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Simulated proof asset · US law firms · Updated 2026-07-12

US law firm AI intake confidentiality diagnostic example

A transparent synthetic proof-of-work showing how AICloudStrategist maps phone, web form, live chat, SMS, voicemail, paid-search and referral intake into missed-call, after-hours, conflict-screening and confidentiality prompt review queues before recommending AI automation.

View the diagnostic package Back to proof hub

Honesty label

This is a simulated internal proof-of-work asset. It uses synthetic law firm intake rows only. It is not a real customer case study, not production data, not confidential information, not a testimonial, not an attorney-client relationship and not evidence that any firm gained leads, signed clients, cases, revenue or rankings.

Why this asset exists

AICS has a buyer-ready US law firm AI intake confidentiality diagnostic package. This proof page shows the operating logic behind that offer: expose intake-source leakage, after-hours queues, missed-call callbacks, conflict-screening handoffs, CRM stage gaps and approved no-legal-advice / confidentiality-safe prompt boundaries before adding AI chat, voice or CRM follow-up.

Synthetic input summary

MetricResult from synthetic sampleDiagnostic meaning
Intake-source rows reviewed10Small synthetic sample for demonstrating method, not a real firm export.
Inquiries modelled154Demand pool requiring source, practice-area, owner and status visibility.
Missed calls33Calls requiring callback evidence before AI receptionist changes.
After-hours inquiries73 (47.4%)Partner-visible queue for triage, disclaimers and next-business-day ownership.
Callback-within-2h coverage on missed calls24 / 33 (72.7%)Measured service-level gap; not a signed-client or revenue claim.
Conflict-screened inquiries68 / 154 (44.2%)Shows where AI or CRM follow-up must hand off before sensitive facts are collected.
Inquiries lacking confidentiality/no-legal-advice prompt boundary108Rows needing approved script boundaries before automation is expanded.
Late conflict-screening review pool119Partner review queue, not legal or ethics advice.

Partner review queue from the synthetic run

PrioritySourcePractice areaEvidence gapOwner
1Google Business ProfileCriminal defense7 missed calls; 12 after-hours; missing prompt boundary; 12 not conflict-screenedIntake manager
2Website chatbotBusiness litigation7 after-hours; missing prompt boundary; 11 not conflict-screenedMarketing
3PhoneFamily law9 missed calls; 8 after-hours; missing prompt boundary; 14 not conflict-screenedReception lead
4VoicemailProbate11 missed calls; 9 after-hours; missing prompt boundary; 12 not conflict-screenedReception lead
5Paid search landing pagePI mass tort4 missed calls; 11 after-hours; missing prompt boundary; 12 not conflict-screenedMarketing
6Live chatEstate planning10 after-hours; missing prompt boundary; 12 not conflict-screenedMarketing

Owner-dashboard proof pack

  1. Phone, voicemail, website form, live chat, SMS, paid search and referral intake counts by source and practice area.
  2. Missed-call and after-hours queues with callback timestamp, owner and next-action fields.
  3. Conflict-screening handoff status before sensitive facts or legal questions are collected.
  4. Approved no-legal-advice and confidentiality-safe prompt boundaries for AI chat, voice or CRM automation.
  5. CRM stage map showing new, contacted, unqualified and partner-review rows.
  6. Weekly partner dashboard with leakage, SLA, handoff and exception notes.
  7. Written approval before any real case study, testimonial, logo, lead-volume, client, case-win or revenue claim.

Reproducible artifact

The source model and generated markdown report are stored internally at /home/agent/.hermes/aicloudstrategist/case-studies/simulated-us-law-firm-ai-intake-confidentiality-2026-07-12/. Inputs are explicit in sample_intake_log.csv; calculations are deterministic and labelled as simulated.

Verification: python3 law_firm_intake_diagnostic.py regenerated the report with rows=10, total_inquiries=154, missed_calls=33, after_hours=73, callback_coverage=0.727, conflict_coverage=0.442, no_conf_prompt_inquiries=108, late_conflict_inquiries=119 and callback_gap=9. Input SHA256: 321e5a8580a9499a6f9b4ea278114472635eca2818909a7f9dfc3172804c3ba0.

Claim boundary

No real US law firm, client, prospect, production data, confidential information, attorney-client relationship, logo, testimonial, legal advice, ethics advice, bar-compliance advice, confidentiality advice, privilege advice, advertising advice, security audit, compliance certification, case result, signed client, lead-volume increase, revenue, ranking, platform partnership or AI accuracy guarantee is claimed. This means no legal advice, no ethics advice, no bar approval, no confidentiality guarantee, no security guarantee and no revenue guarantee. Real implementation would require explicit scope, data-handling approval, firm-approved policies, payment route and written authorization before any public proof use.