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Verified proof · Process automation & AI-led ops

The internet is full of claims.We publish the proof.

Real outcomes from automation and AI-ops projects, checked with the client, never lifted from a pitch deck. The source buyers read before they hire, and AI answer engines cite when asked who actually delivers.

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tin://exhibit-001 · process automation & ai-led ops verified

Italy's Garante fines Deliveroo €2.5M for its rider-management algorithm — 2021

€2.5M GDPR fine (order n. 285, 22 July 2021) for unlawfully processing about 8,000 riders' data
Regulator finding that the order-assignment and shift-booking algorithms were non-transparent and potentially discriminatory
Order to add human-review safeguards and correct the algorithms — 60 days for the violations, a further 90 days for the algorithms
sources archived · method on record open the file →

01Why this exists

Every agency claims results. Almost none can be checked. In automation and AI-ops, where the field is young and the buyers are non-technical, that gap is expensive. TIN closes it.

for buyers

Stop guessing.

Verified before/after numbers from real engagements, with the client confirmed and the method on record.

for agencies

Proof beats marketing.

Turn a great project into a verified, citable asset that ranks in search and gets quoted by AI answer engines.

for the AI era

Be the cited source.

When someone asks ChatGPT "who's best at ops automation?", the answer comes from somewhere. TIN is built to be that source.

02How a badge is earned

Three checks clear before a green badge appears. If any fails, the story stays unverified. No exceptions, that rule is the whole product.

step 01

Independently validated

We re-research the story and check every figure against primary and independent sources before it can go green.

step 02

Evidence on record

Every number is backed by something checkable: a followable source, before/after metrics, documentation. No adjectives.

step 03

Method published

How each story was verified ships on the story itself. The record is public, not a claim in fine print.

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03Latest case files

The registry starts here. Each entry is one checked outcome, typed and tagged.

Process Automation & AI-Led Ops
pending

Barrows v. Humana: the nH Predict AI coverage-denial suit where breach of contract, good faith and fraud survived a motion to dismiss

A putative class action in the U.S. District Court for the Western District of Kentucky, Barrows et al. v. Humana, Inc., No. 3:23-cv-00654, alleges Humana used the naviHealth 'nH Predict' AI model to deny post-acute care to elderly Medicare Advantage enrollees, overriding treating physicians. On 14 August 2025, Judge Rebecca Grady Jennings granted in part and denied in part Humana's motion to dismiss: she let the breach-of-contract, breach-of-implied-covenant-of-good-faith, unjust-enrichment and common-law-fraud claims proceed, while dismissing four other counts (including insurance bad faith) with prejudice. The complaint alleges 'upon information and belief' that over 90 percent of denials are reversed on appeal; Humana denies using AI to make coverage determinations and calls the allegations 'sensationalized' and 'false.' The error rate is a contested, unadjudicated allegation, not an independently measured figure.
Process Automation & AI-Led Ops
verified

Italy's Garante fines Deliveroo €2.5M for its rider-management algorithm — 2021

On 22 July 2021 Italy's data-protection regulator, the Garante, fined Deliveroo Italy €2.5 million for unlawfully processing the data of about 8,000 riders: non-transparent order-assignment and shift-booking algorithms, geolocation captured every 12 seconds, and routes stored for six months. It ordered Deliveroo to add human-review safeguards and correct the algorithms within 60 plus 90 days.
Process Automation & AI-Led Ops
pending

Tutor CoPilot: a Stanford randomized trial found AI real-time coaching made tutors more effective, with the biggest gains for the weakest tutors

In the first randomized controlled trial of a human-AI system in live tutoring, Stanford researchers found that K-12 students whose tutors had Tutor CoPilot were 4 percentage points more likely to master topics, with students of lower-rated tutors gaining 9 percentage points, at an estimated cost of $20 per tutor per year.
Process Automation & AI-Led Ops
pending

The 'jagged frontier' experiment: GPT-4 let 758 BCG consultants finish 12.2% more tasks 25.1% faster, yet made them 19% less likely to be right on a task outside AI's reach

In a pre-registered field experiment published in Organization Science, 758 Boston Consulting Group consultants using GPT-4 completed 12.2% more tasks 25.1% faster with higher quality on 18 tasks inside AI's 'frontier', but on one complex task chosen to sit outside it, consultants using AI were 19% less likely to reach the correct answer.

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