School reports don't say ADHD. But they may contain the pattern.
One teacher, one year, writes one story. All teachers, across years, through an ADHD lens, may tell a new one.
Some childhood patterns were obvious. Others only became clear later, when life required more than school structure could hide.
Tested with confirmed-ADHD adults, the pattern was in their records.
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Wherever you are on the journey ,
your reports have never been read this way before.
Some people arrive here because a clinician has asked for school reports. Some arrive because the pattern was never explained.
Select where you are, this personalises your results.
You may have sensed a pattern for years without knowing how to describe it. ADHDLumina reads the language teachers used at the time, across classrooms and ages, to show whether those same traits were already present.
ADHDLumina reads your reports across years and teachers, then organises the childhood patterns clinicians often ask adults to describe during ADHD assessment, so you arrive with childhood evidence already structured, not reconstructed under pressure.
For many adults diagnosed later, school reports contain descriptions that suddenly make earlier experiences easier to understand. ADHDLumina helps show what teachers repeatedly noticed before anyone named it.
Waiting often leaves people carrying uncertainty for months. ADHDLumina helps you examine the childhood evidence already in your hands while you wait for formal assessment.
Sometimes the question is not certainty, but whether the same difficulties were visible long before adulthood. ADHDLumina helps examine whether childhood reports contain a pattern worth understanding properly.
If someone has asked you to bring school reports, ADHDLumina helps you understand what they may already show before you walk into the room.
Some patterns become clearer only when structure falls away, independent study, deadlines, or daily organisation becoming harder than expected. ADHDLumina reads earlier reports for what was noted, what was missing, and what began to emerge over time.
When reports from different years begin to sound familiar, patterns are often easier to recognise across time than in isolated comments. ADHDLumina reads them longitudinally so recurring traits become clearer.
“Reading through my report was thought-provoking in a way I didn’t expect — it made me realise things I’ve always thought but never been able to articulate.
When I was young, I struggled to write things down as fast as everyone else. I just thought I was a slow writer. If something didn’t interest me, I couldn’t concentrate for more than a few minutes before my mind drifted — and I thought that made me lazy or weird. I always struggled to talk about it. When I was young, I didn’t know it was there. I just thought that’s how people were.
It’s hard to describe a state of being — but reading this hit me like a tonne of bricks. There are clear patterns in those reports, combined with an internal feeling of knowing it to be true. I’d feel slightly less of a failure knowing there’s a reason. I need to look into this further.”
“How it shows up as an adult describes him exactly.”
Adam’s sister
I spent over a decade measuring data professionally — millions of consumer decisions, tracked across time, across markets, across contexts. What I didn’t expect was that during my ADHD assessment at 36, I would find that I had been sitting on the richest data set of my own life. In a cupboard. In a box. My school reports.
Read from a clinical perspective, the language my teachers used had always contained the clues. The pattern was there all along. It just hadn’t been read that way before.
During my ADHD assessment at 36, the clinician asked for my school reports. I dug them out. As she read through them, I asked what she was looking for.
"I spent over a decade at a global data measurement company. What I didn't expect was that during my own ADHD assessment, I would find I had been sitting on the richest dataset of my life, stored in a cupboard, in a box: my school reports."
"Read from a clinical perspective, the language my teachers used held clues. The pattern had always been there. It just hadn't been read that way before."
"That pattern had been there since I was five. Thirty-one years passed before anyone found it."
School reports draw on observations from independent sources, in the developmental window that matters, with recurring language that can be attributed to the domains that ADHD affects.
Clinicians don't look for one teacher that said something striking. They look for multiple teachers, across a decade, saying the same thing.
“Bright lad, underachieving.” “Prefers to operate off his natural wit.” “Able but too casual.” “Needs encouragement to stay on task.”
All from the same week’s reports. The PE teacher that same week wrote: “Excellent working hard — role model.”
Same child. Same week. That’s not inconsistency — that’s what interest-based attention looks like from the outside. These aren’t character judgements. They’re independent teachers describing the same pattern from different angles, without knowing that’s what they were doing.
Patterns are not always obvious. Sometimes they appear in what teachers repeatedly avoid mentioning, or emerge later as school demands increase and earlier compensation stops working.
"This is not a picture of a child who struggled to learn. It is a picture of a child whose learning was often not visible in the way school expected it to be."
What people find.
For some people, the pattern becomes clearer when seen structurally.
A clean result doesn’t rule out ADHD — masking is real. A strong result doesn’t confirm it. Every result is a starting point for a professional conversation.
A real example.
A portion of what came back from the founder's own 96 pages.
A consistent pattern, across 10 years, multiple teachers, multiple subjects. This warrants further exploration.
Something consistent appears across these reports, a gap between what could be clearly expressed verbally and what appeared in written work. Teachers noticed the understanding, the ideas, the capability. But what arrived on the page was different.
The pattern in your reports is consistent with someone who processed information quickly verbally but found translating that into written form unexpectedly difficult, a gap that often goes unnoticed until academic demands increase.
This may show up in adult life as: starting tasks but struggling to finish them, preferring to talk through ideas rather than write them, or feeling like your output doesn’t reflect your actual ability.
Results vary. The pattern found, its strength, and what it means will all be specific to yours.
How it works.
Standard AI reads a page at a time. ADHDLumina reads across years, finding what recurs independently, across teachers who never compared notes.
ADHDLumina doesn’t just look for a phrase — it looks for how that phrase is used, how often, and what it maps to.
“Occasionally distracted” is noise. “Often fails to concentrate,” “always loses his work,” “rarely completes tasks without prompting” — these are different. Clinicians look for behaviours frequent and persistent enough to indicate a pattern, not a bad day. ADHDLumina reads qualifying language the same way.
The nine criteria used in ADHD assessment have natural language equivalents that teachers use without knowing it. “Speaks before thinking” is impulse regulation. “Never finishes” is task initiation. “Loses things constantly” is working memory. “Doesn’t concentrate” is sustained attention. ADHDLumina recognises this language and maps it to the domains a clinician would assess.
“Gets distracted easily” at age 7 and “fails to reach his potential” at age 14 may be describing the same child, the same brain — but the language changes as demands increase. Observations before age 12 carry the most developmental weight, because they predate the compensation strategies most people develop. ADHDLumina tracks how language evolves and connects observations that look different on the surface but describe the same underlying pattern.
A 2025 study in European Child & Adolescent Psychiatry (Waltereit et al.) examined 1,853 school reports and found that systematic analysis of teacher language mapped to DSM-5 criteria could identify ADHD retrospectively with 91% sensitivity and 93% specificity — and called for natural language processing tools to implement it at scale.
Going back through old reports is its own experience. What ADHDLumina does is help you make sense of what they already contain.
Your reports have never been read this way before.
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If you’re preparing for assessment, this helps organise what childhood reports already show.
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For supportive exploration only — not a clinical or diagnostic tool. Always speak with a qualified professional for a formal assessment. Your files go directly from your device to the AI and are not stored.