Reader Inc. builds assisted-reading software that runs entirely on the reader's own device — the trainer, the drills, and a neural voice, all local. That one architectural decision means margins that look like a book publisher's, not a SaaS company's. This page holds the business plan, the pitch deck, the five-year pro forma, and a way to reach the founder directly.
Most reading and ed-tech products carry a cloud bill that grows with every user. Reader Inc. inverted that: the entire product — pacing engine, comprehension drills, neural text-to-speech — executes on the customer's device. Revenue scales; cost of goods essentially doesn't.
Students, professionals and readers with dyslexia or attention differences all hit the same wall: text arrives faster than they can comfortably take it in. Existing tools either promise implausible speed-reading multiples or park the user in a cloud service that reads their documents.
One app presents text one word at a fixed point, pairs it with imagery and an on-device neural voice, and measures comprehension as you train. A browser extension and desktop/Android builds carry it everywhere. Nothing the user reads ever leaves their machine.
Consumer memberships at $20/month or $192/year (free tier: 5,000 words/day). Institutional seat packs from 10 seats for schools and universities. Custom-branded builds — an institution's own subdomain, apps and mark — from $5,000 per engagement.
Because the product is local-first, the privacy promise institutions need — staff can see that a student read, never what — is enforced by the design, not by a terms-of-service page. Competitors built on cloud pipelines cannot copy this without rebuilding.
The deck below is the same one we present in person, written out so it can be read without a meeting. A call walks through the same ten points.
Understanding is the product; the words are only the packaging. We build the machinery that gets meaning across faster — for everyone, and especially for the readers the standard page was never designed for.
Assistive-reading and literacy software spans consumers, K-12, and higher education. Every accommodation office in every university is a buyer of exactly what we build; every professional with a reading backlog is a trial away from a membership.
On-device neural speech and in-browser machine learning crossed the quality line only recently. A voice that used to require a data centre now runs in a tab. We built on that shift early, and it is the whole reason the unit economics work.
Shipped and live at readerinc.com: the trainer, the Gym's drill programme, a public-domain library, Reader AI, a browser extension, and desktop and Android builds. This is not a prototype seeking funding to exist.
Free tier for reach, $20/month or $192/year memberships with a one-day trial, seat packs of 10+ for institutions, and custom institutional software from $5,000. Payments run through card and PayPal; custom work is invoiced.
Cost to serve one more member is approximately the cost of static file hosting — cents, not dollars. Gross margin on memberships is effectively the payment processor's fee away from 100%. Institutional work carries service cost but prices accordingly.
Consumer: organic search around the free tier and the magazine's editorial content. Institutional: direct pilots with disability-services offices, where one accommodation coordinator can bring hundreds of seats and renew annually.
Speed-reading apps over-promise and churn; cloud TTS readers carry both a server bill and a privacy problem. We are the only entrant whose honesty about the research (see the science page) is itself a sales asset with institutions.
Founder-built and founder-led — one person has carried product, engineering and design to a shipped multi-platform suite. Funding buys the second hire, not the first version. More on the founder below.
We are raising a seed round to fund institutional sales, a second engineer, and accessibility certification work. Terms, data room and current traction figures are shared in conversation — reach out.
A summary pro forma, fiscal years one through five. It assumes steady rather than viral consumer growth, institutional seats compounding through annual renewals, and the cost structure a local-first product actually has. The full model with assumptions is available on request.
| USD, thousands | Year 1 | Year 2 | Year 3 | Year 4 | Year 5 |
|---|---|---|---|---|---|
| Revenue | |||||
| Consumer memberships | 72 | 230 | 560 | 1,050 | 1,700 |
| Institutional seat packs | 40 | 180 | 520 | 1,150 | 2,100 |
| Custom institutional software | 25 | 90 | 200 | 350 | 500 |
| Total revenue | 137 | 500 | 1,280 | 2,550 | 4,300 |
| Costs | |||||
| Cost of revenue (hosting, payments) | 10 | 30 | 70 | 135 | 220 |
| People | 120 | 310 | 600 | 980 | 1,450 |
| Sales & marketing | 30 | 90 | 210 | 380 | 560 |
| General & administrative | 25 | 50 | 95 | 150 | 220 |
| Total costs | 185 | 480 | 975 | 1,645 | 2,450 |
| Results | |||||
| Gross margin | 93% | 94% | 95% | 95% | 95% |
| Operating income | (48) | 20 | 305 | 905 | 1,850 |
| Operating margin | — | 4% | 24% | 35% | 43% |
These figures are forward-looking projections prepared by management for discussion purposes. They are illustrative, involve assumptions about growth and renewals that may not hold, and are not a guarantee of future performance or an offer of securities.
Valentin founded Reader Inc. and built the product single-handed: the reading trainer and its pacing engine, the Gym's drill programme, the on-device neural voice, the browser extension, and the desktop and Android apps — a full multi-platform suite carried from first line of code to shipped software.
The company reflects his convictions as much as his engineering. Reading tools should be honest about what the research supports — the science page says plainly what we will not claim. And software that handles what people read should keep it on their own machine, which is why the entire product runs locally and the privacy promise to schools is structural, not contractual.
He works directly with early institutional partners and answers investor enquiries personally.