Production agents don’t manage themselves.

Why This Matters

The first agent in production is the easy part. Keeping twelve of them compliant for four quarters is the actual job.

Agents must be constantly managed against your current security and compliance controls to prevent drift. Without continuous oversight, a system that meets standards today can quickly become a liability as your internal policies and external regulations evolve.

Most teams lack the resources to monitor these changes in real time. We provide the observability and traceability required to document agent behavior over the long term, ensuring your AI operations maintain the resilience needed to satisfy auditors and protect your data.

88%

of organizations reported confirmed or suspected AI agent security incidents in the last year

Gravitee, State of AI Agent Secuirty 2025 (900+ executives and practioners

By The Numbers

82%

of enterprises discovered previously unknown AI agents in their environment in the past 12 months

Cloud Security Alliance / Token Security, April 2026 (418 IT & security professionals)

88%

of organizations reported confirmed or suspected AI agent security incidents in the last year

Gravitee, State of AI Agent Secuirty 2025 (900+ executives and practioners

Agents are live and need to be managed on an ongoing basis.

Who This Is For

Situation 1

First agent is live, team can't sustain the watch

Your internal team shipped an impressive pilot, but they have now returned to their primary roles. Without 24/7 coverage for the agents they built, your AI operations lack the resilience to handle edge cases or downtime. You need operational continuity without the overhead of hiring a dedicated agent-ops team.

Situation 2

Governance exists on paper, nowhere in execution

You have the AI policy and the acceptable-use documents, but you lack a mechanism to enforce them on every prompt and tool call. Governance on paper is not enough; you need traceability at the runtime level to prove that every interaction follows your defined rules.

Situation 3

Agents from multiple vendors, no unified view

Security, operations, and compliance are all running different agents in silos. Without a unified view of behavior, cost, or risk across these tools, you have no real observability into how AI is actually impacting your environment.

Best Outcome

A managed service that ensures long-term resilience with SLAs you can put in front of a regulator.

Best Outcome

Policy enforcement running at the orchestration layer, providing the clear traceability and audit logs required to satisfy any auditor.

Best Outcome

A single operations plane that provides total observability across all agents, keeping behavior, cost, and control state in one place.

You get a running operations discipline, not a dashboard with a login.

Each item below is an active service, with named engineers and measurable commitments behind it.

What's Included

After this engagement, you will have:

24/7 Agent Monitoring and Observability

Every agent action captured, correlated, and alerted on: prompt, response, tool call, external egress, and cost, across vendors.

After this engagement, you will have:

Runtime policy enforcement and guardrails

Your acceptable-use policy enforced at every agent action, not in a document. Violations blocked, logged, and reported.

After this engagement, you will have:

A human-in-the-loop review queue

A staffed queue for actions your policy requires humans to approve with SLAs, escalations, and a decision log.

After this engagement, you will have:

Drift detection and scheduled retraining

Continuous evaluation against your baseline, so drift is caught before it shows up in an incident or an audit.

After this engagement, you will have:

An audit-ready evidence base

Every decision, approval, and policy action retained and queryable: the package an auditor asks for, pre-built.

After this engagement, you will have:

Quarterly program reporting for your board

Risk posture, cost, outcomes, and near-misses, a quarterly narrative you can hand up without assembling it yourself.

Three phases to bring agents onto the managed service.

How It Works

Phase 1

Onboard

We inventory every agent in scope, map its controls and data boundaries, and wire it into our observability and policy-enforcement plane.

Phase 2

Operate

Named engineers run the service; monitoring, responding to alerts, staffing the HITL queue, and managing drift and retraining on a published cadence.

Phase 3

Report & improve

Quarterly reviews against your risk posture and roadmap with recommendations, retirements, and expansion decisions signed off with your team.

You Walk Away With

• Agent-by-agent onboarding doc

• Telemetry flowing into ops plane

• Policy enforcement active

You Walk Away With

• Named service team

• Published SLAs

• Incident Management + decision log

You Walk Away With

• Quarterly board report

• Control posture trendline

• Roadmap for the next-quarter

Expertise This Work Draws On

The Capabilities Behind A Running Managed Agent Service

Technology & Security Operations

SIEM & Observability

Agent telemetry flows into the same detection-and-response plane that watches the rest of your environment. One plane, one evidence base.

Cybersecurity & Compliance

Incident Response Planning

An agent misfire is an incident. We bring IR playbooks purpose-built for AI failure modes, data leakage, prompt injection, runaway cost.

Cybersecurity & Compliance

Compliance Framework Alignment

AI controls mapped into your existing framework (NIST, HIPAA, HITRUST, SOC 2) so AI evidence rolls into the audits you already run.

Technology & Security Operations

Logging & Audit Trail

Retention, integrity, and queryability engineered to the standard your regulator expects, not a best-effort log file.

Your agent was safe the day it shipped. Can you prove it's still safe today?

Thirty minutes with a senior partner. Bring the agents you have; we'll map what it takes to run them without drift, surprise, or audit finding.