As AI systems and autonomous agents move into courts, clinics, banks, classrooms, streets, factories, and power grids, small mistakes can snowball into serious harm. Picture livelihoods erased by quiet shadow bans, triage tools that misprioritize high‑risk patients, fraud scaled by automated decisioning, grid instability from brittle automations, and reputations wrecked by confidently wrong "facts." On the road, self‑driving cars can misread lane markings, fail to detect pedestrians at dusk, or over‑trust faulty maps—leading to collisions and near‑misses in school zones. In homes and workplaces, robots can misclassify humans as obstacles, grip too hard, or skip safety interlocks—resulting in injuries and property damage. Children are uniquely exposed: recommendation loops that push harmful content, biometric misidentification in schools, grading assistants that amplify bias, and location‑sharing toys that leak private data. In healthcare, we have seen assistive radiology overlook acute intracranial bleeds later found in surgery, sepsis risk scores down‑rank patients who then decompensate, and oncology decision support suggest contraindicated dosing tied to fatal toxicity. These aren’t mere model glitches—they are system breakdowns where sloppy prompts, stale inputs, hidden overrides, or unvetted integrations distort human judgment. The remedy is disciplined forensics that reconstructs the chain of control and chain of decisions—who or what acted, when, and why—so we can establish causality, assign accountability, and repair the stack, not just the headlines. Our team helped build leading clinical AI platforms and spent over a decade at Google investigating large‑scale fraud and abuse. We operate a hardened platform with enterprise‑grade security and end‑to‑end observability to run investigations, anchored by human oversight and seasoned judgment throughout.
Automated, verifiable chain-of-custody workflows for files, logs, endpoints, and cloud artifacts, including immutable hashing, timestamping, and custody event journaling. Supports on-prem and cloud sources (EHR, SIEM, CI/CD, RAG indexes, agent transcripts), with selective redaction, PII minimization, and locale-aware metadata capture.
Multi-agent reasoning to map timelines, anomalies, and probable root causes across prompts, tools, policies, and integrations. Correlates user actions, model versions, feature flags, and environment drift; highlights causal chains and counterfactuals that withstand adversarial review.
Court-ready summaries with explainable steps, reproducible methods, and exhibits suitable for civil, criminal, and regulatory proceedings. Includes sworn declarations, Daubert-informed methodology disclosures, and appendices for opposing expert replication.
Native handling of multilingual artifacts (documents, chats, logs) with certified translations and dialect-aware nuance checks. Provides in-court expert testimony, interpreter-coordinated briefings, and parallel-language report sets (EN, ES, FR, DE, PT, IT, ZH, JA, KO, AR) with terminology glossaries.
Expert reports, affidavits, voir dire preparation, demonstratives, and cross-examination readiness. Real-time trial war room for evidence callouts, chain validation, and on-the-fly model/version attribution during depositions and hearings.
Mappings to GDPR/CCPA, HIPAA, SOC 2, ISO 27001, NIST AI RMF, and EU AI Act obligations. Produces bilingual regulatory packets and multi-jurisdictional findings suitable for international disclosures and supervisory inquiries.
Region-specific risk analysis that accounts for local norms, legal definitions, and linguistic ambiguity. Ensures prompts, safety policies, and content moderation are evaluated against the correct cultural and legal backdrop.
Remediation playbooks, guardrail upgrades, and change-management guidance. Provides bilingual runbooks and user training to prevent recurrence, with dashboards to monitor post-incident drift, bias, and safety regressions.
Reduce investigation time from weeks to hours without sacrificing rigor. Our platform pairs expert oversight with autonomous agents for speed, transparency, and defensibility. Our agent architecture runs in auditable code and does not use unexplainable AI for orchestration - who watches the watchers? Quis custodiet ipsos custodes. All work product is delivered and managed in a private Google Workspace, which also houses complete logs and records of the forensic agents within a SOC 2 security perimeter.
We handle end-to-end inquiries across models, agents, and infrastructure—collecting artifacts, reconstructing timelines, and producing court-ready reports.
Hallucinations, toxic outputs, data leakage, jailbreak abuse, prompt injection, and prompt drift impacting safety or compliance.
Disparate outcomes in lending, hiring, healthcare triage, and moderation; root-cause analysis with counterfactual testing.
Click fraud, account takeovers, synthetic identity rings, affiliate abuse, and bot-driven manipulation across platforms.
Tool misuse, unsafe action plans, escalation loops, missing human-in-the-loop checkpoints, and autonomy guardrail bypasses.
Poisoned datasets, compromised model weights, malicious packages, and CI/CD tampering affecting model integrity.
Credential leaks via embeddings, prompt exfiltration, RAG data exposure, SSRF through tools, and lateral movement by agents.
Missing audit trails, undocumented model versions, unlawful data processing, and violations of internal AI policies.
Incident postmortems for outages tied to model updates, latency spikes from tool chains, and cost/runaway usage anomalies.
GDPR, CCPA/CPRA, HIPAA, SOC 2, ISO 27001, and PCI-DSS aligned workflows with data minimization, DSR support, and audit-ready logs.
Copyright infringement detection, DMCA takedown support, trademark misuse monitoring, model output provenance, and license compliance.
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