Supply Chain & Logistics
AI that moves freight, not just data
Supply chains generate an explosion of operational data spread across systems. Datafi connects the full picture so AI can reason over real operations and take action, not just generate reports.
Critical information lives in too many places. Decisions are made with partial context.
Fragmented Data Access
Procurement, transportation, warehousing, fulfillment, and invoicing each generate data in different formats, owned by different teams, across different tools. The first job in any workflow becomes hunting and reconciling information.
Workflow Gaps
AI tools operate alongside processes, not inside them. Conversations stop at advice while employees still have to find data, run analysis, and execute follow-up actions across multiple systems manually.
Governance Barriers
Without built-in permissioning, data lineage, and auditability, AI adoption stalls because the risk feels too high. Security and compliance get bolted on after deployment, creating gaps that grow with scale.
The Solution
An operating system that connects insight to action
Datafi brings together a unified data experience, policy-driven control, and agentic workflows so organizations can move from AI that answers questions to AI that solves problems across supply chain operations.
1 unified
Data Experience
Every employee interacts with the complete operational picture
100% governed
By Default
Every agent inherits authentication, authorization, and audit trails
1000s daily
Micro-Decisions
AI handles the operational backbone of routing, exceptions, and audits
E2E context
Full Ecosystem
TMS, WMS, ERP, EDI, carrier portals, and spreadsheets connected
Use Cases
AI that operates inside the process, not alongside it
Document Automation
BOL creation and validation
Bill of Lading workflows involve repetitive steps, manual data entry, and compliance checks that consume hours of operational time. AI streamlines document creation, validates required fields, cross-checks shipment details, and flags discrepancies before they become delays or chargebacks.
Auto-populate BOL fields from shipment and order data
Cross-check compliance requirements before submission
Flag discrepancies and route for resolution automatically
Transportation Planning
Route optimization and planning
Route and mode decisions require balancing service levels, capacity constraints, cost, and real-time disruption signals. AI workflows evaluate routing options, incorporate current constraints, and recommend or execute changes with auditable reasoning and business rules.
Evaluate multi-modal routing against live constraints
Balance cost, service, and capacity trade-offs automatically
Respond to disruptions with auditable decision logic
Freight Audit
Revenue recovery and freight audit
Freight invoices and accessorial charges frequently contain errors, mismatches, or missed recovery opportunities. AI agents compare invoice line items against contracts, shipment events, and agreed terms to identify recoverable charges and trigger dispute workflows with supporting evidence.
Compare invoices against contract terms automatically
Identify recoverable charges and accessorial mismatches
Generate dispute workflows with evidence documentation
Proactive Resolution
Exception management and proactive resolution
Late pickups, missed appointments, inventory mismatches, and allocation issues are unavoidable. What matters is response time and resolution quality. AI workflows monitor event signals, triage exceptions, recommend next-best actions, notify stakeholders, and keep customers informed, all while logging actions for continuous improvement.
Monitor and triage exceptions in real time
Recommend next-best actions with auditable reasoning
Log all actions for continuous process improvement
The Contextual Layer
What LLMs need to solve hard business problems
Supply chain decisions depend on context: business rules, service commitments, carrier performance, contract terms, inventory positions, customer priorities, and the messy reality of what is happening right now. For AI to move beyond answering questions and into solving problems, it needs a contextual layer that connects models to real operations. This is not about calling an API or generating a response. It is about creating an environment where AI can reason, act, and learn inside the guardrails of the business.
Root Cause Analysis
Identify service failures across multiple systems
Predictive Cost Control
Predict overruns before invoices arrive
Trade-off Optimization
Balance expedited shipping against customer value
Continuous Improvement
Improve decision logic from observed outcomes
The Platform
A complete stack for supply chain AI
Four layers working together so logistics teams can build, govern, run, and secure AI that operates inside real workflows.
Outcomes
Transformative outcomes from actionable AI
When everyone from a transportation analyst to a customer service representative can access the same source of truth through an intuitive interface, operational alignment improves dramatically.
Faster decisions
Employees no longer lose hours searching across systems or waiting on specialized teams. AI puts trusted, governed, contextual information in front of the right person at the moment of action.
Better decisions
Answers are grounded in enterprise context, not just one system's view. AI reasons across TMS, WMS, ERP, EDI feeds, carrier portals, and contract data to deliver evidence-based recommendations.
More consistent execution
Workflows become repeatable and measurable rather than ad hoc. AI ensures the same quality of routing, auditing, exception handling, and communication every time, regardless of who is on shift.
Move from AI that answers questions to AI that solves operational problems
Datafi gives supply chain teams the operating system to deploy AI agents and workflows across roles, processes, and systems, without sacrificing governance or usability.