The one thing every "AI for ERP" pitch skips: how the agent actually writes
Every AI-agent vendor can show you a read. Almost none can show you a write that a security review would actually pass — policy enforcement, approval gates, and a rollback path, not a direct database write with a prayer.
Who this is for
IT and security leaders who've been pitched AI-for-ERP demos that all quietly stop at read-only — and want to know how a write actually gets approved, logged, and rolled back.
What you get
A working, governed write path from your AI agent into your ERP — executing through the application's own logic layer, with a policy-enforcement gate, a full evidence trail, and a defined rejection/rollback flow.
Why this is real, not a pitch deck
A named engagement, not a hand-wave
The Agent-Ready ERP Diagnostic & Governed Write-Path is scoped specifically around one stalled write path in your environment — chosen because it's the constraint actually blocking you.
Try the actual write-path pattern, live
The Governed AP Exception Workflow demo runs the full loop — propose, policy decision, approval or block, simulated write, audit, and rollback — the same pattern this engagement builds around your write path.
A real write into a live system of record, not a mock
On 2026-07-31 this pattern executed against a real, paid Snowflake sandbox tenant — not a free trial, not a mock: 3 real writes to an open PO's committed amount persisted and were confirmed by re-reading state afterward, plus 2 correctly rejected writes (a vendor on hold, a closed PO), with the full gateway-to-Snowflake round trip logged with real policy-check and audit-trail data. Ask and I'll walk you through it directly.
Operator experience on both sides
Before founding Tioga AI, the founder managed ERP systems across four sister companies — including the approval and control workflows a governed write has to respect.
Audit-grade evidence, not a screenshot
Every write produces a reviewable record — what was proposed, what policy check ran, who or what approved it, and what happened if it was rejected.
Doesn't ServiceNow's Action Fabric (or SAP's Agent Hub, or Salesforce's MCP servers) already do this?
Partly, and it's worth being precise about which part. ServiceNow's Action Fabric — a GA MCP server bundled into every Now Assist / AI Native SKU — already lets an agent write through ServiceNow's own flows, playbooks, and approvals. SAP ships an equivalent through Agent Hub and Joule Agent Studio's MCP gateway. Salesforce ships hosted MCP servers, GA and free on Enterprise Edition and above, with full user attribution. Inside each vendor's own estate, a governed write already exists.
The write path most buyers actually need crosses that boundary. An agent that qualifies a lead in Salesforce, resolves an AP exception flagged in ServiceNow, or reconciles a PO in SAP frequently needs to write into a different system of record than the one that triggered it — an ERP the triggering platform doesn't own. Action Fabric's approval trail stops at ServiceNow's edge; it doesn't extend into SAP's application logic, and none of these platforms' write paths were built to police a competitor's ledger. That's not a defect — it's the natural limit of a platform vendor governing its own product.
It's also not something a platform vendor can neutrally build past: verifying that a write into a competing ERP was authorized and consistent with that ERP's own controls isn't a capability a platform vendor has an incentive to build well, since it isn't governing its own transaction anymore. This engagement builds the specific write path through the target ERP's own application logic layer — not a database write — with a policy-enforcement gate and an audit-grade evidence trail, regardless of what triggered the write. It's designed to work alongside Action Fabric, Agent Hub, or Salesforce's MCP servers as the trigger or orchestration layer, not to replace them — the gap it closes is the write itself, into the system that actually owns the record.
Engagements
Every engagement starts with a 5-day Discovery Sprint ($5,000 flat, prototype included) that scopes the work before any larger commitment — credited toward the price below if you move forward.
Not ready to scope an engagement? Free ERP Agent-Readiness Checklist →Agent-Ready ERP Diagnostic & Governed Write-Path
Assess one stalled agent-to-ERP write path, then build a governed version of it — executing through your application's own logic layer, with policy enforcement and an audit-grade evidence trail your control owners can actually clear.
$60–120K
~6 weeks
Questions
What does "governed write" mean technically?+
The agent never writes directly to the database. It executes through your application's own API/logic layer — the same path a human user's action would take — with a policy-enforcement check and logging before and after.
What if the agent gets it wrong?+
The write path is designed with an explicit rejection and rollback flow from day one, not added after an incident.
How is this different from just giving an agent API credentials?+
API credentials alone don't give you policy enforcement, an approval gate, or an audit trail scoped to what a control owner needs to see. This engagement builds all three around the write, not just the API call.
Can we see the audit trail this produces?+
Yes — see the live Governed AP Exception Workflow demo for the interactive version. This pattern has also run against a real Snowflake sandbox tenant, not just the mock (3 real writes persisted, 2 correctly rejected, full policy-check and audit-trail data on 2026-07-31) — ask and I'll walk you through the real run directly.
Does the diagnostic cover payroll/HRIS or FP&A write paths too, or only the ERP?+
Yes, where a candidate write path originates in or lands in payroll/workforce management or FP&A planning rather than the ERP alone — grounded in hands-on configuration, implementation, and operating experience with UKG Pro and Workday Adaptive Planning (formerly Adaptive Insights, spanning both its pre- and post-Workday-acquisition generations), not a general "AI in HR" or "AI in FP&A" framework applied from the outside. Two examples: a timecard exception agent proposing punch corrections carries the same attribution-loss risk this diagnostic already looks for on the ERP side — now against real wage-and-hour exposure (FLSA/state overtime rules) rather than only a posting-period control; a headcount-forecast drafting agent has to write into a draft, never a locked/approved, version, with each number tagged to its source data and stated assumption. Any demo shown ahead of a live engagement runs on synthetic data — UKG doesn't issue developer sandboxes outside its formal partner program, and Adaptive Planning sandboxes come bundled with a customer license — stated plainly, not implied away.