Automations
This pillar addresses governance workflows that monitor decisions, record rationale, and produce defensible explanation layers for legal, ethical, and operational review. Pages should show how custom audit-trail systems connect operations, interpretability tooling, and policy enforcement to support regulated AI deployment without stalling delivery.
This foundational page details the architecture for a custom governance workflow that ingests operational logs, model outputs, and user actions to produce immutable, queryable audit trails. It explains how to build a system that reduces compliance risk and manual evidence gathering by automating the capture of decision rationale, data lineage, and approval states across AI-driven operations.
This workflow automates the continuous scanning of regulatory publications, news, and legal databases to identify relevant changes, assess impact, and route alerts to compliance teams. The page covers the architecture for parsing unstructured text, mapping regulations to internal controls, and triggering policy update workflows, significantly reducing the lag and labor of manual monitoring.
This page details a custom workflow where specialized agents monitor system actions against policy rules, automatically enforce controls, and route policy violations through structured exception and approval paths. It explains how this architecture reduces manual oversight, standardizes enforcement, and creates a defensible log of all policy decisions and overrides.
This workflow automates the systematic gathering, validation, and packaging of evidence from disparate systems (ERP, CRM, IAM) to support internal and external audits. The page explains the integration architecture, data validation logic, and secure evidence locker design that cuts manual evidence collection effort by 70-80% while improving audit readiness.
This page outlines a custom workflow that automates the tracking of model versions, performance drift, bias metrics, and validation results, triggering revalidation or retirement alerts. It covers the integration of MLOps pipelines with governance systems to provide a continuous, auditable record of model health and compliance for regulated AI deployments.
This workflow uses agents to execute predefined control tests (e.g., access reviews, configuration checks), analyze results, and automatically generate deficiency reports with remediation assignments. The page details the test orchestration, exception classification, and integration with GRC platforms to transform control testing from a quarterly manual exercise to a continuous automated process.
This page explains a custom workflow that pulls validated data from source systems, applies regulatory formatting and calculation logic, and generates draft reports (e.g., Call Reports, Solvency II) for review. It covers the data pipeline, calculation engine, and human-in-the-loop approval gates required to reduce reporting cycle times and errors.
This workflow creates an immutable, context-rich audit trail for every transaction, logging the AI models, rules, and human approvals involved in decisions like trade execution or loan origination. The page details the event-sourcing architecture and integration with core banking systems to meet stringent regulatory demands for explainability and reconstructability.
This page details a custom agentic workflow that maps financial processes to controls, automates evidence collection for key SOX controls, and maintains up-to-date process documentation (narratives, flowcharts). It explains how this system reduces the annual SOX scramble, lowers external audit fees, and provides real-time compliance visibility.
This workflow automates the detection and classification of personal data, manages consent records, processes data subject access requests (DSARs), and triggers data deletion workflows. The page covers the data discovery, policy engine, and case management architecture needed to operationalize privacy compliance at scale.
This page explains a workflow that automatically tags data with jurisdiction classifications, monitors data flows against localization rules (e.g., China's PIPL, Russia's Data Localization Law), and triggers alerts or blocking actions. It details the integration with data loss prevention (DLP) and storage systems to prevent costly compliance violations.
This workflow automates the application of retention schedules to records and documents, sending legal hold notifications, and triggering secure, logged disposal events upon schedule expiry. The page covers integration with content management and email archiving systems to eliminate manual record reviews and reduce legal discovery risk.
This page details a workflow that structures the ethical review of proposed AI applications, tracks approved use cases, and continuously monitors deployed models for adherence to ethical guidelines. It explains the orchestration of review boards, bias detection tools, and incident logging to build trust and mitigate reputational risk.
This workflow automates the monitoring of employee trading activity against restricted lists, earnings calendars, and material non-public information (MNPI) access logs. The page covers the data fusion, pattern detection, and case management architecture that reduces false positives and accelerates investigation of potential violations.
This page explains a workflow where agents intake and anonymize whistleblower reports, triage them based on severity and policy, and route them to the appropriate investigators with relevant evidence assembled. It details the secure portal, NLP classification, and workflow orchestration that ensures consistent, timely, and confidential handling of reports.
This workflow automates the screening of customers, transactions, and counterparties against global sanctions lists, using AI to reduce false positives by analyzing context before escalating true hits. The page details the integration with payment and CRM systems, the fuzzy matching logic, and the audit trail required for regulatory examinations.
This page outlines a workflow that extracts key obligation terms from contracts, connects them to operational data sources, and monitors for compliance or potential breaches, triggering alerts to legal and business owners. It covers CLM integration, data connector design, and reporting dashboards that transform static contracts into active governance instruments.
This workflow tracks expiration dates for professional licenses, software licenses, and facility permits, automatically gathering renewal requirements, initiating applications, and routing them for approval. The page explains the database integration, document assembly, and notification logic that prevents costly lapses in operational authority.
This page details a workflow that automatically scans code repositories for open-source components, identifies their licenses and vulnerabilities, and flags compliance issues (e.g., GPL violations) for remediation. It covers integration with SDLC tools, policy engines, and bill of materials (SBOM) generation to manage software supply chain risk.
This workflow automates the determination of export control classifications (ECCN) for products and technology, screens international shipments against denied party lists, and ensures proper documentation. The page explains the integration with product lifecycle management (PLM) and logistics systems to prevent violations of ITAR, EAR, and other regulations.
This page explains a workflow that ingests risk-weighted asset data, applies evolving Basel regulatory formulae, and performs the calculations for capital adequacy reporting (Pillar 1). It details the data validation, calculation engine, and audit trail architecture that reduces manual effort and improves accuracy for large financial institutions.
This workflow goes beyond batch processing to monitor transactions in real-time, using network analysis and anomaly detection to identify suspicious activity, and then auto-drafts Suspicious Activity Reports (SARs) for investigator review. The page covers the high-throughput data pipeline, alert scoring, and integration with FinCEN reporting systems.
This page details a workflow where agents analyze claims for red flags, cross-reference data against historical patterns and external databases, and automatically route high-risk cases to special investigation units (SIUs) with a compiled evidence package. It explains the architecture for reducing false positives and accelerating the identification of fraudulent claims.
This workflow automates the complex data aggregation, actuarial calculation, and disclosure reporting required under new insurance accounting standards like IFRS 17 and LDTI. The page covers the integration with policy administration and general ledger systems, the calculation orchestration, and the controlled reporting outputs needed for audit.
This page outlines a workflow that automates the analysis of investment recommendations against a customer's profile and objectives to ensure compliance with Reg BI and suitability rules. It details the integration with order management and CRM systems, the rationale logging, and the exception handling required for broker-dealers and advisors.
This workflow monitors access to electronic protected health information (ePHI), detects potential breaches (unauthorized access, data exfiltration), and automates the steps for risk assessment and regulatory notification if required. The page covers log aggregation, pattern detection, and workflow integration with legal and communications teams.
This workflow compares patient data and site activities against the clinical trial protocol in near real-time, flagging deviations (e.g., missed visits, out-of-range vitals) for immediate review. The page explains integration with EDC and EHR systems, reducing monitoring costs and improving data quality and patient safety.
This page details a workflow that manages the lifecycle of patient consents for treatment, research, and data sharing, tracking versions, expirations, and revocations, and automatically enforcing restrictions in downstream systems. It covers the consent repository, API integrations, and audit trail critical for trust and compliance.
This workflow enforces FDA Part 11 requirements for electronic records in life sciences by automating audit trail generation, signature verification, and access control checks across lab, manufacturing, and quality systems. The page details the agent-based monitoring and validation architecture that replaces manual checks.
This workflow ingests adverse event reports from multiple sources, uses NLP to triage and validate signals, and auto-populates regulatory reports (CIOMS, MedWatch) for medical review and submission. The page explains the pipeline that accelerates time-to-detection and reduces the manual burden of case processing.
This workflow automates the collection of evidence for quality, environmental, and health & safety management systems, maps it to ISO clause requirements, and generates pre-audit readiness dashboards. The page covers integration with QMS, EMS, and operational systems to turn certification audits from a disruptive project into a continuous process.
This workflow monitors customer complaints, supplier quality data, and production logs for safety signals, triggers risk assessments, and if needed, orchestrates the recall process including regulatory notifications and customer communications. The page details the cross-system data fusion and workflow automation that minimizes brand damage and liability.
This page explains a workflow where agents monitor process data, equipment inspections, and training records against PSM/RMP requirements, automatically generating compliance reports and flagging gaps for remediation. It covers integration with SCADA, maintenance, and HR systems for high-risk industrial facilities.
This workflow automates the collection and scoring of supplier quality data (e.g., defect rates, audit findings), triggers corrective action (CAPA) requests, and tracks them to closure. The page details integration with ERP and SQM systems, reducing the administrative load on quality engineers and improving supply chain resilience.
This workflow continuously pulls logs, configurations, and policy documents from cloud infrastructure and SaaS applications, compiling them into organized evidence packages for SOC 2 audits. The page explains the multi-cloud integration, evidence validation, and auditor collaboration portal that streamlines the annual compliance cycle for tech companies.
This workflow automatically generates and maintains an accurate, up-to-date SBOM for applications, monitors components for new vulnerabilities or license changes, and triggers remediation workflows. The page details integration with CI/CD pipelines and vulnerability databases, which is critical for meeting software supply chain security mandates.
This workflow ingests DPAs, extracts data handling obligations (location, deletion, subprocessor use), and monitors cloud and data platform configurations for compliance, alerting on deviations. The page covers the NLP extraction, configuration management database (CMDB) integration, and reporting needed for cloud-centric enterprises.
This workflow ingests penetration test reports, parses findings and severity, automatically creates tickets in development and ops trackers, and monitors remediation progress against SLAs. The page explains the orchestration between security, DevOps, and GRC tools that closes the loop on vulnerability management and satisfies audit requirements.
This workflow pulls performance metrics from application and infrastructure monitors, calculates SLA compliance in real-time, and generates breach notifications and root-cause analysis reports. The page details the data aggregation, calculation engine, and integration with billing and customer success systems for SaaS and managed service providers.
This workflow automates the monitoring and evidence collection for NERC CIP standards, such as access control logs for critical cyber assets, patch management status, and personnel training records. The page explains the integration with OT/IT security tools and the audit-ready reporting that utilities need to avoid massive penalties.
This workflow ingests sensor data, inspection reports, and maintenance records from pipeline operations, checks them against PHMSA integrity management rules, and flags potential non-compliances. The page details the IoT data pipeline and regulatory rule engine that helps pipeline operators proactively manage safety and avoid incidents.
This workflow automates the metering, aggregation, and certification of renewable energy generation to produce verified RECs, and handles the reporting for compliance markets (RPS) and voluntary claims. The page covers integration with generation assets, registry APIs, and settlement systems to monetize clean energy and meet mandates.
This workflow validates product formulations and packaging artwork against global regulations for ingredients, allergens, nutrition facts, and claims (e.g., FDA, EU, China). The page explains integration with PLM and formulation systems, preventing costly relabeling, recalls, and blocked shipments for CPG and food companies.
This workflow maps multi-tier supplier relationships, collects and validates social compliance data (audits, certifications), and auto-generates mandatory modern slavery statements. The page details the supplier portal, data verification logic, and reporting engine that turns a complex manual exercise into a managed operational process.
This workflow captures every data point, model score, and rule outcome used in a credit decision, synthesizing them into a clear, auditable rationale for approval or denial. The page details the integration with underwriting engines and core banking systems, which is essential for fair lending compliance (ECOA) and customer dispute resolution.
This workflow logs all inputs (images, lab results, notes), model inferences, confidence scores, and clinician interactions within an AI diagnostic support tool, creating a complete audit trail for clinical validation and liability protection. The page covers the immutable logging architecture and integration with hospital information systems.
This page details a workflow where agents extract key decision factors from underwriting models and policy rules, assemble supporting documents, and generate a comprehensive, plain-language approval or denial letter. It explains the architecture that satisfies regulatory demands for explainability (like the FTC's 'logic and factors') while reducing manual documentation.
This workflow creates a detailed log for every content moderation action (flag, review, decision), capturing the policy violated, the AI/ human reviewer rationale, and enabling a structured appeal process. The page explains the case management and audit system that platforms need to demonstrate consistent, fair enforcement and defend against legal challenges.
This workflow automatically generates a detailed, compliant explanation for claim denials, citing specific policy language and investigation findings, and logs all related communications. The page details integration with claims systems and document generation, reducing disputes and providing a clear audit trail for state insurance department reviews.
This workflow automates the initial triage of security alerts, enriches them with context, executes predefined containment playbooks, and logs every action for post-incident review and audit. The page covers SOAR integration, timeline generation, and reporting that reduces mean time to respond (MTTR) and satisfies regulatory reporting requirements.
This workflow ingests data from incident reports, system failures, and external feeds to automatically identify, categorize, and score operational risk events, generating reports for management and regulators (e.g., ORSA). The page explains the data pipeline and risk aggregation logic that moves risk management from reactive to proactive.
This workflow automatically routes customer-reported defects to the appropriate engineering and quality teams, triggers root cause analysis (RCA), and compiles the investigation findings and corrective actions into a governed document. The page details integration with CRM, Jira, and QMS systems to accelerate resolution and improve product quality.
This workflow parses auditor requests for information (RFIs), identifies the relevant data sources and documents across the enterprise, extracts and validates the data, and assembles it into a secure, organized response package. The page explains the agent orchestration and data lake integration that cuts the manual labor of audit support by over 50%.
This workflow uses AI to identify, collect, and review potentially relevant documents from email, file shares, and collaboration tools in response to legal holds and discovery requests, logging the entire chain of custody. The page details the integration with e-discovery platforms and the defensible process that reduces legal spend and risk.
This workflow automates the versioning, approval, and assembly of documents for major regulatory submissions (e.g., FDA NDA, EMA MAA), ensuring only approved versions are included and creating a complete submission audit trail. The page explains integration with document management systems (Veeva, Documentum) and publishing tools.
This workflow manages the lifecycle of company policies: drafting, review, approval, publication to relevant employees, tracking of read acknowledgments, and managing attestations. The page details the CMS integration and notification logic that ensures policy awareness and creates a verifiable record for audits.
This workflow automates the collection of vendor information, performs automated risk scoring based on financials, cybersecurity, and compliance data, and routes the onboarding packet through approval chains based on risk tier. The page explains integration with procurement and third-party risk platforms, slashing onboarding time while improving due diligence.
This workflow guides requesters through a structured business case, automatically pulls relevant financial and operational data, and routes the proposal through multi-level approvals with a complete log of justifications and decisions. The page details integration with ERP and planning systems, bringing transparency and auditability to spending controls.
This workflow continuously monitors deployed AI models for statistical bias across protected attributes (race, gender, age), triggers alerts when thresholds are breached, and logs all mitigation actions taken. The page explains the integration with model serving platforms and fairness toolkits, which is critical for ethical AI governance and regulatory compliance (like NYC's AI bias law).
This workflow processes data subject deletion requests by identifying all instances of a customer's personal data across databases, applications, and backups, orchestrating secure deletion, and providing verification logs. The page details the data discovery and workflow engine required to operationalize GDPR Article 17 and CCPA requests at scale.
This workflow continuously scans cloud infrastructure (AWS, Azure, GCP) against CIS Benchmarks, detects configuration drift, auto-remediates where possible, and creates tickets for manual intervention, all with a full change log. The page explains the agent-based architecture that maintains a strong security posture and provides evidence for audits.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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We add the checks and visibility needed to keep it useful.
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