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Haladir

Haladir combines operational data, process intelligence and optimization to support logistics decisions through its Nomos framework.

Pricing
Customer-specific implementation and quote
Free plan
No permanent free plan publicly verified
Platforms
Web

Tool Information

Haladir
Haladir
Updated: September 2026
Tool type: Logistics Decision Intelligence
Pricing: Customer-specific implementation and quote
Free plan: No permanent free plan publicly verified
Platforms: Web
Login required: Yes
API: Customer-specific system integrations; public standalone API not verified
Browser extension: No official browser extension verified
Mobile app: No dedicated native mobile app verified
AI models: Customer-scoped predictive models and constraint solvers
Developer: Haladir

About Haladir

A decision layer above logistics systems

Haladir develops decision intelligence for logistics operations through its Nomos framework. It is presented as a layer above existing warehouse, transport, order and related systems rather than a mandatory replacement for them. Operational data is reconciled into a common graph so that orders, shipments, pallets and other objects can be considered together. This common representation supports reasoning about the operation rather than treating each source system as an isolated record.

Model the process and compare choices

The official framework combines data infrastructure, process intelligence, predictive models, optimization, implementation and monitoring. A digital representation of the operation is built from events, while models estimate uncertain quantities and solvers apply relevant constraints. Advertised decision areas include routing, wave release, dock assignment, labor allocation and inventory positioning. These are scoped per customer; the site explicitly explains that components and decision classes are shaped for each implementation. Its interactive examples are simulations, not evidence that the displayed savings or timings will occur in another operation.

Keep execution proportional to confidence

Recommendations can be routed to an operator or pushed back into connected systems for suitably constrained decisions. The product also describes tracking recommended versus executed actions and recording overrides. A pilot should begin with a narrow decision class and historical examples whose outcomes are understood. Verify timestamps, identifiers, capacity limits and the cost assumptions used by the optimizer. Decide which actions need approval and how an operator can intervene when conditions change. Public pricing and a universal connector list are not established. Haladir's value must be assessed against the accuracy of the operational model and the usefulness of its decisions, with accountable human oversight where a mistake could disrupt service or create safety risks.

Key features
  • Operational data graph
  • Process reconstruction
  • Digital-twin workflows
  • Predictive models
  • Constraint optimization
  • Operator review and execution channels
  • Decision traceability
Use cases
Warehouse Decisions,Transport Planning,Supply Chain Analysis
How to use
  1. Request a scoped discussion.
  2. Select a logistics decision to improve.
  3. Map authorized operational systems.
  4. Validate identifiers and event timing.
  5. Define objectives and constraints.
  6. Test recommendations on known scenarios.
  7. Set approval and execution boundaries.
  8. Monitor decisions and operator overrides.
Best for
Warehouse Decisions, Transport Planning, Supply Chain Analysis
Integrations
WMS,TMS,OMS,YMS,ERP,Data Lakehouse
Commercial use
Professional use subject to official service terms

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