FirmaTRUST helps you safely put AI to work. We design governance, provide 24/7 monitoring to protect your data, and build automation to accelerate your business, backed by 30 years of managed IT and cybersecurity expertise.
AI tools are in your workflows today, whether you approved them or not. Without governance and monitoring, your most valuable data is exposed to misuse, leakage, and risk.
FirmaTRUST puts guardrails in place with AI policy, governance, and real-time monitoring, so your team can use AI with confidence.
Clear, enforceable AI policies covering acceptable use of AI tools (such as OpenAI, Claude, ChatGPT, Microsoft Copilot, and Google Gemini), data classification and restrictions for PII, PHI, and financial data, prompt security and data leakage prevention, employee accountability standards, and regulatory alignment with HIPAA, GDPR, SOC 2, and more.
Deliverable:
Custom AI Acceptable Use Policy
Executive Summary
Staff Acknowledgment Form
We design and implement an AI governance structure that includes an AI Risk Assessment and Readiness Audit, risk tiering for AI tools, model-usage approval workflows, data retention and audit logging standards, and alignment with cybersecurity and compliance frameworks.
Deliverable:
AI Governance Framework Document
Risk Register
Technical safeguards that reduce AI-related risk: AI application discovery and monitoring, SaaS access control policies, DLP integration for AI platforms, API security and logging, endpoint AI usage controls, and Zero Trust integration. We help prevent data leakage into public LLMs, prompt injection attacks, model manipulation, and IP exposure.
Deliverable:
Enterprise-grade AI guardrails fully implemented
A routine training program covering responsible AI use, secure prompting best practices, AI phishing and social engineering awareness, compliance-focused AI training, and executive AI risk briefings.
Deliverable:
Employee training on the company’s AI policy and governance, because a policy nobody understands isn’t a policy at all
We design and implement an AI governance structure that includes an AI Risk Assessment and Readiness Audit, risk tiering for AI tools, model-usage approval workflows, data retention and audit logging standards, and alignment with cybersecurity and compliance frameworks.
Deliverable:
Continuous AI risk visibility and control-24/7/365
Collects AI usage signals from users, devices, applications, and network traffic.
See AI usage Across your environment
Analyzes data to identify AI applications, usage patterns, and potential risks.
Applies policies to allow, block, monitor, or protect AI interactions in real time.
Maintains a centralized inventory of AI tools, models, agents, and supporting evidence.
Establishes policies, approval workflows, risk management, and regulatory compliance.
Fragmented documents, siloed platforms, and complex integrations keep AI from delivering real productivity. And when vendor roadmaps shift, a wrong integration decision becomes tomorrow’s technical debt.
FirmaTRUST delivers the technical execution and strategic foresight to make AI work across your organization, without disruption, risk, or replatforming.
FirmaTRUST develops AI agents and automation workflows that automate and optimize your operations. We plan and design your automation workflows, then implement them with a disciplined, use-case-first approach
Identify high-friction, repetitive workflows worth automating. Map current processes, who owns them, time spent, error rates, and cost. Prioritize by ROI potential and feasibility.
Narrow to one specific workflow (e.g., ticket triage, lead follow-up, report generation). Define measurable outcomes: hours saved, response time, accuracy, and cost per task.
Document inputs, outputs, decision points, and edge cases. Audit what data and systems the agent needs access to (CRM, email, docs, APIs) and confirm data quality and availability.
Choose the stack: LLM/agent framework (e.g., Claude, Claude Code), orchestration layer (e.g., n8n, Make, custom), integrations, and where it runs (cloud, on-prem, workstation). Decide agent design: single agent vs. multi-agent, human-in-the-loop checkpoints.
Define access controls, credential management, data handling policies, and audit logging. Align with relevant frameworks (SOC 2, HIPAA, GDPR, etc.) before anything touches production data.
Develop a minimal working version of the agent workflow. Write and refine system prompts, connect integrations, and build guardrails (validation, fallbacks, escalation paths to humans).
Run the agent against real-world scenarios and edge cases. Measure accuracy, failure modes, and hallucination risk. Iterate on prompts, logic, and error handling until output is consistently reliable.
Launch with a limited user group or a single department. Keep humans in the loop for review and approval. Collect feedback and monitor performance against the Step 2 metrics.
Deploy company-wide with documentation, training, and clear escalation procedures. Communicate what the agent does, its limits, and how employees interact with it.
Continuously track performance, costs, and drift. Refine prompts and logic as processes evolve. Identify adjacent workflows to expand into, turning the single agent into a portfolio of automations.
