What is sentiment + intent classification for multi-vertical customer support — and what is the per-vertical-PHI-times-ECOA-routing problem distinctive to this skill?

A multi-vertical operator runs customer-support agents across Salesforce Service Cloud + Zendesk + Freshdesk + Intercom + HubSpot Service + ServiceNow + Front + HelpScout + Kustomer + Gladly. Per-message sentiment + intent classification routes the message through downstream automation (refund + escalation + termination + cancellation + churn-risk + cross-sell + upsell). Verticals served include healthcare + legal + financial + retail + DTC + franchise + hospitality + technology + education + government. The four-skill bundle on the customer-support-NLU agent — Ingest, Classify, Gate, Audit — sits above the customer-service + NLU + LLM + moderation substrate and writes a per-message canonical record. The operationally distinctive anchor: per-vertical PHI handling when healthcare customer-support input contains PHI (HIPAA 45 CFR 164.502/504/514 Safe Harbor de-identification + HHS OCR enforcement) + attorney-client privilege when legal vertical (ABA Model Rule 7.1-7.5 + state bar 50-state) + FINRA Rule 2210 when financial vertical + ECOA Reg B disparate-impact when AI-ML classification drives consumer-impacting routing (refund + escalation + termination) + Title VII + ADEA + ADA + Fair Housing + EEOC AI Guidance 2024 + NYC Local Law 144 AEDT + EU AI Act Article 22 + Annex III high-risk + replication-crisis discipline (Brier + ECE + inter-rater agreement + Bonferroni + BH FDR + Rosenbaum + pre-registration + ASA p-value statement).

Why do Salesforce Service Cloud + Zendesk + Freshdesk + Intercom + Hugging Face + OpenAI + Anthropic + Amazon Comprehend + Google NLU + Microsoft Text Analytics + IBM Watson NLU break at multi-vertical-replication-crisis NLU classification scale?

Each customer-service vendor ships per-tenant flat ticket-classification + sentiment-score primitives. Each NLU vendor ships flat sentiment + intent label. Each LLM ships flat prompt response. None calibrates classification with replication-crisis discipline (Brier + Expected Calibration Error + reliability diagram + isotonic + Platt + Beta recalibration + Rosenbaum + E-value + ASA p-value statement + inter-rater agreement Krippendorff alpha + Cohen kappa + Fleiss + Gwet AC1 + pre-registration + per-test-family multiple-comparisons Bonferroni + BH FDR + Holm + Storey). None coordinates per-vertical PHI handling (HIPAA 45 CFR 164.502/504/514 Safe Harbor + HHS OCR settlements when classifier output includes PHI) + attorney-client privilege (ABA Model Rule 7.1-7.5 + state bar 50-state) + FINRA Rule 2210 + SEC Regulation FD + GLBA. None gates against ECOA Reg B disparate-impact + Title VII + Fair Housing + EEOC AI Guidance 2024 + NYC Local Law 144 AEDT + EU AI Act Article 22 + Annex III + FRIA + SOX when public-company. None writes a per-message audit trail with regulatory-defense retention. The four-skill bundle Ingest + Classify + Gate + Audit sits above the customer-service + NLU + LLM + moderation substrate — it does not replace it.

How does Ingest + Classify work with replication-crisis discipline?

Ingest runs per-portfolio per-banner per-vertical per-channel per-message extraction from Salesforce Service Cloud + Zendesk + Freshdesk + Intercom + HubSpot Service + ServiceNow + Front + HelpScout + Kustomer + Gladly. Per-message metadata: customer + channel + vertical + previous-interaction-history + sentiment-history + intent-history + per-message PII classification + per-vertical sensitive-data flag (PHI + PCI + CPNI + financial + biometric). Per-vendor LLM zero-retention attestation. Classify runs multi-method classification: Hugging Face Transformers + spaCy + NLTK + TextBlob + VADER + RoBERTa + DistilBERT + DeBERTa + Sentence-BERT + BERTopic + Amazon Comprehend + Google Cloud Natural Language + Microsoft Text Analytics + IBM Watson NLU + Lexalytics + MonkeyLearn + per-vendor LLM (OpenAI GPT-4o + Anthropic Claude + Google Gemini + Mistral + Llama) classification. Per-message sentiment (negative + neutral + positive + mixed + sarcasm) + per-message intent (refund + escalation + termination + cancellation + churn-risk + cross-sell + upsell + complaint + compliment + question + bug-report). Vector-similarity via Pinecone + Weaviate + Chroma + Qdrant + Milvus + Vespa + Marqo. Replication-crisis discipline: per-test power-analysis + per-test pre-registration per Center for Open Science + AsPredicted + protocols.io + OSF + per-test-family multiple-comparisons (Bonferroni + BH FDR + Holm + Storey) + Rosenbaum + E-value + ASA p-value 2016/2019 + Brier + ECE + reliability + isotonic + Platt + Beta calibration + inter-rater agreement Krippendorff alpha + Cohen kappa + Fleiss + Gwet AC1.

What does this skill connect to on the customer-support-NLU agent and across the swarm?

On the customer-support-NLU agent: cs-agent-assist (parent commercial pillar) + chat-deflection compliance + multi-location review classification at scale (sibling build-pillar). Across the swarm: per-location AI review-response drafting (#565 same per-vertical compliance overlay) + voice-attribute extraction (#549 brand-voice canonical) + false-positive suppression (#574 same replication-crisis substrate) + multi-stream severity routing (#578 same regulatory-clock substrate) + buyer-state-aware BANT scoring (#568 same ECOA + EU AI Act Article 22) + governance-decision-router five-destination routing + master-record. Build-pillar siblings: tiered pre-filter deterministic gates for AI content compliance + marketing AI autonomy profile configuration + per-vertical compliance overlay. Commercial-pillar parent: /cs-agent-assist.

What does the 6-workstream pre-engagement-baseline reporting cycle look like for this skill?

Every two weeks during the Tier 3 Fractional CMO with AI Swarm engagement, six workstreams report against the pre-engagement baseline. Workstream 1: per-portfolio customer-service substrate coverage — service-platforms enrolled + per-platform LLM zero-retention attestation + per-vendor LLM cost reconciliation + per-vertical taxonomy. Workstream 2: Ingest per-message flow — per-message metadata + per-message PII classification + per-vertical sensitive-data flag + per-vendor zero-retention attestation. Workstream 3: Classify multi-method ensemble flow — Hugging Face + spaCy + RoBERTa + Amazon Comprehend + Google NLU + per-vendor LLM classification + vector-similarity + replication-crisis discipline + Brier + ECE + inter-rater agreement. Workstream 4: Gate-pass/gate-fail distribution — per-anchor gate-fail + per-vertical breakdown + ECOA disparate-impact + EU AI Act FRIA. Workstream 5: Regulatory-defense audit coverage — replication-crisis + Brier + ECE + inter-rater agreement + ECOA + Title VII + HIPAA Safe Harbor + ABA Model Rule + FINRA 2210 + EU AI Act Article 22 + Annex III + SOX. Workstream 6: FBC feedback-loop pattern-learning — per-vertical realized-vs-predicted classification + per-vendor recalibration + per-jurisdiction enforcement-update + per-vertical pattern shifts.

Build pillar · customer-support-NLU agent

How to build sentiment + intent classification for multi-vertical customer support

Salesforce Service Cloud + Zendesk + Freshdesk + Intercom + HubSpot Service + ServiceNow + Front + HelpScout + Kustomer + Gladly customer-service substrate + Hugging Face Transformers + spaCy + RoBERTa + DistilBERT + DeBERTa + Sentence-BERT + OpenAI GPT-4o + Anthropic Claude + Google Gemini + Mistral LLM + Amazon Comprehend + Google Cloud NLU + Microsoft Text Analytics + IBM Watson NLU + Lexalytics ship per-tenant flat sentiment + intent classification primitives. The Ingest + Classify + Gate + Audit skill bundle on the customer-support-NLU agent sits above the customer-service + NLU + LLM + moderation substrate and writes a per-message canonical record with named regulatory anchors covering replication-crisis discipline + Brier + ECE + inter-rater agreement + ECOA Reg B disparate-impact + Title VII + Fair Housing + HIPAA 45 CFR 164.502/504/514 Safe Harbor when MedicalBusiness + ABA Model Rule 7.1-7.5 when LegalService + FINRA Rule 2210 when FinancialService + EU AI Act Article 22 + Annex III + SOX 302/404/906.

Published December 16, 2026 · 3,200 words

The 4-skill bundle on the customer-support-NLU agent

One agent. Four coordinated skills. The Ingest + Classify + Gate + Audit bundle runs above the customer-service + NLU + LLM + moderation substrate under replication-crisis discipline and writes one canonical per-message record.

Ingest

Per-portfolio per-banner per-vertical per-channel per- message extraction from Salesforce Service Cloud + Zendesk + Freshdesk + Intercom + HubSpot Service + ServiceNow + Front + HelpScout + Kustomer + Gladly. Per-message metadata + interaction history + sentiment/intent history + per-message PII classification + per-vertical sensitive- data flag (PHI + PCI + CPNI + financial + biometric).

Classify

Multi-method ensemble: Hugging Face + spaCy + NLTK + VADER + RoBERTa + DistilBERT + DeBERTa + Sentence-BERT + Amazon Comprehend + Google NLU + Microsoft + IBM Watson + per- vendor LLM (OpenAI + Anthropic + Google Gemini + Mistral + Llama). Per-message sentiment + intent. Vector-similarity via Pinecone + Weaviate + Chroma + Qdrant + Milvus. Replication-crisis: pre-registration + Bonferroni + BH FDR + Storey + Rosenbaum + E-value + Brier + ECE + inter- rater agreement (Krippendorff + Cohen + Fleiss + Gwet AC1).

Gate

5 anchors per-message before consumer-impacting routing: replication-crisis pass + HIPAA Safe Harbor when MedicalBusiness + ABA Model Rule + FINRA Rule 2210 + GLBA + per-vertical + ECOA Reg B + 4/5ths rule + Title VII + Fair Housing + EEOC AI Guidance + NYC Local Law 144 + FCRA + CFPB Circular 2022-03 + EU AI Act Article 22 + Annex III + FRIA + SOX + FDD Item 12.

Audit

Per-message WORM record: classification snapshot + multi- method ensemble + calibration + inter-rater agreement + pre-registration + multiple-comparisons + per-anchor gate- pass + per-vertical applicability + AI-ML provenance + EU AI Act label + ECOA analysis + FRIA. Retention: 7-year FTC + 7-year IRS + 7-year HIPAA + 7-year state bar + 6-year SEC + 3-year FINRA + 4-year ECOA + 7-year SOX + GDPR Article 30 + EU AI Act Article 12 + SOC 2 CC7/CC8.

The real ecosystem this sits above

Ingest + Classify + Gate + Audit does not replace the customer-service platforms, NLU vendors, or LLM. It sits above them under replication-crisis discipline and writes one canonical per-message record.

Customer-service substrate

Salesforce Service Cloud + Zendesk + Freshdesk
Intercom + HubSpot Service + ServiceNow + Front
HelpScout + Kustomer + Gladly customer-service
Per-vertical taxonomy + per-message metadata
Per-vertical sensitive-data flag (PHI + PCI + CPNI)

NLU + LLM + moderation

Hugging Face Transformers + spaCy + NLTK + TextBlob
VADER + RoBERTa + DistilBERT + DeBERTa + Sentence-BERT
OpenAI GPT-4o + Anthropic Claude + Google Gemini
Mistral + Llama + Amazon Comprehend + Google NLU
Microsoft Text Analytics + IBM Watson + Lexalytics

Statistical + warehouse

Pinecone + Weaviate + Chroma + Qdrant + Milvus + Vespa
Hive + Spectrum Labs + Microsoft Content Moderator
OpenAI Moderation + Anthropic policy + Llama Guard
scipy.stats + statsmodels + scikit-learn classification
Snowflake + BigQuery + Databricks warehouse

Compliance overlay

Five anchors run per-message before any consumer-impacting routing decision commits. The first anchor is operationally distinctive: replication-crisis discipline + Brier + ECE + inter-rater agreement under multi-vertical sensitive-data handling.

Anchor 1: Replication-crisis + Brier/ECE + inter-rater agreement (operationally distinctive)

Ioannidis 2005 PLOS Medicine + Open Science Collaboration 2015. Per-test power-analysis + per-test pre-registration per Center for Open Science (cos.io) + AsPredicted + protocols.io + OSF. Per-test-family multiple-comparisons (Bonferroni + BH FDR + Benjamini-Yekutieli + Holm- Bonferroni + Hochberg + Sidak + Storey q-value). Rosenbaum bounds + E-value + Sensitivity Analysis. ASA p-value 2016/ 2019 + Nature 2019. Brier + ECE + reliability + isotonic + Platt + Beta calibration. Inter-rater agreement (Krippendorff alpha + Cohen kappa + Fleiss kappa + Gwet AC1).

Anchor 2: HIPAA + ABA + FINRA + per-vertical

HIPAA 45 CFR 164.502/504/514 Safe Harbor de-identification when healthcare customer-support PHI in input + HHS OCR enforcement + state mini-HIPAA + state medical board. ABA Model Rule 7.1-7.5 when LegalService + attorney-client privilege preservation + state bar 50-state. FINRA Rule 2210 when FinancialService + SEC Regulation FD + GLBA Safeguards Rule. FDA OPDP + DEA + alcohol + + COPPA when child customer.

Anchor 3: ECOA + Title VII + AI-ML disparate-impact

ECOA Reg B 12 CFR 1002 disparate-impact when classification drives consumer-impacting routing (refund + escalation + termination) + 4/5ths rule per Uniform Guidelines 1978 + Title VII + ADEA + ADA + Fair Housing + GINA + EEOC AI Guidance 2024 + NYC Local Law 144 AEDT + FCRA Section 604/615 + CFPB Circular 2022-03.

Anchor 4: EU AI Act Article 22 + DSA + privacy

EU AI Act Article 22 + 26 + 50 + Article 13/14/15 + Annex III high-risk when AI-ML classification drives consumer- impacting routing + Article 6/27 FRIA. DSA + DMA. GDPR Article 6/7/9 special category when health-support + Article 17/22 + Article 28/30. LGPD + DPDP + PIPEDA + Quebec Law 25 + CCPA + CPRA + COPPA + 18-state + Washington MHMDA + Texas SCOPE + state biometric.

Anchor 5: SOX + security + WORM retention

SOX 302/404/906 + COSO + Exchange Act 13(b)(2) + FASB ASC 606 + SEC Reg S-K + FDD Item 12 + 15-state franchise + state UDTPA. NIST AI RMF + ISO 42001 + ISO 27001 + ISO 27701 + SOC 2 Type II. Per-vendor LLM zero-retention + per-source DPA + per-API rate-limit. Policy-as-code via OPA Rego + AWS Cedar + Casbin + Cerbos + Oso + Styra DAS + Permit.io. Storage: AWS S3 Object Lock + Azure Blob immutable + GCS + Wasabi WORM. Retention: 7-year FTC + 7-year IRS + 7-year HIPAA + 7-year state bar + 6-year SEC + 3-year FINRA + 4-year ECOA + 7-year SOX + GDPR Article 30 + EU AI Act Article 12 + SOC 2 CC7/CC8.

6-workstream reporting cycle

Every two weeks during a Tier 3 Fractional CMO engagement, six workstreams report against the pre-engagement baseline. No forecast accuracy claims. Process commitments only.

1. Per-portfolio customer-service substrate coverage. Service-platforms + per-platform LLM zero-retention + per- vendor LLM cost reconciliation + per-vertical taxonomy.
2. Ingest per-message flow. Per-message metadata + PII classification + per-vertical sensitive-data flag + zero-retention attestation.
3. Classify multi-method ensemble flow. Hugging Face + spaCy + RoBERTa + Amazon Comprehend + Google NLU + per-vendor LLM + vector-similarity + replication- crisis + Brier + ECE + inter-rater agreement.
4. Gate-pass/gate-fail distribution. Per-anchor gate-fail + per-vertical breakdown + ECOA + EU AI Act FRIA.
5. Regulatory-defense audit coverage. Replication-crisis + Brier + ECE + inter-rater + ECOA + Title VII + HIPAA Safe Harbor + ABA Model Rule + FINRA 2210 + EU AI Act Article 22 + Annex III + SOX.
6. FBC feedback-loop pattern-learning. Per-vertical realized-vs-predicted classification + per- vendor recalibration + per-jurisdiction enforcement-update + per-vertical pattern shifts.

FAQ

What is sentiment + intent classification for multi-vertical customer support — and what is the per-vertical-PHI-times-ECOA-routing problem distinctive to this skill?: A multi-vertical operator runs customer-support agents across Salesforce Service Cloud + Zendesk + Freshdesk + Intercom + HubSpot Service + ServiceNow + Front + HelpScout + Kustomer + Gladly. Per-message sentiment + intent classification routes the message through downstream automation (refund + escalation + termination + cancellation + churn-risk + cross-sell + upsell). Verticals served include healthcare + legal + financial + retail + DTC + franchise + hospitality + technology + education + government. The four-skill bundle on the customer-support-NLU agent — Ingest, Classify, Gate, Audit — sits above the customer-service + NLU + LLM + moderation substrate and writes a per-message canonical record. The operationally distinctive anchor: per-vertical PHI handling when healthcare customer-support input contains PHI (HIPAA 45 CFR 164.502/504/514 Safe Harbor de-identification + HHS OCR enforcement) + attorney-client privilege when legal vertical (ABA Model Rule 7.1-7.5 + state bar 50-state) + FINRA Rule 2210 when financial vertical + ECOA Reg B disparate-impact when AI-ML classification drives consumer-impacting routing (refund + escalation + termination) + Title VII + ADEA + ADA + Fair Housing + EEOC AI Guidance 2024 + NYC Local Law 144 AEDT + EU AI Act Article 22 + Annex III high-risk + replication-crisis discipline (Brier + ECE + inter-rater agreement + Bonferroni + BH FDR + Rosenbaum + pre-registration + ASA p-value statement).
Why do Salesforce Service Cloud + Zendesk + Freshdesk + Intercom + Hugging Face + OpenAI + Anthropic + Amazon Comprehend + Google NLU + Microsoft Text Analytics + IBM Watson NLU break at multi-vertical-replication-crisis NLU classification scale?: Each customer-service vendor ships per-tenant flat ticket-classification + sentiment-score primitives. Each NLU vendor ships flat sentiment + intent label. Each LLM ships flat prompt response. None calibrates classification with replication-crisis discipline (Brier + Expected Calibration Error + reliability diagram + isotonic + Platt + Beta recalibration + Rosenbaum + E-value + ASA p-value statement + inter-rater agreement Krippendorff alpha + Cohen kappa + Fleiss + Gwet AC1 + pre-registration + per-test-family multiple-comparisons Bonferroni + BH FDR + Holm + Storey). None coordinates per-vertical PHI handling (HIPAA 45 CFR 164.502/504/514 Safe Harbor + HHS OCR settlements when classifier output includes PHI) + attorney-client privilege (ABA Model Rule 7.1-7.5 + state bar 50-state) + FINRA Rule 2210 + SEC Regulation FD + GLBA. None gates against ECOA Reg B disparate-impact + Title VII + Fair Housing + EEOC AI Guidance 2024 + NYC Local Law 144 AEDT + EU AI Act Article 22 + Annex III + FRIA + SOX when public-company. None writes a per-message audit trail with regulatory-defense retention. The four-skill bundle Ingest + Classify + Gate + Audit sits above the customer-service + NLU + LLM + moderation substrate — it does not replace it.
How does Ingest + Classify work with replication-crisis discipline?: Ingest runs per-portfolio per-banner per-vertical per-channel per-message extraction from Salesforce Service Cloud + Zendesk + Freshdesk + Intercom + HubSpot Service + ServiceNow + Front + HelpScout + Kustomer + Gladly. Per-message metadata: customer + channel + vertical + previous-interaction-history + sentiment-history + intent-history + per-message PII classification + per-vertical sensitive-data flag (PHI + PCI + CPNI + financial + biometric). Per-vendor LLM zero-retention attestation. Classify runs multi-method classification: Hugging Face Transformers + spaCy + NLTK + TextBlob + VADER + RoBERTa + DistilBERT + DeBERTa + Sentence-BERT + BERTopic + Amazon Comprehend + Google Cloud Natural Language + Microsoft Text Analytics + IBM Watson NLU + Lexalytics + MonkeyLearn + per-vendor LLM (OpenAI GPT-4o + Anthropic Claude + Google Gemini + Mistral + Llama) classification. Per-message sentiment (negative + neutral + positive + mixed + sarcasm) + per-message intent (refund + escalation + termination + cancellation + churn-risk + cross-sell + upsell + complaint + compliment + question + bug-report). Vector-similarity via Pinecone + Weaviate + Chroma + Qdrant + Milvus + Vespa + Marqo. Replication-crisis discipline: per-test power-analysis + per-test pre-registration per Center for Open Science + AsPredicted + protocols.io + OSF + per-test-family multiple-comparisons (Bonferroni + BH FDR + Holm + Storey) + Rosenbaum + E-value + ASA p-value 2016/2019 + Brier + ECE + reliability + isotonic + Platt + Beta calibration + inter-rater agreement Krippendorff alpha + Cohen kappa + Fleiss + Gwet AC1.
What does Gate + Audit do?: Gate runs 5 anchors per-message before any consumer-impacting routing decision commits. (1) Replication-crisis discipline pass + Brier + ECE + Rosenbaum + E-value + ASA p-value + pre-registration + inter-rater agreement. (2) HIPAA 45 CFR 164.502/504/514 Safe Harbor when healthcare customer-support PHI in input + HHS OCR + state mini-HIPAA + state medical board + ABA Model Rule 7.1-7.5 when LegalService + attorney-client privilege + state bar 50-state + FINRA Rule 2210 when FinancialService + SEC Regulation FD + GLBA Safeguards Rule + FDA OPDP + DEA + alcohol + + COPPA when child customer. (3) ECOA Reg B 12 CFR 1002 disparate-impact when classification drives consumer-impacting routing (refund + escalation + termination) + 4/5ths rule + Title VII + ADEA + ADA + Fair Housing + GINA + EEOC AI Guidance 2024 + NYC Local Law 144 AEDT + FCRA Section 604/615 + CFPB Circular 2022-03. (4) EU AI Act Article 22 + Article 26 + Article 50 + Article 13/14/15 + Annex III high-risk when AI-ML classification drives consumer-impacting routing + Article 6/27 FRIA + DSA + DMA. (5) SOX 302/404/906 when public-company classification material to financial reporting + COSO + Exchange Act 13(b)(2) + FASB ASC 606 + SEC Reg S-K + FDD Item 12 + 15-state franchise + state UDTPA + GDPR Article 6/7/9 special category when health-support + Article 17/22 + Article 28/30 + LGPD + DPDP + PIPEDA + Quebec Law 25 + CCPA + CPRA + 18-state + Washington MHMDA + Texas SCOPE + state biometric. Audit writes a per-message WORM canonical record: classification snapshot + multi-method ensemble + calibration metrics + inter-rater agreement + per-test pre-registration + multiple-comparisons applied + per-anchor gate-pass + per-vertical applicability + AI-ML provenance + EU AI Act transparency label + ECOA disparate-impact analysis + FRIA artifact. Storage: AWS S3 Object Lock + Azure Blob immutable + GCS + Wasabi WORM. Retention: 7-year FTC + 7-year IRS + 7-year HIPAA + 7-year state bar + 6-year SEC + 3-year FINRA + 4-year ECOA + 7-year SOX + GDPR Article 30 + EU AI Act Article 12 + SOC 2 CC7/CC8.
What does this skill connect to on the customer-support-NLU agent and across the swarm?: On the customer-support-NLU agent: cs-agent-assist (parent commercial pillar) + chat-deflection compliance + multi-location review classification at scale (sibling build-pillar). Across the swarm: per-location AI review-response drafting (#565 same per-vertical compliance overlay) + voice-attribute extraction (#549 brand-voice canonical) + false-positive suppression (#574 same replication-crisis substrate) + multi-stream severity routing (#578 same regulatory-clock substrate) + buyer-state-aware BANT scoring (#568 same ECOA + EU AI Act Article 22) + governance-decision-router five-destination routing + master-record. Build-pillar siblings: tiered pre-filter deterministic gates for AI content compliance + marketing AI autonomy profile configuration + per-vertical compliance overlay. Commercial-pillar parent: /cs-agent-assist.
What does the 6-workstream pre-engagement-baseline reporting cycle look like for this skill?: Every two weeks during the Tier 3 Fractional CMO with AI Swarm engagement, six workstreams report against the pre-engagement baseline. Workstream 1: per-portfolio customer-service substrate coverage — service-platforms enrolled + per-platform LLM zero-retention attestation + per-vendor LLM cost reconciliation + per-vertical taxonomy. Workstream 2: Ingest per-message flow — per-message metadata + per-message PII classification + per-vertical sensitive-data flag + per-vendor zero-retention attestation. Workstream 3: Classify multi-method ensemble flow — Hugging Face + spaCy + RoBERTa + Amazon Comprehend + Google NLU + per-vendor LLM classification + vector-similarity + replication-crisis discipline + Brier + ECE + inter-rater agreement. Workstream 4: Gate-pass/gate-fail distribution — per-anchor gate-fail + per-vertical breakdown + ECOA disparate-impact + EU AI Act FRIA. Workstream 5: Regulatory-defense audit coverage — replication-crisis + Brier + ECE + inter-rater agreement + ECOA + Title VII + HIPAA Safe Harbor + ABA Model Rule + FINRA 2210 + EU AI Act Article 22 + Annex III + SOX. Workstream 6: FBC feedback-loop pattern-learning — per-vertical realized-vs-predicted classification + per-vendor recalibration + per-jurisdiction enforcement-update + per-vertical pattern shifts.

Engage Completions

Two ways to engage. The Tier 1 AI Readiness Assessment maps the customer-service + NLU + LLM + moderation substrate + per-vertical sensitive-data + replication-crisis surface against the Ingest + Classify + Gate + Audit bundle. The Tier 3 Fractional CMO with AI Swarm embeds 1-2 days per week for 6+ months and runs the bundle end-to-end against the customer- support-NLU agent across the swarm.

Tier 1 AI Readiness Assessment Tier 3 Fractional CMO with AI Swarm Not sure which tier? Take the 3-question quiz