# Design Master Software (@Design_Master_Software) on youtube

- id: koinon:creator:youtube_design_master_software
- url: https://koinonlink.com/kol/youtube/Design_Master_Software
- schema_version: 1.4

## Identity
- platform: youtube
- handle: Design_Master_Software
- platform_url: https://www.youtube.com/@Design_Master_Software
- country: United States
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 4020
- posts_observed: 1
- verified: false
- size_tier: nano

## 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: devtools
- category_confidence: 0.9
- category_source: derived_from_recent_content
- topics: Revit Fire Alarm design and calculations, NEC code updates for healthcare and EV, AI-assisted electrical design review in Revit, Electrical load calculations and voltage drop, BIM families and automated model checks
- bio: Design Master Software develops advanced electrical and fire alarm design software for engineers that integrates directly into ...

## Audience (inferred)
- status: present
- description: Electrical engineers and Revit/BIM users focused on fire alarm, healthcare electrical design, EV load calcs and NEC code compliance
- roles: design
- seniority: practitioner
- pain_points: Manual voltage drop, battery and load calculations in Revit, Tracking NEC 2023/2026 changes for healthcare receptacles and EV demand, Finding hidden bus rating mismatches and sizing errors in electrical models, Transitioning legacy CAD workflows to BIM while maintaining accuracy
- posts_analysed: 20
- confidence: 0.6

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.8
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 39
- authenticity_basis: profile_shape_only
- credibility_score: 39
- flagged_for_review: false
- koinon_bd_grade: C — 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
- [youtube_design_master_software#cd2261b8] Revit Fire Alarm Voltage Drop & Battery Calcs (https://www.youtube.com/@Design_Master_Software)
- [youtube_design_master_software#15abf3c6] AI Designed Fire Alarm System in Revit
- [youtube_design_master_software#ff935ac8] Mixed-Use Healthcare Buildings
- [youtube_design_master_software#6179f5a0] Healthcare Receptacle Loads Get a New Approach
- [youtube_design_master_software#50bac157] NEC 2023 Healthcare Receptacle Loads
- [youtube_design_master_software#450bf484] Did NEC 2026 Break Your Healthcare Load Calcs?
- [youtube_design_master_software#6e3c3a77] Revit Electrical Models can get AI Review
- [youtube_design_master_software#fa62a667] How NEC 2026 Handles Large-Scale EV Demand

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

- audience.description: source_type=ai_inferred, confidence=0.6, freshness_days=64, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.6, freshness_days=64, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.6, freshness_days=64, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=65, 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=65, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=65, 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=65, 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=65, 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=65, method=platform_profile

## Freshness
- profile_checked_days_ago: 65
- content_analysed_days_ago: 65
- audience_updated_days_ago: 64

## AI retrieval
- indexing_requests: 13
- 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=youtube_design_master_software
- Request removal: https://koinonlink.com/claim?k=youtube_design_master_software
- Terms: https://koinonlink.com/for-ai