Connect Governed AI Workflows to Your Systems
We connect governed AI workflows to the systems they must read, update and escalate through, without forcing a rip and replace of your existing stack. This is the layer where an AI demo becomes an operation, and where most AI projects quietly stop.
- The wiring that makes governed AI roles operationally useful: identity, permissions, data contracts, APIs and webhooks, exception routing, audit trails and the runbook your team operates from.
- Built across the systems you already run. No rip and replace, and no requirement that a system be modern before it can participate.
- Seven deliverables: system inventory, data contracts, permission map, failure-mode register, integration test results, runbook and ownership matrix.
- Browser automation is a last resort here, not a feature. Where we have to use it, we label the operational risk and plan to remove it.
- Post-launch support boundaries are written down: what we hold, what you hold, and what happens when a vendor changes an API without notice.
The Four-Layer Model
The same four layers used across the AI-Native Operations pages. This service builds the third one, and the third one is where AI pilots most often stop: the model worked, the integration did not, the runbook never got written, and nobody owned the operation.
Humans
Layer 1Judgment, exceptions, relationships, escalations
A named owner for every governed AI role, and the approval authority for anything the role is not permitted to decide alone.
Governed AI roles
Layer 2Repeatable workflows with a defined start, end and success test
Bounded scope, durable context, logged inputs and outputs, a cost ceiling and a rollback path. Branded internally as Virtual Employees.
Automation layer
Layer 3Identity, permissions, data contracts, retries, exception routing
Where a workflow becomes an operation. Least-privilege service identities, idempotent writes, and a defined path for every failure mode.
Systems of record
Layer 4ERP, EHR, CRM, billing, ticketing, payroll, data warehouse
Your systems, your tenancy. The operating layer reads and writes through them rather than replacing them.
System, Action, Permission, Failure, Owner
The inventory is the first deliverable and the substrate for everything after it. One row per action, not one row per system, because the permission and the failure mode differ per action. Illustrative rows below.
| System | Action | Permission scope | Failure mode | Owner |
|---|---|---|---|---|
| ERP | Read open purchase orders | Read-only, PO objects, single company code | Rate limit exceeded. Backs off and retries, then queues | Client IT |
| ERP | Post an invoice match result | Write, invoice-match field only, idempotency key required | Duplicate post prevented by operation key. A conflict routes to exception | Client controller |
| Payer portal | Check coverage eligibility | Service account, eligibility screen only, no claims submission | Portal layout change breaks extraction. Role stops, alerts, falls back | Reliable Group |
| EHR | Read encounter documentation | Read-only, scoped to the encounter types in the workflow | Record locked by another user. Queued and retried on a schedule | Client IT |
| Ticketing | Create an exception ticket | Write, one queue, no ability to close or reassign | Queue unavailable. Held locally and replayed, with an alert at 15 minutes | Client function owner |
| Identity provider | Hold the role’s service identity | Own credential per role, revocable independently, quarterly review | Revocation stops the role immediately and the workflow falls back | Client security |
Every action in the real inventory carries a data contract too: the exact fields read or written, their types, and what the role does when a field it expects is absent. That is the document that stops an integration breaking silently six months later.
Identity, Least Privilege and the Boring Parts That Matter
None of this is novel, which is exactly the point. An AI integration should be no less disciplined than any other production integration, and the pressure to skip these steps in a pilot is how pilots become incidents.
Identity
Each governed AI role holds its own service identity, issued by your IT team and revocable on its own. Never a human user’s credentials, never a shared account across roles. Shared identity destroys attribution in the audit trail, which is the thing an auditor will ask for first.
Least privilege
Permissions scoped per action, not per system: read-only where the role only reads, and write access narrowed to the specific fields or object types the workflow touches. Reviewed quarterly with your team, and reduced when a workflow changes rather than left broad.
Secrets handling
Credentials live in your secret manager and are read at runtime. Nothing in source control, nothing in configuration files, nothing in a prompt. Rotation is your process; we integrate with it rather than asking for an exception to it.
Environment separation
Development, staging and production are separate, with no path from a development environment to a production credential. Test data is synthetic or masked. This is the control most often skipped under pilot pressure and the one that produces the worst incidents.
Observability
Every call logged with system, action, payload reference, outcome, latency and cost, written to your logging infrastructure so your team can query it without us. Alerts on error rate, latency, queue depth and cost, routed to your named owner as well as to us.
Idempotency and rollback
Every write carries an operation key so a retry cannot post twice, which is the failure that costs the most to unwind. Every integration has a tested rollback: disable the role, revert to the previous process, and a named person who can do it without our involvement.
Browser Automation Is a Last Resort
Some systems have no API worth using, and some vendors will not grant access to the one they have. In those cases a role can be made to drive the user interface directly. It works, and we have built it. It is also the least durable thing we build, and we would rather say so here than discover the disagreement later.
The operational risk: a layout change by the vendor breaks it without warning, and often silently. It usually requires a credential with broader rights than the workflow needs, because the UI was designed for a person. It is slower and more expensive per action. It can breach the vendor’s terms of use, which is your legal exposure and not a technical question. And it is difficult to test properly, because the environment moves underneath the test.
So we treat it as temporary. Where we use it, we say so in the inventory, we label the specific risk on that row, we monitor it more aggressively than an API integration, and we record what would have to change for it to be replaced. A permanent browser automation is an unowned liability sitting in the middle of your operation.
Every Failure Class Has a Defined Route
The failure-mode register is a deliverable, not a design note. An integration without one fails silently, and silent failure in a regulated workflow is worse than an outage because nobody knows to look.
| Failure class | How it is detected | Automatic response | Escalation |
|---|---|---|---|
| Transient error or rate limit | HTTP status or error payload from the system | Exponential backoff and retry to the agreed limit, all attempts logged | Exception queue after the retry limit, with the attempt history attached |
| Record locked or in use | Lock response from the system of record | Requeue on a schedule rather than spin, so the role does not hold the lock open | Named owner if the record is still locked past the agreed age |
| Data contract violation | Expected field absent, or a type or enum outside the contract | Stop processing that item. No guessing at a missing field | Exception queue immediately, with the offending payload reference |
| Low confidence | Model confidence below the workflow floor set at acceptance | Route to human review rather than release | Standard review queue, at the priority the workflow defines |
| Policy check failure | A written rule in the specification returns fail | Block the output. A policy failure is never overridden automatically | Named owner, and recorded as a policy event rather than a technical one |
| Cost ceiling reached | Month-to-date spend against the agreed ceiling | Hard stop, and the workflow reverts to the fallback process | Client owner and Reliable Group together, before any ceiling is raised |
| Upstream schema or UI change | Contract test failure, or extraction failure on a browser-automated step | Disable the affected action rather than continue on bad data | Reliable Group on call, with client notification inside the agreed window |
What Gets Tested Before Cutover
Contract tests per integration
One test per data contract, asserting the fields, types and enums the role depends on. These run on a schedule after launch too, so a vendor changing a field is detected by a failing test rather than by a wrong result reaching your close.
Failure injection
Each row of the failure-mode register is exercised deliberately: forced timeouts, forced rate limits, locked records, malformed payloads, revoked credentials. A route that has never been triggered is a route nobody can rely on.
Idempotency and replay
Every write path is replayed to prove that a retried step cannot post twice, including the awkward case where the first attempt succeeded but the response was lost. This is the test that saves the most cleanup.
Load and surge
Run at expected volume and at the agreed surge multiple, watching latency, queue depth and rate-limit headroom. Where a system of record is the constraint rather than the role, we document the ceiling instead of designing around it silently.
End-to-end with the role
The integration is tested with the actual governed AI role rather than a stub, on synthetic and historical data, so the acceptance evidence covers the whole path from trigger to system of record to audit log.
Test results as a deliverable
The results are handed over as evidence, not summarised in a status update. Your security and compliance teams get the artefact rather than an assurance that testing happened.
Who Owns What, After Cutover
The support boundary is written into the runbook before launch. Vague support expectations are how a working integration becomes an argument in month four.
The runbook itself
What your team approves, what they monitor, what they escalate and what they own. Severity definitions, contacts by hour, the fallback procedure per workflow and the ownership matrix. Written for the person on shift, not for the person who commissioned the project.
What Reliable Group holds
The integration code and its releases, the contract tests, monitoring and alerting on the integration layer, and on-call response within the agreed severity windows for the support period. Fixes for anything we built that breaks on its own.
What you hold
The service identities and their permissions, the decision to run or stop a workflow, the exception queues and the judgment inside them, your systems of record and their change calendar, and the named owner per workflow.
Vendor and third-party changes
When a system you depend on changes an API or a screen, the contract tests catch it and we fix the integration within the agreed window. Where a vendor removes a capability entirely, it is a change request rather than a defect, because no amount of integration work restores a withdrawn endpoint.
What is out of scope
We do not administer your systems of record, license or procure tooling on your behalf, take responsibility for data quality upstream of the integration, or provide legal advice on vendor terms. Each of those has an owner, and it is clearer to name them here.
Exit
The integration, the contracts, the tests and the runbook are yours. If you take the operation in-house or move it to another partner, there is a documented handover rather than a dependency, which is the whole point of building it this way.
The Systems We Usually Integrate
Grouped here rather than in the opening, per v1.0. The pattern is the same in each; what changes is the change-management posture of the systems and how much of the workflow is regulated.
Healthcare
EHR platforms, practice management, billing and clearinghouse systems, prior-authorisation portals, payer eligibility and claim-status systems, document management. The constraint is usually portal access rather than the EHR.
Insurance
Policy administration, claims platforms, case management, rating engines, document and correspondence systems, and the reinsurance reporting path. Long-lived platforms with conservative change windows, which shapes the sequencing.
Banking and financial services
Core banking, loan origination and servicing, trading and order-management systems, AML and sanctions screening, risk monitoring, and the general ledger. Segregation-of-duties requirements shape the permission map more than anything technical.
Pharma and life sciences
Safety databases, clinical trial management, regulatory information management, quality management and document control. Validation and change control set the timeline, not the integration difficulty.
Cross-industry back office
ERP and the general ledger, CRM, procurement, HRIS and payroll, expense management, ticketing and service management, identity provider, data warehouse and the audit log estate.
IT and software operations
Source control and CI, issue trackers, observability and incident platforms, customer support desks, and the internal service catalogue. Usually the best API surface of any of these, and therefore the fastest integration work.
Automation Layer Implementation: Seven Artifacts You Keep
The v1.0 standard deliverable list. The three that were missing from this page before are the ones that make the difference in year two: the data contracts, the permission map and the failure-mode register.
System inventory
Every system in scope with its authentication model, API surface, rate limits and change-management posture, and one row per action rather than per system.
Data contracts
The exact fields read and written per action, with types, enums and the defined behaviour when an expected field is absent. The document that stops silent breakage later.
Permission map
Which identity holds which permission on which object, at what scope, reviewed on what cycle. The artefact your security team will actually ask for.
Failure-mode register
Every failure class with its detection method, automatic response and escalation route, matching the section above and kept current as workflows change.
Integration test results
Contract tests, failure-injection results, idempotency and replay evidence, load results at expected and surge volume. Handed over as evidence rather than summarised.
Runbook and ownership matrix
The operating runbook your team runs from, plus the matrix naming who owns each control, each workflow and each escalation path, on both sides.
Where AI Integration Work Actually Fails
Most AI work that stalls does not stall on the model. A triage role produces a good recommendation that nobody can post back into the system holding the customer record. A pricing-exception role finds a genuine outlier that nobody can flag inside the ERP. A pipeline-hygiene role identifies a stale opportunity that nobody can update in the CRM. The output is correct and useless.
Every operator we have spoken to who shelved an AI pilot describes the same failure: the model worked, the integration did not, the runbook never got written, and the human team never owned the operation. Three of those four are this service.
We build this layer as a first-class engagement because we had to build it for our own workflows first, and because it is the part nobody demos. We publish reviewable security architecture and data-handling documentation rather than certification badges. The architecture and data-handling documentation are in the Trust Center for your security team to review.
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Start with the Blueprint.
Three to five weeks. Paid engagement. Both levers scoped together.