Integration Surface

Connected Systems

The detection, ticketing, approval, identity, and observability systems this agent is designed to plug into — and the tight boundary it keeps around each one.

A bank already runs a mature operational stack. It has a detection platform, a ticketing system, an approval channel, identity providers, change and observability tooling, and a GRC system of record. The remediation agent is designed to plug into those systems rather than replace any of them.

No new systems of record. The agent is a layer, not a replacement.

Every integration below is either simulated in this prototype or scoped for a near-term phase. Each one is described with its direction of data flow, its operational purpose, and the narrow permission the agent would hold against it in production.

Group 01

Detection & risk signal

Upstream platforms that surface the control gap the agent acts on.

Risk detection platform

Simulated

Brontë

Receives gap exports in structured JSON with control ID, evidence, and severity.

Inbound

SIEM

Simulated

Splunk Enterprise Security

Consumes correlated alerts and detection rules linked to operational controls.

Inbound

SecOps telemetry

Coming soon

Chronicle

Ingests long-retention security telemetry to confirm gap reproducibility over time.

Inbound

GRC risk register

Simulated

ServiceNow GRC Risk

Pulls the canonical control definition, owner, and residual risk rating.

Inbound

Group 02

Ticketing & work management

Where remediation becomes real, tracked, accountable work inside the bank.

Ticketing

Simulated

Jira Cloud

Opens drafted remediation tickets in a scoped project with labels and approver.

Outbound

Change & incident

Simulated

ServiceNow ITSM

Links remediation to the canonical change record and pulls incident status back.

Bi-directional

Engineering tracker

Simulated

Linear

Alternative path for engineering-heavy remediations routed to platform teams.

Outbound

Operational work

Coming soon

Asana

Used by operational-risk teams to track non-engineering remediation actions.

Outbound

Group 03

Approval & comms

Where a named human approver sees, reviews, and explicitly signs off.

Approval channel

Simulated

Slack

Posts a structured approval card to a designated channel and waits for sign-off.

Bi-directional

Approval channel

Simulated

Microsoft Teams

Equivalent approval surface for banks standardised on Microsoft 365.

Bi-directional

Notification

Simulated

Email (Outlook / Gmail)

Fallback approval and notification surface for control owners outside chat tools.

Outbound

Escalation

Coming soon

PagerDuty

Escalates stalled approvals on critical-severity gaps to an on-call risk owner.

Outbound

Group 04

Identity & change

The systems of record for who can do what, and where change actually lands.

Identity provider

Simulated

Okta

Resolves control owners and issues scoped, short-lived tokens for every tool call.

Bi-directional

Identity provider

Simulated

Azure AD / Entra ID

Equivalent identity surface for Microsoft-first institutions and their change paths.

Bi-directional

Cloud access control

Simulated

AWS IAM

Reads policy state on detected access-control gaps; writes remain strictly proposal-only.

Outbound

Source & change

Simulated

GitHub / GitLab

Opens a pull request with the generated change spec; the agent never merges directly.

Outbound

Group 05

Observability & evidence

Where the agent draws telemetry, proves the fix worked, and files the evidence pack.

Observability

Simulated

Datadog

Reads metrics, logs, and traces to validate the remediation behaved as intended.

Inbound

Log platform

Simulated

Splunk

Queries audit log events that prove the control is now operating correctly.

Inbound

Audit log

Simulated

AWS CloudTrail

Sources account-level API evidence for access-control and configuration gaps.

Inbound

GRC evidence store

Simulated

Archer / MetricStream

Appends regulator-ready evidence to the control record, scoped to that control only.

Outbound

Authorisation & safety model

Scoped, short-lived, least-privilege.

The integration model is built around a simple assumption: the agent should be able to do exactly the thing it was asked to do on the specific control it was asked to do it on, and nothing else. That shape is consistent with the expectations placed on regulated workflows under APRA CPS 234 and CPS 230.

Dedicated service account per integration

Every outbound system has its own identity. No shared credentials, no admin keys, no human-user impersonation.

Scoped to specific projects and channels only

Jira access is restricted to the remediation project; Slack to a single approval channel; GRC to one control record.

Short-lived access tokens (1 hour maximum)

Every tool call uses a freshly minted, time-bound token. Long-lived secrets are never handled by the agent runtime.

Human-approved kill switch on every destructive tool

A named control owner can revoke the agent's access to any downstream system from a single control panel, instantly.

Data Flow

From detection to evidence, end-to-end.

A single remediation traces a bounded path through the bank's existing stack. The agent is the connective tissue; every box on either side of it remains the system of record for its own domain.

DetectionBrontë / Splunk / GRCAgentDiagnose, plan, draftApprovalSlack / TeamsChangeJira / GitHub / ITSMEvidenceArcher / MetricStream

Step 01

Detection platform

Brontë, Splunk ES, or GRC surfaces a verified control gap.

Step 02

Risk engineering agent

Diagnoses, plans, drafts — produces artefacts, not actions.

Step 03

Approval channel

Named control owner approves or rejects in Slack or Teams.

Step 04

Change system

Approved remediation is filed to Jira, ServiceNow, or GitHub.

Step 05

GRC evidence store

Evidence pack is appended to the control in Archer or MetricStream.

Outbound Write Surface

Every write action the agent can take.

The write surface is deliberately narrow. Anything outside this list is either read-only or proposal-only, and any destructive call requires explicit human approval first.

  • 01

    Create Jira ticket in the designated remediation project only.

  • 02

    Post approval message to the designated Slack or Teams channel.

  • 03

    Append evidence to the GRC pack, scoped to the affected control.

  • 04

    Open a pull request with the generated change spec — never merge.

  • 05

    Submit the validation test to the sandbox environment only.

Prototype vs Production

What this prototype simulates, and what production would do.

A side-by-side view so the shape of the production system is clear from the demo. The behaviours below remain illustrative — real deployment would require institution-specific policy, security review, and change governance.

Prototype

Creates a synthetic Jira draft in the browser.

Production

Calls the Jira Cloud REST API using an OAuth2 service account.

Prototype

Streams agent events to the local browser only.

Production

Publishes events to an internal Kafka topic for audit replay.

Prototype

Shows the approval card inline in the UI.

Production

Posts a signed approval card to a dedicated Slack or Teams channel.

Prototype

Evidence pack renders as a downloadable document.

Production

Evidence is lodged directly against the control in Archer or MetricStream.

Prototype

Validation tests run as illustrative text.

Production

Validation executes in a sandboxed CI runner with human-reviewed results.

Prototype

Control owner identity is hard-coded in the gap fixture.

Production

Owner is resolved live from Okta or Entra ID against the control record.