partners. Outcome range: $80–200M+.

Path 2 — IPO (Lower Probability, Higher Outcome)

If MindNova reaches $50M+ ARR with NRR >120%, defensible data moat, and demonstrated efficacy, IPO is viable 2030–2032. Comparable: Duolingo IPO'd at ~$6.5B market cap (July 2021).

Path 3 — Sustained Cash-Flow Business

At 82–84% gross margin, MindNova can operate as a cash-flow positive private company indefinitely from 2027 onward. Founder retains control and optionality.

Comparable transactions

Illustrative return profile

The next 36 months.

12-month roadmap (Q2 2026 – Q1 2027)

24-month roadmap (Q2 2027 – Q1 2028)

36-month vision

Category leadership — default AI-native STEM platform in U.S. middle/high schools. Workforce pipeline — 200K+ MindNova-credentialed students annually with career outcomes tied to mastery records. Corporate — 8+ Fortune-500 L&D contracts (aerospace/defense/semiconductor/clean-energy). Federal — NSF Phase II awarded, DOE workforce partner, named in CHIPS-adjacent K-12 initiatives. International — Canada launch + EU exploratory (UK, NL, IE). Open standards — public efficacy dataset + Socratic-tutor benchmark.

North Star Metric

Concept-mastery hours per active student per week — the single metric that captures product use, learning value, and revenue together.

Reference materials.

A. Glossary

B. Key references

• U.S. Bureau of Labor Statistics — STEM Occupations Projections (2024)
• NAEP — National Assessment of Educational Progress, 2024 mathematics
• NEA — Educator Workforce Report (2025)
• NSF — Women, Minorities, and Persons with Disabilities in S&E (2025)
• HolonIQ — Global EdTech Market Outlook (2025)
• Owl Ventures + Reach Capital — K-12 EdTech Investment Reports (2024–2025)
• Tutor.com + Wyzant — Published pricing pages (2025)
• U.S. Department of Education — Title I funding allocation tables (2024)

C. Data room

Available to qualified investors under NDA. Contents include: cap table (current + post-seed), financial model (Excel, monthly granularity), customer research (teacher and parent interviews), curriculum architecture, technical diagrams, compliance posture, product demos, founder + advisor bios, legal docs (incorporation, IP assignments, employment templates), trademark filings.

D. Contact

E. Forward-looking statements

This document contains forward-looking statements regarding MindNova, its business, products, market opportunity, financial projections, and strategic plans. These statements are based on management's current expectations, estimates, and assumptions, and are subject to significant risks and uncertainties. Actual results may differ materially from those projected. Factors that could cause such differences include, but are not limited to: K-12 adoption rates of AI tutoring tools, competitive dynamics from Khanmigo and other incumbents, regulatory changes (FERPA, COPPA, state-level AI-in-education frameworks), technological challenges (LLM provider pricing, model behavior), retention of the founder and key personnel, ability to raise additional capital on favorable terms, macroeconomic conditions affecting school district budgets, and the inherent uncertainty of pre-revenue projections. This document is not an offer to sell or a solicitation of an offer to buy any securities. Any offer of securities will be made only pursuant to definitive transaction documents in compliance with applicable U.S. securities laws.

F. Confidentiality notice

This document is confidential and proprietary to MindNova. It is being provided to the recipient solely for the purpose of evaluating a potential investment in the Company. The recipient agrees to maintain the confidentiality of this document and its contents, to use it solely for the stated purpose, and not to disclose, distribute, or reproduce any portion without prior written consent of the Company. Upon request, the recipient agrees to return or destroy all copies. Any unauthorized use or disclosure may result in legal action.