# Sujar Henry (@sujar.tech) on tiktok

- id: koinon:creator:tiktok_sujar.tech
- url: https://koinonlink.com/kol/tiktok/sujar.tech
- schema_version: 1.3

## Identity
- platform: tiktok
- handle: sujar.tech
- platform_url: https://www.tiktok.com/@sujar.tech
- website: sujartech.com/links
- country: United States
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 28062
- following: 36
- posts_observed: 3
- verified: false
- size_tier: koc

## Engagement
- status: not_collected
- status_note: Engagement has not been collected for this creator yet. This is a gap in our collection, NOT a statement that the creator has no engagement. Follower count is known, so it is measurable.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: software
- subcategory: ai_tools
- category_confidence: 0.95
- category_source: derived_from_recent_content
- topics: Machine learning roadmaps and quick learning tips, Resume projects and coding project ideas for hiring, Free certifications and GitHub repos for job search, Math required for machine learning, Tech career advice and job market realities

## Audience (inferred)
- status: present
- description: Aspiring software engineers and machine learning students, mainly CS majors, recent grads, and self-taught learners trying to break into tech jobs
- roles: none
- seniority: learner
- pain_points: Hard to get hired without prior experience in a tough 2026 job market, Unclear which math and resources are actually needed for machine learning, Need strong resume projects that stand out to ATS and recruiters, Overwhelmed by how long it takes to learn ML basics and coding skills
- posts_analysed: 40
- confidence: 0.75

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.6
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 50
- authenticity_basis: profile_shape_only
- credibility_score: 50
- flagged_for_review: false
- koinon_bd_grade: B — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [tiktok_sujar.tech#79141513] We’ve all thought this as kids too… #softwareengineer #coding #computerscience #hacker #funny (https://www.tiktok.com/@sujar.tech)
- [tiktok_sujar.tech#1f8250fe] original sound - sujar.tech
- [tiktok_sujar.tech#f14ac946] It is a becoming a big trend on TikTok now! Click here: softwareengineer
- [tiktok_sujar.tech#7bf07f8d] Check out Sujar Henry’s video! #TikTok >
- [tiktok_sujar.tech#124e7205] Let’s see if it’s possible this Week,make sure to follow along if you want to see the results for the model… @NFL  #coding #computerscience #cs #nfl
- [tiktok_sujar.tech#bf8c3bd5] POV: you walk through the wrong door of the tech company Part 2 #computerscience #coding #cs #machinelearning #cloud #ai #softwareengineer #Tech #funny
- [tiktok_sujar.tech#d0c72eb1] original sound - m_v365
- [tiktok_sujar.tech#9e373f68] A lot of people get these concepts confused so I thought I’d break it down in the simplest and most fun way that I know,with Pokemon!!! These are both really good high paying fields but if you’re interviewing for either, it’s

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.75, freshness_days=22, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.75, freshness_days=22, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.75, freshness_days=22, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=0, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=0, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=1, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.25, freshness_days=0, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=1, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=1, method=platform_profile

## Freshness
- profile_checked_days_ago: 1
- content_analysed_days_ago: 0
- audience_updated_days_ago: 22

## AI retrieval
- indexing_requests: 1
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=tiktok_sujar.tech
- Request removal: https://koinonlink.com/claim?k=tiktok_sujar.tech
- Terms: https://koinonlink.com/for-ai