The Shift Left Movement: How Real-Time Visibility + AI Solves Critical Supply Chain Challenges
Supply chains have become highly automated, yet disruptions, delays, and manual workarounds still dominate day-to-day operations. Traditional automation delivers efficiency only through fixed workflows and fails when real-world conditions change. And in logistics, conditions are always changing. This calls for what we term as the “Shift Left Movement.”
In this article and video, we explore how combining real-time visibility with AI-driven intelligence creates adaptive, resilient supply chain execution and planning as early as possible in the logistics flow (“Shift Left”). Instead of breaking when exceptions occur, operations become intelligent, responsive, and proactive.
Watch the Video
Key Takeaways
- Traditional automation is cumbersome to build for each unique supply chain workflow
- It fails when real-world conditions change
- AI agents adapt to exceptions instead of freezing
- Real-time supply chain visibility enables proactive decision-making for AI
- Autonomous workflows reduce manual effort and firefighting
- Human + AI collaboration drives higher adoption and trust
Why Traditional Automation Breaks in Real Supply Chains
For years, automation has been positioned as the solution to supply chain inefficiency: automate more, save time, reduce cost. In reality, automation alone is brittle.
When trucks are delayed, drivers fail to arrive, ports slow down, or conditions change mid-journey, traditional systems freeze. Teams lose trust, turn back to spreadsheets, and revert to manual coordination.
Decklar takes a different approach. Rather than relying only on rigid rules, the platform uses intelligent, adaptive AI agents that learn from real operational environments. These agents do not replace people. They work alongside them, acting as copilots that handle repetitive tasks, monitor exceptions, and support decision-making as early as possible in the chain of custody to minimize the bullwhip effect downstream.
How Visibility + AI Work Together in the Shift Left Movement
Decklar applies this visibility and intelligence across real operational workflows, starting with one of the most common and risk-heavy processes in supply chains right from the point of departure.
This workflow is divided into three connected stages of transportation.
Ready to Leave: Preventing Errors Before the Truck or Container Leaves
At the dock, conditions are often chaotic. Trucks queue, teams rush, and time pressure increases error rates.
Decklar’s AI agents are built to operate like a digital dock supervisor. They verify driver identity, confirm sensors are active, ensure quality checks are complete, and capture visual evidence of the load before departure. This creates situational awareness, not just process automation.
In Transit: Intelligent Monitoring Beyond GPS
Real-time transport visibility requires more than location and condition tracking.
Decklar’s platform monitors:
- Route deviations that are of concern
- Temperature change trends that could indicate an upcoming quality risk
- Door openings that could indicate risk
- Security-risk zones; unexpected or prolonged stops
- Detention and demurrage risk exposure
Instead of waiting for humans to discover issues, AI agents trigger alerts, initiate responses, and build full audit trails automatically.
Ready to Close: Smarter, Faster, Auditable Goods Receipt
When shipments arrive, AI agents automate what traditionally slows teams down:
- Geofence-triggered goods receipt note (GRN) closure
- Compliance validation
- Electronic proof of delivery (ePOD)
- Quality compliance image capture
- Automated claim creations as needed
By the time teams review the shipment, key operational steps are complete, reducing delays and errors.
What’s Inside Turning Visibility into Decision Intelligence
Why LTCVI Matters
All operational signals are unified through Decklar’s RADAR architecture, which acts as a command center rather than a traditional dashboard.
RADAR connects:
- Real-time location and device data
- SOP compliance
- Risk posture
- Driver behavior
- Shipment condition
- And more
Only high-value signals reach teams, while lower-value noise is automatically suppressed. This is the difference between having data and having decision intelligence.
AI-Driven Risk Detection and Autonomous Response Example
When disruptions occur, speed and clarity matter.
If a truck stops in a high-risk zone, Decklar’s AI can:
- Call the driver automatically
- Escalate issues to supervisors
- Select the best communication channel
- Create a fully auditable response trail
This turns operations from reactive firefighting into proactive risk prevention.
Proactive Intelligence for Reusable Asset Management
Visibility is not just about today’s shipments. It is also about future readiness.
Decklar tracks reusable assets such as pallets, bins, totes, and containers to monitor:
- Dwell time
- Circulation cycles
- Loss rates
- Idle time
- Asset aging
AI forecasting then predicts shortages and bottlenecks before they impact production, helping teams optimise asset utilization and capital investment.
Why Visibility + Supply Chain AI Matter Now
When real-time supply chain visibility is combined with intelligent automation, teams move from reacting to problems to preventing them.
The impact includes:
- Faster, more confident decisions
- Stronger operational resilience
- Reduced manual workload
- Smarter collaboration between humans and systems
This is not just tracking. It is intelligent execution.
See Decklar in Action
Request a personalized demo to see how real-time visibility and Decision AI power faster, smarter supply chain decisions.
https://www.decklar.com/request-a-free-demo/
