A briefing from Enmovil

Same catch. Half the nodes. Zero extra planners.

The restructuring landed. The volume didn’t shrink. Four Alaska plants listed for sale, Saint Paul closed through 2025, 10 percent of Seattle HQ cut[4][7][10]. The same 1.2 million annual transactions[2] still move vessel to customer across a tighter network. Every exception now lands on the planners who remain.

“There is no slack in this chain.”
Trident operations lead, on fuel, freight, labor, and climate pressure across Alaska.[3]
“We have tripled the volume of transactions, but support required hasn't really changed.”
Rick Resto, Chief Information Officer, Trident Seafoods. On ~1.2 million annual transactions across Alaska, Minnesota, Oregon, Washington.[2]
The gap, in the public record

The December 2023 restructuring removed nodes. It did not remove load.

Four Alaska plants listed for sale. Saint Paul closed through 2025. Ten percent of Seattle HQ cut[4][7][10]. Catch volume is unchanged. Every remaining planner now carries a heavier exception load with less buffer at each node.

12plants
Alaska coastal processing, plus 6 in the lower 48.[1]
3Mlbs/day
Akutan at peak. Largest seafood facility in North America.[2]
67Ksqft
Carrollton cold storage. 15 climate truck bays.[2]
55countries
Wholesale, retail, food service distribution.[8]
1.2Mtxns/yr
Across four states. JD Edwards and RFgen.[2]
-10% HQ
Seattle headquarters, December 2023.[10]
Caddie
Enmovil's agentic AI. Sits above your existing SAP, Oracle, JD Edwards, TMS, and WMS stack[9]. Closes the loop between plan and execution without a migration.
Caddie · Enmovil's AI co-pilot

Six agents. One continuous loop. Over JD Edwards, your TMS, your WMS. No rip and replace.

A shipment enters at Demand Sensing, exits at Settlement, autonomously, in minutes. Then the next one enters. The loop runs 24/7.[9]

Demand Sensing
Long tail and value-added forecast on customer pull signals.
Vessel & Tender
Paces RSW hold time against plant receiving capacity.
Cold Chain
Temperature compliance and dwell across the 15 climate bays.
Dock & Yard
Sequences truck arrivals. Compresses dock-to-truck cycles.
Multimodal
Road, rail, ocean, air on one control tower through final distribution.
Settlement
Freight audit, 3PL spend analytics, landed cost per pound.
Caddie, in Enmovil's own words: “Your AI co-pilot for supply chain orchestration. Unifies planning, logistics, and execution into one autonomous intelligence layer.”[9]
Caddie applied to your operation

Three places Caddie maps to your supply chain. Pick one for a two-week experiment.

01 · Handoff time
Vessel to tender. Tender to plant. Plant to cold. Cold to truck. Every handoff runs on its own clock.
Tender hold, dock idle, Carrollton dwell, sequencing into 15 climate bays. None of it sits on one screen. With fewer nodes, a delay at one point has no buffers downstream.
Caddie answer: one orchestration layer across every handoff. When the tender lands late, dispatch renegotiates everything downstream automatically.[9]
02 · Exception load per planner
Four plants gone. Saint Paul dark. Ten percent of HQ cut. The exception queue did not shrink proportionally.
The restructuring removed nodes and headcount at the same time[4][7][10]. Exceptions that used to spread across more people and more buffers now land on the planners who remain.
Caddie answer: auto-routable exceptions get auto-routed. Planners handle judgment, not clerking. Deployed customers reclaim 30 to 50 percent of planner time on exceptions.
03 · Forecast on new SKUs
The 2026 value-added pivot pushes revenue into SKUs the org has never forecast before, at the worst possible time.
Long-tail CPG forecast accuracy runs 60 to 75 percent versus 80 to 90 percent for hero SKUs[11]. The 2026 shelf strategy[8] drops that gap into a season already running with fewer buffers.
Caddie answer: demand sensing on deployed customers runs at 97 percent forecast accuracy on long tail and new SKU shapes, because the model ingests customer pull signals, not just shipment history.
Operational impact

Six operating numbers you can measure.

Every number below comes from deployed customer outcomes, not projections. Pick the shape closest to Trident's.

Daily ETA accuracy
97%
Road, rail, ocean, air on the deployed customer base.
Source: Enmovil Caddie
Forecast accuracy
97%
Demand sensing. Long tail and new SKU shapes included.
Enmovil deployed benchmarks
Tender to plant cycle
-2hr target
Compression on RSW hold plus dock idle.
Baseline: 4 to 6 hour exception window. Booth validated.
Planner minutes reclaimed
30 to 50%
Auto-routed exceptions take clerking off the planner.
Enmovil deployed benchmarks
Integration
3 to 4weeks
Over existing SAP, Oracle, JD Edwards, TMS, WMS. No migration.
Enmovil deployment playbook
Logistics spend compression
8 to 15%
Across deployed customers. A ceiling, not a promise.
Enmovil deployed benchmarks
Already deployed

Three customer stories that map onto Trident's chain.

No seafood customer to name yet. Multimodal, cold-chain adjacent, and SAP-heavy deployments where the operating shape transfers. Named references at the booth.

Tier 1 global auto OEM
Multimodal orchestration on one control tower. Four-plus years live.
~$18B revenue · 80+ flows · rail, road, ocean, air on one platform.
Shape
Domestic and international flows across rail, road, ocean, and air on an automated control tower. Same multimodal muscle the vessel-tender-plant-ocean chain needs.
Outcome
Four to five years live. Contract extended by five more.
Relevance
Closest analog to Trident's network: many modes, many plants, weather and geography on the same clock.
“Transfers to Trident: one orchestration layer across vessel, tender, plant, cold storage, truck, and ocean freight. Today they live in separate screens.”
Fortune 100 CPG brand
Cold-chain temperature compliance on dispatch. Pan-India.
Chocolate and confectionery plants. Sensors on climate trucks.
Shape
Temperature-sensitive finished goods plant to DC. Sensor compliance and dispatch planning on one platform.
Outcome
10 percent reduction in transportation spend across first and middle mile.
Relevance
Temperature compliance transfers to Carrollton's 15 climate bays and the cold cross-dock.
“Transfers to Trident: Cold Chain agent monitors temperature and dwell across every bay, every load, in real time.”
Fortune 500 SAP customer
Head-to-head against SAP, Kinaxis, EY, Blue Yonder. Enmovil won.
Discrete and continuous manufacturer. SAP-native. Tier 1 bakeoff.
Shape
SAP-heavy planning environment where the overnight forecast job ran 16 hours and planner reports took 40 minutes.
Outcome
Extract to decision to writeback collapsed to 90 minutes. Reports went from 40 to 5 minutes. The 16-hour overnight forecast job was retired.
Relevance
Same SAP-adjacent stack Harish's team operates in.
“Transfers to Trident: Caddie ingests JD Edwards and RFgen via API, EDI, or bulk upload. Runs the loop. Writes back. No second consulting engagement.”
Scale
~100,000 trucks per day under orchestration. 97 percent daily ETA accuracy. 97 percent demand sensing accuracy. Selected over Blue Yonder, Manhattan, Kinaxis, o9, Oracle, and EY in tier-1 evaluations.
Who's building this

Enmovil · the technology thought partner for autonomous supply chains.

One AI-native platform. Demand sensing, inventory, dispatch, execution, freight settlement, sustainability reporting. All on one intelligence layer that sits above the systems you already own.

Under orchestration
~100K
Trucks per day across the customer base
Daily ETA accuracy
99%
Road, rail, ocean, air
Forecast accuracy
97%
Demand sensing on deployed customers
Logistics cost savings
8 to 15%
Measured across deployments
Integration
3 to 4wks
On existing SAP, Oracle, TMS, WMS. No migration.
Deployed at
Dispatch Planning
Multimodal Logistics
Multimodal Orchestration
Dispatch Planning
Fleet Management
Logistics Orchestration
Logistics Resilience
Inventory Management
Freight Settlement
Dispatch Planning
Transport Management
Export Planning
Runs under GDPR and SOC 2. Data ingestion via API, EDI, or bulk upload. Enterprise SSO. Deploys over existing SAP ECC 6.0 and above.
The ask

A sixty to ninety minute working session.

We leave with a shared view of where the exception load is landing post-restructuring, and three scoped experiments against it. Three questions shape what we bring.

Question 1 of 3
Since December 2023, which leg generates the most unplanned planner interventions?
Vessel to tender. RSW hold time decisions when no secondary plant absorbs overflow.
Tender to plant. Dock scheduling gaps left by closed facilities.
Inter-plant reroutes. Volume that used to divert to Saint Paul or the listed Alaska plants.
Carrollton. Cross-dock pressure from inbound flows on fewer legs.
All of them, and they stack.
Question 2 of 3
Of exceptions landing on the planning team today, what share is genuine judgment versus data lookup or status chasing?
Mostly judgment. Clerical work is minimal.
Roughly half and half.
Mostly clerking. Planners chase status across systems that do not talk.
Not measured. Would be a useful number to have.
Question 3 of 3
On the integration surface (JD Edwards, RFgen, 3PL/4PL layer), where is the biggest gap between what the system knows and what the planner needs?
Vessel and tender data does not land in JDE fast enough to drive shore-plant decisions.
3PL and 4PL status updates arrive too late.
Cross-system handoffs. Exception is in one system, the actor is in another.
Spend analytics. Freight cost per pound by leg only visible after settlement.

If you have already solved these, that is the conversation we most want to have. Bring one Alaska operations lead, one integration engineer, and one planner who owns exception resolution.

Book 60 to 90 minutes →
At the American Supply Chain Summit · Dallas · Booth [BOOTH_NUMBER]