8 tools. 5 ordered guardrails. 3 pluggable LLM providers (Anthropic, OpenAI, Bedrock). End-to-end OpenTelemetry observability into Tempo/Loki/Grafana.
View the portfolio →GenAI and AppSec Advisory for Regulated Industries
Your CISO needs to sign off. Your engineers want to ship. That gap is the engagement.
Be Digital advises technology and security teams at banking, insurance, asset management, and healthcare payer organizations on how to deploy generative AI systems that satisfy compliance requirements without stalling the engineering roadmap.
Start a conversationWhy regulated industries need a different approach
Deploying generative AI that drafts, monitors, and scans inside a regulated environment is not a model selection problem — it is a controls problem. Banking institutions under SR 11-7, insurance carriers with NAIC guidance, and healthcare payers subject to HIPAA all operate under model risk management frameworks that require explainability, auditability, and documented human oversight. Dropping an LLM into a workflow without addressing those requirements creates regulatory exposure that the security team will discover at the worst possible time.
The Model Context Protocol (MCP) server built for this advisory practice is a reference implementation of exactly those controls. It runs eight tools through five ordered guardrails — input sanitization, prompt injection detection, policy enforcement, output filtering, and rate limiting — before any response reaches the application layer. Three pluggable LLM providers (Anthropic, OpenAI, and AWS Bedrock) mean you are not locked into a vendor, and you can route traffic based on data residency requirements without rewriting the integration.
End-to-end OpenTelemetry observability — traces into Tempo, logs into Loki, dashboards in Grafana — means every inference request is a structured event with a trace ID. That trace is your audit trail. When a regulator asks what the model was asked, what guardrails fired, and what was returned, you answer with logs rather than reconstruction.
The advisory engagement applies those patterns to your specific system: your data classification, your approval workflows, your existing security tooling. The goal is a deployment your CISO can sign off on without blocking the team that built it.
Published reference implementation
Sample engagement types
Fractional advisory
Monthly retainer
- GenAI deployment review against your compliance framework
- Recurring threat modeling sessions for new features where AI drafts, monitors, or scans
- CISO briefings — written summaries and live Q&A
- Scope and cadence defined at engagement start
Fixed-scope threat model
Time-boxed engagement
- Threat model for a specific GenAI integration — data flows, trust boundaries, attack surface
- Written deliverable suitable for model risk management review
- Presentation to security leadership and CISO
Ship GenAI your CISO will sign off on.
The gap between what engineers want to deploy and what security will approve is a scoping problem, not a technology problem. Let's close it.
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