The control tower for
supply chain operations.
Role-aware portals on top. Three pillars in the middle. A connected fabric of systems-of-record underneath. OpsATC.AI is the operational layer that product companies (OEMs), hub providers, contract manufacturers, distributors, and the logistics carriers that move their product have been missing.
The product is small in concept and big in surface area.
Three pillars define the product. Five portals deliver it. One agent, The Captain, oversees and orchestrates your operations. Operator commits in their own UI.
The operational mechanism behind Improve.
Every operation's data is dirty when we start. The Captain doesn't pretend otherwise. The Data Quality Detection Layer spans the six issue classes that erode operator trust (staleness, missing identifiers, duplicate keys, source-of-truth contradiction, schema drift, and reference-data gaps) through four layered detection modes: baseline scan at MCP connect, inline checks on every read, scheduled background sweeps per record type, and operator-triggered deep dives. On-demand checks run in the demo today; the continuous modes are on the roadmap. Findings surface through the Trusted Advisor card; the operator owns the response.
A field tech shouldn't see customer financials.
A CFO shouldn't see warehouse pick queues.
Each portal is purpose-built for a specific role with its own sidebar, The Captain prompts, and data lens with role-based access from day one. Per-tenant co-branding places each customer's own workspace mark beside the OpsATC.AI logo. The surface white-labels to the tenant.
For the people who run the operation.
Multiple personas, role-specific sidebars, one shared digital thread. Operations Directors see strategic dashboards. Supply Chain Analysts see tactical buffer health. Process Improvement Leads see the Process Intelligence Engine driving continuous improvement.
| Order | Status | ETA |
|---|---|---|
| SO-88142 | In transit | May 6 |
| SO-88137 | Delivered | May 2 |
| SO-88129 | Exception | May 9 (revised) |
| SO-88121 | On hold | Pending credit |
| SO-88105 | In transit | May 7 |
For your customers, branded as theirs.
Self-service order status, OTIF visibility, exception transparency, document retrieval. Replaces the "where's my PO" inbound, and replaces it with a customer experience that drives renewals.
Transparent scheduling for a collaborative and expedited onboarding experience.
New-customer onboarding is where most distributors lose 60-90 days of margin. OpsATC.AI walks both sides through guided EDI mapping, master-data validation, item setup, and pricing rules, with The Captain as the co-pilot.
Field service that arrives already briefed.
RMA, warranty, technical support, depot repair. Tickets land with full context. The Captain reads the customer's last 90 days of shipments, the open exceptions, and the relevant engineering notes from the PLM on demand the moment the ticket arrives. No data lake, no historical extract, just a read against the source systems via MCP.
Air Traffic Control within the control tower.
EDI transaction monitor, integration health, user permissions, audit trail, MCP connector configuration. The portal that makes every other portal trustworthy.
Five layers of intelligence. One product.
OpsATC.AI is built top-to-bottom as an AI-native platform, not retrofitted onto a legacy SaaS spine. Every layer observable, every connector MCP-native, every read logged.
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Read
01 Read
Reads from your systems via MCP: ERP, WMS, CRM, MES, PLM, planning suites, EDI.
No writes, ever. -
Reason
02 Reason
Builds a coherent picture of the operation across systems that don't natively talk to each other.
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Analyze
03 Analyze
Compares what's happening to what should be happening. Surfaces variance, slippage, and risk before they escalate.
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Sync
04 Sync
Aligns the team. Every operator on a build, an account, or an exception sees the same truth at the same moment.
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Recommend
05 Recommend
Surfaces the best next move with sources cited. The team decides. The team acts. The Captain doesn't act for you. Recommend-then-commit is the direction operations AI is heading, not a stage to grow out of.
Orchestration finds the work. Process intelligence finds the fix.
Every other category in the comparison table stops at orchestration. The Process Intelligence Engine is the layer above: it identifies bottlenecks, quantifies their dollar impact with cited, auditable math (labeled modeled until proven against live reads), and tracks the fix closed-loop. The difference is reactive vs. compounding.
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CaptureEvery event, every system.
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IdentifyPatterns find the bottleneck.
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QuantifyAuditable dollar math.
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TrackInterventions ranked by ROI.
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VerifyPredicted vs. actual. Loop reopens.
Auditable math, not gut estimates
Every quantified bottleneck shows the source data, the assumption set, and the calculation. CFOs can dispute a number. They cannot dispute the math because they can see it. And a figure The Captain models is labelled modeled, never measured, until an outcome is recorded against it. Why AI cost and AI value are one problem →
No black box
Every recommendation cites the underlying pattern and the systems of record it was derived from. Process improvements identified in your tenant belong contractually and operationally to you.
Every system you've already paid for, working as one.
All 141 of our Tier-1 connectors are built to a five-criteria rubric against each vendor's documented API contract, within a 695-surface catalog. Each has a typed client, a health-check ping(), replay fixtures, and normalizes to canonical domain types, including SAP S/4HANA, SAP ECC, Oracle Fusion ERP, Manhattan Active WMS, and Microsoft Dynamics 365 Business Central. Live Captain reads are proven end-to-end today against four systems: SAP S/4HANA (a vendor sandbox), New Relic, Confluence, and PagerDuty. The remaining Tier-1 connectors are contract-tested against synthetic replay fixtures, with per-customer live reads brought online as each design-partner pilot requires. The remaining ~550 catalog surfaces harden just-in-time on the same codegen framework as design-partner needs emerge. Plus an MCP SDK for the systems that are uniquely yours.
Several Tier-1 connectors target vendors that publish free developer sandboxes, including SAP S/4HANA's public sandbox, which OpsATC.AI is proven against today, and Microsoft Dynamics 365 Business Central via the M365 Developer Program. A technical evaluator can wire OpsATC.AI against a public test endpoint before requesting a paid pilot. Email [email protected].
ERP & FinancialsEnterprise resource planning
Planning & S&OPDemand, supply, IBP
Warehouse ManagementWMS & inventory orchestration
Manufacturing ExecutionMES & shop-floor systems
PLM & EngineeringProduct lifecycle management
Logistics & TMSTransportation, visibility, freight
CRM & Field ServiceCustomer + service operations
ProcurementSpend, sourcing, supplier mgmt
ITSMIT service management
Project & Work ManagementTasks, plans, cross-team coordination
Data & AnalyticsWarehouses, lakes, BI
HRPeople & workforce data
EPMEnterprise performance management
QMSQuality management systems
EDI & B2B NetworksTrading partner integration
Generic AdaptersFor the systems uniquely yours, your custom escape hatch
MCP-native. No data lake required.
Most integration platforms replicate your operational data into a warehouse before they can act on it. OpsATC.AI is built to read your live systems read-only, on demand. No ETL pipeline, no historical extraction, no data-team involvement to start.
What we need
- ✓At least two connected systems of record to reason across: an ERP, WMS, CRM, MES, PLM or planning suite. If your operation runs entirely on spreadsheets and accounting software with no system of record, there isn't enough connected data for The Captain to orchestrate yet, and we will tell you that rather than sell you a pilot.
- ✓ Read-only credentials per system you want orchestrated
- ✓ Service accounts on those systems
- ✓Allow-list approval for OpsATC.AI's egress addresses
- ✓ One-time field-mapping confirmation per connector
- ✓ Sandbox access during Day-1 validation
What we don't need
- ✗ Historical data extraction from your data lake
- ✗ Data warehouse seeding
- ✗ Replicated copies of your operational data
- ✗ Custom adapter work for standard platforms
- ✗ Data-team involvement to begin
Designed for the day your vendor makes a change unannounced.
SAP renames a field. Salesforce deprecates an endpoint. A vendor flips Basic auth to OAuth. APIs change, sometimes quarterly, and most integration platforms break loudly when they do. OpsATC.AI is built so that change happens at the adapter layer, never in your workflow.
- 01Canonical domain types. Your queries reference typed entities (SalesOrder, Part, WorkOrder, Shipment), so vendor field renames stop at the mapper file, not your prompts.
- 02Per-vendor isolation. A SAP change cannot affect a Salesforce path. Adapters fail independently and recover independently.
- 03Spec-driven adapter generation. When a vendor publishes an updated OpenAPI / WSDL / OData spec, adapters regenerate from the spec rather than being hand-patched. Phase 1 architecture; expanded coverage in Phase 2.
- 04Contract testing. Every adapter is designed to ship with replay-mode tests against recorded vendor responses, so drift surfaces in CI before production data flows. Contract-test infrastructure deploys with the first design-partner pilot.
- 05Structured error mapping. Vendor error codes are normalized into a typed error layer customer-facing code can branch on cleanly. No surprise downstream exceptions when a vendor adds a code.
- 06Merge gates. Every adapter (first-party or partner-built) must pass a fixed conformance check before merging. The bar is the same across the catalog.
Digging a bit deeper
Roadmap (Phase 2, planned, not yet available). Read adapters for Snowflake, Databricks, Google BigQuery, and Microsoft Fabric would query in place against your existing schemas, with you controlling which tables OpsATC.AI can see. The design goal is that your data is not copied out of your warehouse: OpsATC.AI would act as a federation layer, not a storage layer. This is opt-in, never a prerequisite to start.
Built for the operator who can't afford a leak, or a hallucination.
Every connector designed to be audited. Every recommendation cited by design. Every tenant isolated at every layer. Humans always decide. Pilot-scope vs production-hardening status, architectural commitments, contractual protections, and the page to send your security team live on the Trust Center.
We sit on top of your investments.We don't replace them.
Your ERP stays. Your S&OP suite stays. Your customer portal stays. Your factory MES stays. If you've spent eight figures on any of those, OpsATC.AI is the layer above, never a rip-and-replace. Wherever your data and AI platform already runs, cloud or on-prem, The Captain reads it in place through MCP: we complement the substrate, we don't rebuild it. This is built for the hard part everyone is stuck on: moving AI from a pilot into continuous, governed production.
ETL, historical extraction, model training, validation, schema reconciliation, before the first useful answer.
Read-only credentials. MCP queries live systems on demand. The Captain can answer questions about your operational state immediately.
How: pre-trained operational reasoning + MCP queries in place of replication + feedback-driven adaptation instead of retraining cycles. See the Day 1 to first-outcome detail →
The Captain
Existing portals
If you already operate a customer-facing portal (your branded e-commerce front, an internal customer-success platform, a partner network), The Captain and the orchestration layer work behind it via MCP. We don't ask you to retire your front door.
Established AI investments
SAP Joule, Oracle AI, Kinaxis Maestro's planning intelligence, Microsoft Copilot. They continue to do what they're good at. OpsATC.AI orchestrates across them and fills the agentic gap they don't.
Smart-factory programs
If you've invested in Industry 4.0, Siemens digital-thread, or a homegrown MES, OpsATC.AI consumes the data they emit and orchestrates exception response. Your factory program is the floor. We're the layer that hears it.
How we compare to Blue Yonder, Kinaxis, SAP, and the category alternatives.
Across 14 capabilities (AI-native architecture, cross-system reads, role-aware portals, source citations, read-only doctrine, and nine more), see where OpsATC.AI sits against the six categories operators evaluate alongside us: ERP-with-AI (SAP Joule, Oracle AI, Microsoft Copilot), supply chain platforms (Kinaxis, o9, Blue Yonder, e2open), logistics control towers (FourKites, Roambee), AI ops platforms (Aera, C3.ai, Palantir Foundry), process intelligence & RPA (Celonis, UiPath), and generic AI assistants (ChatGPT Enterprise, Claude, Copilot). We didn't grade ourselves green on every row. The pattern that emerges: every other category does part of the job. None does the whole job.
| Capability | OpsATC.AI | ERP + AI SAP Joule, Oracle AI, MS Copilot |
Supply Chain Platform Kinaxis, o9, Blue Yonder, e2open |
Logistics Control Tower FourKites, Roambee |
AI Ops Platform Aera, C3.ai, Palantir Foundry |
Process Intelligence & RPA Celonis, UiPath |
Generic AI Assistant ChatGPT Ent., Claude, Copilot |
|---|---|---|---|---|---|---|---|
| AI-native architecture (built for agents, not retrofit) | ● Built for agents | ◐ Agents retrofit on a transactional core | ◐ Native agentic agents (Kinaxis Maestro, Blue Yonder) | ◐ ML overlays on freight data | ● AI-native (broad) | ◐ Agentic layer on a mining/RPA core | ● AI-native (general) |
| Cross-system read and analysis at the protocol layer | ● MCP, every system | ◐ Within ERP suite only | ◐ Read-heavy; some write | ○ Read-only telemetry | ◐ Custom connectors | ◐ Broad, via ingestion + proprietary connectors | ○ Chat only |
| MCP-native connector fabric | ● Day-one | ◐ Emerging via MCP gateways (SAP, MS) | ○ Proprietary | ○ Proprietary | ○ Custom only | ○ Proprietary connectors | ◐ Native in Claude; partial elsewhere |
| Role-aware portals (5 distinct) | ● Internal · Customer · Onboarding · Service · Admin | ◐ Internal only | ◐ Planner-only | ◐ Logistics-only | ○ Generic dashboards | ○ Analyst / developer surfaces | ○ Single chat surface |
| Customer-tenant isolation (CM serving competitors) | ● Architectural | ● Per-instance | ◐ Multi-tenant SaaS | ◐ Multi-tenant SaaS | ◐ Multi-tenant SaaS | ◐ Multi-tenant SaaS | ○ Not designed for it |
| Process Intelligence Engine (bottleneck detection + ROI) | ● Built-in | ○ No | ◐ Planning-scoped | ○ No | ◐ Custom builds | ● Core strength (Celonis) | ○ No |
| Source-cited responses (every fact attributed) | ● Always | ◐ Sometimes | ○ No | ○ No | ◐ Configurable | ◐ Grounded in the process graph | ◐ Configurable, varies by tool |
| Read-only by doctrine; humans always decide and act | ● By design | ◐ Workflow-dependent | ◐ Autonomous execution shipping | ◐ Moving to automated writes | ○ Variable | ○ Automation is the product | ○ Conversational only |
| Proactive prioritization (ranks the day's decisions before being asked) | ● Continuous, impact-ranked | ○ No | ◐ Agent-driven planning + alerts | ◐ Alerts + emerging agent actions | ◐ Custom dashboards | ◐ Alerting + agent triggers | ○ Reactive only |
| Vertical specialization for distribution / CM / hybrid operations | ● Sole focus | ○ Horizontal | ◐ Mfg-leaning | ○ Logistics-only | ○ Horizontal | ◐ Celonis ships a supply chain suite | ○ Horizontal |
| No customer data used for foundation-model training | ● Contractual + architectural | ◐ Vendor-dependent | ◐ Vendor-dependent | ◐ Vendor-dependent | ◐ Vendor-dependent | ◐ Vendor-dependent | ◐ Tenant-dependent |
| Audit-grade append-only action log | ● Forensic-grade | ● ERP-native | ◐ Planning logs | ◐ Event logs | ◐ Variable | ◐ Automation / process audit | ○ Conversation logs only |
| Time to first measurable outcome (one workflow) | ● Weeks, not months (projected) | ○ 12-24 months | ○ 9-18 months | ◐ 3-6 months | ○ 12+ months | ○ Months (data ingestion first) | ● Days (per-user) |
| Change-of-control protections for design partners | ● Source escrow + perpetual license | ○ Not standard | ○ Not standard | ○ Not standard | ○ Not standard | ○ Not standard | ○ Not standard |
| Comparison reflects vendor public documentation · as of July 2026 | |||||||
Read-only is a deliberate posture, not a missing feature. Vendors shipping autonomous writes are making a different, valid bet; we optimize for trust and auditability first.
Comparison reflects vendor public documentation as of July 2026 and the architectural design intent of OpsATC.AI. Some adjacent vendors offer roadmap items overlapping with us; we update this matrix as the category shifts. Have a vendor or capability we should add? Email [email protected]. We update the matrix on real evidence, not marketing claims.
See it run on your worst week.
Bring an exception you couldn't resolve: a missed cut date, an escalation you didn't see coming, a build that slipped because two buyers couldn't see each other's portfolios. Thirty minutes. We'll walk it through The Captain live.