Compliance-grade autonomous operations for the systems your bank cannot afford to take down. On-premises and air-gapped, audit-recorded by default, policy-bound at every action.
Why banking operations are different
Banking is operations at scale plus operations under regulation. The infrastructure is heterogeneous (core banking, payment processors, identity, ITSM, monitoring, security), the change windows are tight, the audit requirements are uncompromising, and the cost of a missed transaction is measured in seven figures. General-purpose AIOps was not designed for that combination of constraints. It was designed for SaaS observability, where the audit surface is simpler and the blast radius of an automated restart is bounded.
The three constraints that change everything in banking are regulator-grade auditability, payment-system blast radius, and restricted-network deployment. Each rules out the AIOps platforms that grew up in observability cloud.
Five operational pain points banking faces today
Payment gateway monitoring and recovery
A degraded payment processor takes seconds to start losing transactions. By the time a human pages, the regulator-reportable threshold may already have been crossed. Auto-recovery has to be safe enough to trust at 2am.
Fraud signal correlation across detection systems
Most banks run multiple fraud detection systems that emit overlapping alerts. Correlating them into a single decision (act, escalate, investigate) is manual work today. Autonomous correlation with audit reduces alert fatigue without hiding signal.
Regulatory reporting workflow automation
Reporting workflows touch a dozen systems and depend on data quality across all of them. Sentinel detects upstream data issues and routes them for correction before they reach the regulator-facing report.
Change-window enforcement
Bank change calendars are strict. Sentinel reads ServiceNow change records and refuses to execute high-impact MOPs during freeze windows, while still allowing read-only diagnostic actions. No human has to remember to disable the automation.
Identity governance and separation of duties
Joiner, mover, leaver workflows in banks have additional segregation-of-duties checks. Autonomous identity workflows must respect those rules. Sentinel handles them as policy-encoded MOPs, with the audit trail required to defend each action.
Cross-system incident triage
When something breaks at a bank, the signal usually surfaces in one system but the cause lives in another. Sentinel correlates signals across monitoring, ITSM, and business systems into one incident view, with the actual cause surfaced rather than the symptom.
What autonomous AIOps changes for banking ops
The replacement is not "human" with "machine." It is "human as runtime executor" with "human as supervisor and approver." Sentinel runs the OIAO loop continuously (Observe, Investigate, Act, Optimize) and executes through ProcBot under policy your team controls. Engineers stop chasing alerts across systems and start reviewing the approval queue and the audit log. The recovery procedures that used to wake people up at 3am run themselves under guardrails the bank wrote.
The platform is aligned to the standards regulated banking infrastructure requires.
Audit trail. Every action is recorded as a structured Action Ticket: triggering signal, MOP that ran, input state, output state, validation result, human approver where policy required one, rollback if validation failed. Immutable and exportable via API.
Encryption. TLS 1.3 in transit, AES-256 at rest, dedicated secret store with least-privilege scoping per integration credential.
Data residency. US, EU, APAC regional deployments plus private cloud, on-premises, and air-gapped options. For air-gapped, the model itself runs inside the bank perimeter.
Certifications. SOC 2 / ISO 27001 compliance ready, current security and privacy framework alignment, BAA available for healthcare-banking overlap (insurance, claims), and detailed security architecture documents shared with prospective enterprise customers under NDA.
No customer data used to train shared models. Sensitive fields can be excluded or redacted before logs are sent to the model. For air-gapped, nothing leaves the perimeter at all.
Integration with banking systems
The connector library covers both sides of bank operations: infrastructure and business systems. Most AIOps platforms have thin coverage on the business side, which forces banks to keep the cross-system orchestration manual.
Core banking: read-side connectors for major core banking systems, with controlled write paths through Action Tickets carrying validated MOPs.
Payment processors: health and transaction-flow signals, with policy-bound recovery actions on degraded paths.
Fraud and AML platforms: signal ingestion and correlation across detection systems.
Monitoring and observability: Datadog, Dynatrace, Splunk, Prometheus, New Relic and the rest. We federate with whatever the bank already runs.
ITSM: ServiceNow, Jira Service Management, BMC Helix. Bidirectional integration for ticket creation, update, change-record logging, and approval workflows.
Identity: Active Directory, Entra ID, Okta. SoD-aware workflows for joiner-mover-leaver and access governance.
Notification: Slack, Microsoft Teams, email, status pages. Configurable per-incident routing including dedicated war room channels with Sentinel as participant.
No bank takes a new platform straight to production autonomous on day one, and no serious vendor should ask. The realistic path is three phases.
Shadow mode (typically 4 to 8 weeks). Sentinel connects to your signal sources and runs the full intelligence loop, but does not execute any change. It observes, investigates, and recommends. Your team validates each recommendation against what they would have done. The platform learns your environment; your team builds confidence in its judgment.
Graduated autonomy (typically 6 to 12 weeks). You authorize specific MOPs on specific systems in specific environments. Low-risk procedures graduate first (read-only diagnostics, well-understood non-prod recovery). Higher-impact procedures graduate only after the platform has demonstrated reliability. Every change still routes to a human for approval where your policy requires.
Production autonomous (ongoing). Known-pattern incidents resolve under policy. Engineers handle the approval queue and the genuinely novel cases. Most bank deployments continue to require human approval on high-impact writes to core banking and payment systems indefinitely. That is by design.
For the platform-wide adoption pattern in detail, see the comparison page.
Frequently asked questions from banking buyers
Sentinel reads change-freeze calendars from ServiceNow or Jira. During freezes, configurable behavior includes pausing all automated actions, requiring additional approvals, or restricting execution to read-only diagnostic MOPs. The freeze respect is automatic; no operator has to remember to disable automation.
Stronger. A Sentinel action is recorded as an Action Ticket with structured inputs, outputs, validation result, and rollback. A human action depends on the human remembering to log each step in the target system. Sentinel does not forget. Regulators get a cleaner record from an autonomous-executed change than from a manually-executed one, in our experience helping banks prepare for examinations.
Yes. Air-gapped deployment includes the model itself. Telemetry, inference, and training-relevant data all stay inside the bank perimeter. Offline model updates are delivered as verified artifact packages. This is the model required by banks operating under sovereign or defense-grade restrictions.
Read paths are direct integrations. Write paths go through Action Tickets carrying validated MOPs, with pre-checks against the target system state, the change itself, and validation that the change took effect as expected, plus automatic rollback if validation fails. The bank controls which MOPs are authorized to write, in which environments, under which conditions.
Discovery and scoping take 2 to 4 weeks (joint sessions to map highest-value use cases, target integrations, approval boundaries). Implementation kickoff to first signals is 1 to 2 weeks after access is granted (pace is driven by your security, IAM, and change-management cycles). Shadow mode to graduated autonomy is 6 to 12 weeks. Realistic total from contract signature to production-grade autonomous operation is 9 to 18 weeks.
The fastest way to evaluate fit is a working session against your actual use cases. Bring the systems and the pain. We will show you how Sentinel changes the loop.
