Pre-scan your case write-ups, capstone consulting reports, group project drafts, and internship application essays before Turnitin or your recruiter sees them. Sentence-level highlights show exactly which lines read AI, with perplexity and burstiness signals tuned for the McKinsey-style register that business undergrads are taught to write in. FERPA-aware, no training on student work. Free to try. No card.
For undergraduate business students writing 6 to 12 deliverables a semester across strategy, marketing, finance, and operations courses, plus a senior capstone and rolling recruiting essays. The realistic 2026 default is draft fast, scan before submission, fix the specific sentences that read AI.
Business undergrads carry a writing load that mixes formal case-analysis genres with recruiting-deadline pressure, often in the same week. Detectors over-flag the McKinsey-style register the major programs explicitly teach, which means false positives hit hardest in the prose you were trained to produce. Pre-scanning is the cheapest insurance against a wrongful integrity review on a case write-up you actually wrote yourself.
Three to seven pages of structured argument with frameworks like Porter Five Forces, SWOT, BCG matrix, and value-chain. Free tier covers a single case scan up to 5,000 characters. Pro at $19.99 a month, or $14.99 a month on yearly, unlocks 10,000 character pastes for longer Harvard Business School style cases and unlimited scans for the weeks you have two cases due back-to-back.
Senior capstones at Wharton, Ross, Stern, and McIntire often involve real client deliverables: 25 to 40 page strategy memos, market entry recommendations, or operational redesigns. The 90-day Pro history matters when a capstone advisor asks about a draft section you submitted three weeks ago. PDF export keeps a defensible record of what you scanned and when.
Most strategy and marketing courses run team deliverables across three to five students. Mixed-author drafts read uneven to any detector. Scanning section-by-section instead of the merged document tells you which teammate's paragraphs are pulling the score down without surfacing it as a public accusation.
Wharton undergrad, MIT Sloan undergrad, NYU Stern, and Michigan Ross all run Turnitin's AI check across the core curriculum. UVA McIntire, UT McCombs, WashU Olin, USC Marshall, Notre Dame Mendoza, and Maryland Smith follow the same pattern, with capstone consulting projects as the high-stakes deliverable where integrity reviews actually happen. Berkeley Haas, UNC Kenan-Flagler, Indiana Kelley, Cornell Dyson, Emory Goizueta, Georgetown McDonough, Boston College Carroll, Babson, and Bentley round out the list. The pre-Turnitin workflow is the same everywhere: students draft normally, scan with TextSight before submission, edit the flagged sentences, then submit through Canvas, Blackboard, or the school's preferred LMS. The .edu discount applies on Pro for verified Penn, MIT, NYU, Michigan, UVA, UT, WashU, USC, Notre Dame, and Maryland emails.
Five genres cover most of the writing a business undergrad submits across four years. Each has its own false-positive profile, and TextSight is calibrated for all five.
The most common business undergrad genre and the one most often over-flagged. The format rewards uniform sentence rhythm, parallel structure, and recurring framework vocabulary, which all overlap with ChatGPT defaults. Aim for an Authenticity Score above 75. Scattered yellow flags inside a tight Five Forces breakdown usually reflect the genre, not AI use.
STP, marketing mix, and go-to-market write-ups for courses like consumer behavior, brand management, and product marketing. The structured bullet-heavy format trips detectors less than case analyses but more than narrative prose. Scan the full plan as one document, not section by section, because flow matters here.
Ratio analysis, DCF write-ups, and equity research style memos for finance and accounting courses. The numeric content sits outside the classifier; only your narrative explanation gets scored. Common false positives come from textbook-style phrasing around liquidity, leverage, and profitability ratios. Rewrite definitions in your own voice.
Entrepreneurship and new venture courses ask for 15 to 30 page business plans with executive summary, market analysis, financials, and operating plan. Scan the executive summary and market analysis sections most carefully, because those are the prose-heavy parts where AI residue accumulates and where reviewers focus first.
The senior deliverable. Often a real client engagement through a capstone studio at Ross, Mendoza, Smith, or Marshall. Multiple draft cycles, advisor reviews, and a final presentation. The 90-day history on Pro is built for this rhythm: scan after each revision, watch the score climb, keep the PDF receipts.
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Most strategy, marketing, and capstone deliverables are written by three to five students. The merged document looks uneven by design. Here is the realistic workflow.
Each teammate writes their section in their own voice. When you merge into one document, the seams are obvious to any classifier. Scanning section-by-section gives you a per-section score, so you can tell which sections need work without re-running the whole thing.
A merged group document often has uneven burstiness across the page: teammate A writes long flowing paragraphs, teammate B writes short choppy bullets, teammate C copy-pastes from the slide deck. The overall Authenticity Score smooths these out and hides the actual problem sections. Per-section scans surface them.
It usually means either heavy AI assistance on that section or formal-register prose that the classifier reads as AI-shaped. Either way, the conversation is more productive at the section level. Sentence-level highlights show specific lines to revise rather than vague accusations across a whole submission.
For senior capstone teams running multi-week engagements, the Business tier with 5 seats and shared history makes sense: every teammate sees the same scan archive, the audit log shows who scanned what, and you keep the PDF receipts together for the final advisor review.
HULT Prize, Deloitte National Undergraduate Case Competition, KPMG ICC, and EY case competitions all added AI-content review at later rounds in 2025. Capstone consulting projects for real clients face the same pressure.
Judges started getting submissions that were obviously templated. Some teams were running the case prompt through ChatGPT, lightly editing, and submitting. The judging boards responded by adding AI screening at the round between regional and national, which is the round where prize money starts mattering.
For a multi-round competition, scan your team's deck script and written submission before each round. Aim above 75. Below 70 means rewrite the prose-heavy sections, particularly the executive summary and recommendation slides which judges read first.
If the competition committee asks about AI use, the Pro tier exports a PDF showing the input text, the Authenticity Score, the sentence-level flags, the timestamp, and the classifier version. That is the format a competition appeals process actually wants to see.
If your capstone is for a real client (common at Ross, Mendoza, Smith, Marshall, McIntire), the client may not know to ask about AI content. Your professor will. Run a scan before each advisor review and keep the receipts in your team folder.
IB, consulting, and finance recruiting all run AI-content scans on application essays now. The risk profile is different from coursework because there is no formal hearing, just a silent reject before first round.
For Goldman, Morgan Stanley, JPMorgan, Bain, BCG, McKinsey, and the major consulting and IB firms, application essays go through automated screening that includes AI detection as one signal. A flagged essay does not always get rejected outright, but it lowers the read-priority and you may never hear back.
Coursework safety is around 75. Recruiting essays should be higher because the screener is calibrated more aggressively. Below 70 on a 500-word application essay means the prose reads polished enough to look templated, and a busy recruiter may screen it out without reading carefully.
"Why Bain?" essays are the most over-flagged genre across all of recruiting because every applicant pulls similar talking points from the firm's website. Mention specific people you have spoken to, specific cases you have read, specific cities or practices you care about. Detail breaks the templated rhythm.
Cover letters are even more templated than essays by design. Scan and aim above 75. The fix is usually one specific anecdote in the middle paragraph, not a wholesale rewrite. Sentence-level highlights show you exactly which lines to swap.
A single percentage is not a fix path. The TextSight result panel shows which sentences reacted and why, so you can edit the specific lines instead of rewriting a whole case write-up.
Every sentence in your case write-up is colour-coded by its own AI-likeness score. Red sentences clustered in one paragraph are a stronger signal than scattered yellows. Scattered yellows in an otherwise structured analysis often just mean you were taught to write in the McKinsey register. You read the pattern, not just the headline number.
Above sentence highlights, paragraph-level cards show which sections of your write-up are pulling the score down. For a 10-page capstone draft, this is faster than reading every red sentence. Identify the two or three paragraphs that need rewriting, then drill into sentences inside those sections only.
Perplexity is how predictable your word choices are to a language model. Low perplexity reads AI-like. The score is shown per-sentence on Pro, which is the diagnostic context you need to decide whether a flag is real AI residue or just an unusually well-rehearsed framework definition.
Burstiness is how much your sentence length and structure vary across the document. ChatGPT defaults to uniform medium-length sentences. Real student writing has bursty rhythm: one short sentence, one long, one fragment. Low burstiness across an entire case write-up is the classic AI fingerprint, and it shows up most often in finance and accounting prose.
Student submissions are protected by FERPA in the US, by GDPR in the EU and the UK, and by local equivalents elsewhere. TextSight is designed to honour those rules out of the box, not as a paid setting you have to find.
Case write-ups, capstone drafts, and recruiting essays you submit for scanning are never used to train the classifier or any other model. This is a contract clause, not a configuration toggle. It applies on the free tier the same way it applies on Pro and Business.
The free tier needs no email, no account, no identity. For students worried about an internship application essay leaking, this matters. You can scan a Goldman or McKinsey draft without TextSight ever knowing who you are.
Scan history is private to your account. We do not share scan data with universities, professors, career services offices, Turnitin, or any third party. Your case write-ups and capstone drafts are not part of any institutional record, and your professor cannot pull them.
Any scan can be deleted from your history. On Pro you can delete individual records. Data retention is bound to your settings, and a standard DPA is available on Business and Enterprise tiers for capstone teams and student consulting clubs.
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