The Problem
Most enterprise AI projects in supply chain stall because they require replacing existing ERP and TMS infrastructure, demand lengthy integration projects, or lack the security and governance controls IT requires for production deployment.
Most freight AI tools require ripping out SAP or Oracle to work. Multi-year implementation projects, high disruption risk, and no guarantee the new system handles the edge cases the old one handled through manual workarounds.
Connecting freight AI to existing TMS, ERP, EDI, and procurement systems without middleware requires API-first architecture that most vendors don't actually have. Integration projects stretch 12-18 months before any value is realized.
SOC 2 Type II, ISO 27001, and GDPR are baseline requirements for enterprise AI deployment. Most freight AI vendors don't hold the certifications IT requires, creating governance risk that blocks deployment approval.
AI agents processing invoices, executing payments, and posting to ERP need complete audit trails and governance controls. Without them, IT cannot approve production deployment for finance-critical workflows.
Freight AI tools built on a single TMS create dependency risk. If the TMS changes, the AI breaks. Enterprise IT needs TMS-agnostic AI that works across Oracle TMS, Blue Yonder, MercuryGate, and others without rebuilding.
Freight, 3PL, procurement, AP, and trade compliance data sits in disconnected systems with no common data layer, no consistent schema, and no governance controls enabling AI to operate reliably across it.
The Solution
Freehand deploys AI Teams on your existing ERP and TMS infrastructure through native connectors, API-first integration, and EDI automation, with full agent observability, complete audit trails, and enterprise security certifications from day one.
Native connectors to SAP, Oracle Cloud ERP, Oracle JDE, and NetSuite. Direct integration with Oracle TMS, Blue Yonder, MercuryGate, and others. No middleware, no rip-and-replace. Freehand layers over your existing stack.
EDI feeds, SFTP transfers, and carrier portal connections managed natively. Invoice ingestion from every source type, normalized and processed by AI without manual data preparation or custom connector development.
SOC 2 Type II, ISO 27001:2022, ISO 27017, ISO 27018, ISO 42001, GDPR, and CSA STAR certified. Role-based access controls, data residency controls, and complete audit trails built into every AI workflow.
Every AI agent decision visible, traceable, and auditable in Freehand Studio. IT and compliance teams can inspect every invoice processing decision, GL posting, and payment approval without black-box AI risk.
Freehand operates across all major TMS platforms without dependency on any single vendor. Change your TMS, keep your AI. No rebuilding, no re-integration, no re-training required.
The Freehand Context Graph unifies contracted rates, carrier invoices, shipment data, GL rules, and payment records into a governed semantic layer. A single, consistent data foundation for all AI agent operations.
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Use Cases
Benefits
Outcomes measured from enterprise IT deployments across Fortune 100 supply chain and finance organizations.
8 wks to live on existing ERP and TMS infrastructure without rip-and-replace
Zero middleware or custom connector development required
100% agent decision auditability through Freehand Studio from day one
Case Studies
Real outcomes from IT leaders that have deployed Freehand AI Teams on existing enterprise infrastructure.
8 wks From contract signature to live AI processing on existing SAP infrastructure
✓ Native SAP connector deployed and processing live freight invoices in week 8. No middleware layer, no custom development.
✓ Full agent observability configured in Freehand Studio. IT and finance teams approved production deployment in first security review.
✓ Oracle TMS integration live without any TMS configuration changes. Freehand layered over existing infrastructure exactly as designed.
Platform Capabilities
Every capability a CIO needs to deploy freight AI on existing infrastructure, with the security certifications, observability controls, and integration architecture enterprise IT requires.
AI Teams
Each AI Team deploys with complete audit trails, agent observability, and native ERP integration, with no black-box operations and no middleware.
Built For
Deployed across enterprises with complex ERP environments, multi-system infrastructure, and strict security and governance requirements for AI in production.
Complex SAP and Oracle environments, multi-system TMS infrastructure, and enterprise governance requirements for AI deployment
Strict regulatory requirements for audit trail completeness, data residency, and AI governance in production finance workflows
High-volume invoice processing, multi-ERP environments, and enterprise security requirements across global retail operations
Multi-system infrastructure, regional ERP environments, and complex EDI connectivity requirements across supply chain operations
Multi-brand ERP complexity, high-volume data processing, and enterprise API integration requirements across global operations
HIPAA-adjacent data handling, strict audit trail requirements, and enterprise security certifications required for production deployment
Multi-client data isolation, complex TMS integration requirements, and high-volume EDI and SFTP processing environments
Global ERP complexity, API-first integration requirements, and enterprise security standards for AI in supply chain finance
Regulated data handling, complex ERP environments, and strict governance requirements for AI processing hazmat and compliance data
JIT supply chain data requirements, multi-system ERP environments, and enterprise governance for AI in production finance workflows
Technology
FAQ
Straight answers to what IT leaders ask before evaluating freight AI deployment for enterprise supply chain operations.
CIOs evaluating spend management software need to assess four things beyond the feature set: integration architecture, security certifications, agent governance controls, and deployment timeline. Freehand connects to SAP, Oracle, and existing TMS infrastructure through native API connectors with no middleware layer. It holds SOC 2 Type II, ISO 27001, and GDPR certifications. Every AI agent decision is traceable through Freehand Studio. And it goes live in 8 weeks without rip-and-replace, which is the deployment standard most enterprise spend management software vendors cannot match.
Freehand goes live in 8-12 weeks with 11-20 hours of customer team time. Native ERP and TMS connectors deploy without custom integration work. EDI and SFTP connections are configured in parallel with the main deployment. Most enterprises are processing live invoices in production within 8 weeks of contract signature.
Freehand holds SOC 2 Type II, ISO 27001:2022, ISO 27017, ISO 27018, ISO 42001, GDPR, and CSA STAR certifications. Role-based access controls, data residency controls, and encryption standards are built into every AI workflow. Full documentation is available for enterprise security review from week one of the evaluation process.
Freehand Studio provides a complete governance layer for all AI agent operations. Every invoice processing decision, GL coding action, and payment approval is logged with full decision traceability. IT and compliance teams can inspect any agent decision without requesting special exports or data pulls. Audit trails are complete and available in real time.
Freehand has native connectors for Oracle TMS, Blue Yonder, MercuryGate, Manhattan, and e2open. The platform is TMS-agnostic by design. Changing your TMS does not require rebuilding the Freehand integration. The AI layer operates independently of any single TMS vendor.
EDI feeds and SFTP transfers are managed natively by Freehand without custom connector development from IT. Invoice ingestion from carrier portals, email, and ERP exports is all handled through the same normalized ingestion layer. No data preparation pipelines or custom ETL work required from the IT team.
Freehand's Context Graph builds the governed data layer from your existing systems without a separate data engineering project. No data warehouse requirement, no ETL pipeline, and no custom schema work from IT. The AI layer reads from and writes to your existing systems of record directly through native connectors.
Freehand is TMS-agnostic and ERP-connective by design. All outputs are pushed to your systems of record natively. The API-first architecture means IT teams can integrate Freehand outputs into internal data warehouses or analytics platforms without dependency on Freehand's own reporting layer. Change any component of your stack without disrupting the AI deployment.
Most enterprise spend management software projects stall on integration timelines and security reviews. Freehand deploys on your existing ERP, TMS, and EDI stack with SOC 2, ISO 27001, and full agent observability from day one.