Supply Chain LIVE - US Summit 2026 | Yaniv Butel on AI Agents Solving Logistics Spend Leakage

Why It Matters

By turning chaotic logistics data into actionable insights, Fixify helps manufacturers reclaim hidden costs and accelerate AI‑driven procurement, delivering measurable bottom‑line savings.

Key Takeaways

• Fixify uses AI agents to unify structured and unstructured logistics data.
• Platform identifies invoice discrepancies by matching contracts, rates, and shipment details.
• Automated agents handle data extraction, dispute resolution, and credit recovery.
• Targets manufacturers with complex, multi‑vendor logistics spend to reduce leakage.
• Future focus: broader AI adoption while addressing data security concerns.

Summary

At the Supply Chain LIVE US Summit 2026, Yaniv Butel, CRO of Pixify’s Fixify platform, outlined how agentic AI can curb logistics spend leakage for manufacturers that outsource freight to numerous carriers.

Butel explained that procurement teams are hampered by fragmented data—structured system feeds from TMS and ERP on one side, and unstructured emails, PDFs, and driver reports on the other. Fixify’s AI pipeline ingests both, extracts contract terms, rates, invoices, and shipment events, then stitches them into a single narrative for each shipment.

He illustrated the problem with a repeat China‑to‑US container that incurs varying costs due to detention, storage, and ad‑hoc driver fees, often invisible to finance. The platform’s autonomous agents flag mismatches, trigger a second‑stage dispute‑resolution agent, and pursue credit recovery on the buyer’s behalf.

If adopted widely, the solution promises to tighten spend visibility, reduce over‑charges, and accelerate dispute settlements, while Fixify’s roadmap emphasizes broader AI integration and safeguards against data‑leak fears—critical for enterprises wary of exposing sensitive logistics information.

Original Description

BizClik attended Supply Chain LIVE - US Summit 2026 in Chicago to speak with Yaniv Butel, CRO and Partner at Fixefy, on closing the visibility gap in logistics expenditure.

Yaniv Butel is a seasoned leader in the supply chain technology space, serving as the Chief Revenue Officer at Fixefy. With a background that spans from business development to hands-on QA, Yaniv brings a pragmatic, "in-the-trenches" perspective to how AI can solve the persistent problem of hidden costs in manufacturing and logistics.

The core challenge facing procurement teams today is the disconnect between structured contract data and the chaotic, unstructured reality of daily operations. While procurement holds the official rates, logistics teams are managing shifts in detention, demurrage, and storage through a fragmented trail of emails, PDFs, and text messages. This lack of synchronization makes it nearly impossible for finance teams to validate if the final invoice truly matches the agreed-upon terms or the actual services rendered.

Fixefy addresses this by deploying a sophisticated pipeline of AI agents designed to "build the story" of every single shipment. By ingesting everything from driver reports and bills of lading to complex carrier contracts, the platform digitizes and reconciles data points that were previously trapped in silos. This automation allows companies to identify discrepancies instantly, ensuring they only pay for the fair value of the service provided while capturing lost revenue through automated dispute resolution.

Looking ahead, Yaniv emphasizes that the next frontier is helping organizations overcome the "AI fear" regarding data security and IP. By embracing AI early, companies can move beyond simple tracking and toward a total exposure of their operational inefficiencies. For Fixefy, the mission is clear: turning unstructured data into actionable power to ensure that what was planned in the boardroom is what is actually paid for at the dock.

Key Takeaways:

• The Unstructured Data Trap: Why relying on emails and spreadsheets for logistics communication prevents procurement from ever knowing the true landed cost.

• Building the "Shipment Story": How combining structured system data with unstructured operational data creates a full audit trail for every container.

• AI Agents in Action: The role of specialized AI agents in scraping data, identifying billing discrepancies, and managing the reconciliation process without human intervention.

• Bridging the Gap: Why the disconnect between finance and operations is the primary cause of expenditure leakage in manufacturing.

• Overcoming AI Hesitation: Strategies for organizations to safely adopt AI technology while protecting their sensitive IP and data.

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