Best RAG Consulting Firms for Supply Chain in Florida (2026)

Florida’s supply chain and logistics sector is one of the largest in the United States.

Port Miami, Port Everglades, and Port Tampa Bay collectively handle more than 100 million tons of cargo annually, making Florida a critical node in both international trade and domestic distribution.

The organizations operating in and around these ports (freight forwarders, 3PLs, customs brokers, logistics technology firms, and manufacturers with Florida distribution operations) have large, fast-moving knowledge bases.

That is exactly the use case RAG was designed for.

Tariff schedules change. Carrier availability shifts by the week. HS codes, customs documentation requirements, and port-specific procedures are updated continuously. No static knowledge base survives contact with Florida supply chain reality for more than a few weeks.

RAG keeps retrieval and generation separate so that knowledge can be updated without retraining the underlying model.

This guide covers the best RAG consulting firms for Florida supply chain organizations in 2026: what each one builds, who they serve, and how to evaluate RAG capability for the specific demands of logistics and supply chain.

Key Takeaways

• Florida supply chain is a high-velocity knowledge problem. Tariff schedules, carrier availability, port procedures, and customs requirements change continuously. RAG is the right architecture because knowledge can be updated without retraining the model.
• Supply chain RAG has specific retrieval challenges. Structured data (shipment records, inventory tables, carrier rate cards) needs different retrieval handling than unstructured documents. Most general-purpose RAG firms do not evaluate this distinction.
• Phos AI Labs is our pick for Florida mid-market supply chain organizations with $5M+ revenue that need RAG built and calibrated against their specific operational data.
• Ask every firm how they handle structured data retrieval. Vector search on tabular data (rate cards, inventory, shipment history) underperforms compared to hybrid retrieval that combines vector search with structured query approaches. This is a supply-chain-specific RAG challenge that separates specialized firms from general ones.
• Florida port proximity matters for some engagements. Organizations with complex customs and trade compliance requirements benefit from a consulting partner that understands the specific regulatory environment of Florida’s major ports.

1. Phos AI Labs

Best for: Florida mid-market supply chain and logistics organizations with $5M+ revenue that need RAG built against their specific operational data and integrated with their existing TMS, WMS, or ERP systems.

We are an embedded AI consulting firm and one of the first 10 OpenAI Select partners worldwide and one of the first Anthropic partners with CCA-F certification.

Our team of 10+ CCA-F certified forward deployed engineers has completed 400+ total engagements and 40+ AI Native Projects delivered, including production AI deployments for supply chain, logistics, and distribution organizations.

For supply chain, our RAG approach addresses the specific challenges that make logistics knowledge bases difficult to retrieve from effectively.

Structured data (rate cards, shipment records, inventory tables, carrier performance data) requires different retrieval handling than unstructured documents. We design hybrid retrieval pipelines that combine vector search for unstructured content (carrier contracts, customs documentation, procedure manuals) with structured query approaches for tabular data.

What we build for supply chain:

• RAG systems that retrieve from TMS, WMS, and ERP data alongside unstructured documents
• Carrier rate card and availability retrieval with real-time data freshness
• Customs documentation and HS code lookup systems
• Shipment history retrieval for customer-facing status and compliance queries
• Internal knowledge bases for freight forwarding and 3PL operations
• Port procedure and regulatory compliance retrieval for Florida port operations

Pricing:

• AI Readiness Audit: from $10,000
• Ongoing embedded delivery: from $15,000/month
• Full embedded AI department: up to $50,000/month

No self-serve signup. All engagements scoped on a call.

Talk to us about a supply chain RAG build at Phos AI Labs.

2. Grid Dynamics

Best for: Enterprise supply chain and logistics organizations that need RAG integrated as a foundational component of large-scale digital infrastructure rather than a standalone AI feature.

Grid Dynamics is a Silicon Valley-based AI and digital transformation firm whose GAIN (Grid Dynamics AI Native) platform integrates semantic retrieval directly into supply chain and commerce systems.

The firm’s approach treats RAG not as an isolated AI feature but as an infrastructure layer embedded in larger operational systems. Grid Dynamics has documented supply chain RAG deployments across commerce and logistics use cases including demand forecasting, inventory intelligence, and supplier knowledge management.

What they do well: RAG architecture at scale, integration with enterprise supply chain platforms, and the forward deployed engineer model that keeps senior architects embedded in client delivery. Their commerce and supply chain focus makes them more supply-chain-aware than general-purpose AI consulting firms.

Limitations: Grid Dynamics is sized for Fortune 1000 organizations. Project minimums and the enterprise engagement model place them beyond the reach of mid-market supply chain organizations below $200M revenue. Organizations in the $5M to $100M range will find the engagement structure larger than their situation requires.

Pricing: custom. Enterprise engagement model with significant project minimums.

3. N-iX

Best for: Mid-to-large US enterprises that need production-grade RAG for supply chain operations with strong compliance and security requirements, and access to a Florida-based US office.

N-iX is a technology consultancy that runs a US office in Plantation, Florida, and works with a substantial base of US-headquartered clients.

For RAG development, N-iX builds production-oriented proofs of concept that align to ISO 27001, SOC 2 Type 2, HIPAA, and EU AI Act requirements. This is relevant for Florida supply chain organizations with international trade compliance obligations.

What they do well: compliance-aligned RAG implementations, production-grade proofs of concept delivered in defined timeframes, and US-based project management with cost-effective engineering delivery. The Florida office is a genuine logistical advantage for organizations that need in-person engagement during the design and calibration phases.

Limitations: N-iX is a technology consultancy with broad service offerings. Supply chain RAG is part of their AI practice, not a specialized vertical. Organizations with highly specific supply chain knowledge base requirements (complex structured data retrieval, real-time rate card updates, multi-modal document sets) may need additional domain expertise.

Pricing: project-based, custom quoted. Production-oriented proofs of concept typically delivered in seven weeks.

4. Slalom

Best for: Florida-based mid-to-large market supply chain and logistics organizations ($200M+ revenue) that need RAG delivered as part of a practical, business-outcome-focused AI implementation with US-based senior consulting.

Slalom has a strong Florida presence with offices in Miami, Tampa, and Orlando, and a growing AI practice that delivers RAG as part of broader digital implementation work.

The firm’s approach ties RAG delivery to measurable business outcomes rather than technical feature delivery, which aligns well with supply chain use cases where the value case is typically clear: faster document retrieval, fewer manual lookup tasks, lower customer query handling cost.

What they do well: RAG delivery that stays grounded in business impact, close client partnership through implementation, and a staffing model that keeps senior consultants closer to the actual build than the Big 4 firms. Florida market presence and supply chain client experience make Slalom a credible option for mid-to-large market logistics organizations.

Limitations: strongest fit for the $200M to $2B revenue range. Below $200M, the engagement structure may exceed what the organization can absorb. Supply chain RAG is one capability within a broader AI practice rather than a specialized offering.

Pricing: engagements typically run $200K to $600K.

5. LeewayHertz

Best for: Mid-market Florida supply chain organizations ($10M to $200M revenue) that need fast, build-focused RAG delivery for defined logistics use cases without enterprise consulting overhead.

LeewayHertz is an AI consulting and development firm with documented logistics and supply chain RAG deployments. The firm combines strategy with hands-on building, and its ZBrain platform includes pre-built modules that accelerate deployment for defined supply chain use cases: carrier lookup, shipment status retrieval, freight rate comparison, and document processing pipelines.

What they do well: fast delivery for defined use cases, generative AI depth, and a build-first model that suits organizations with specific logistics knowledge base requirements and limited appetite for extended consulting engagements. The pre-built supply chain modules reduce time-to-production for common logistics RAG patterns.

Limitations: less focus on the upstream consulting layer (use case selection, architecture strategy, evaluation framework design) than firms that lead with diagnosis. Organizations that need help defining the use case before building will get more value from firms with a stronger consulting practice. The pre-built modules may constrain customization for organizations with non-standard knowledge bases.

Pricing: project-based. Engagements vary by scope and use of pre-built modules.

Supply Chain RAG: The Specific Challenges

Florida supply chain organizations face RAG challenges that general-purpose AI firms frequently underestimate. Understanding these before engaging a consultant will help you ask the right questions.

Structured vs. Unstructured Retrieval

Most supply chain knowledge bases combine structured data (rate cards, inventory tables, shipment history, carrier performance metrics) with unstructured documents (carrier contracts, customs documentation, HS code manuals, procedure guides).

Vector search underperforms on structured tabular data. A RAG system designed for document retrieval will not reliably answer “what is the current FEU rate from Miami to Rotterdam for carrier X.” This query needs to go to a structured data source, not a vector database.

A properly designed supply chain RAG pipeline separates retrieval by data type: vector search for unstructured documents, structured query approaches for tabular data, and a routing layer that sends each query to the appropriate retrieval method. Ask every firm how they handle this distinction.

Data Freshness and Update Frequency

Carrier rates, port surcharges, fuel adjustments, and tariff schedules can change weekly or even daily in volatile market conditions.

A RAG system designed for a static knowledge base will not handle this update frequency without deliberate engineering of the ingestion pipeline.

Ask every firm: how does the ingestion pipeline handle document updates? Is re-embedding triggered automatically when source documents change? What is the latency between a rate update in the source system and that update being reflected in retrieval results?

Multi-Document and Multi-Source Retrieval

A Florida logistics organization might need to retrieve from a TMS, a customs compliance database, a carrier rate portal, and an internal document library simultaneously.

Multi-source retrieval requires careful relevance scoring across sources that may have different document structures, update frequencies, and reliability levels. Ask every firm how they handle retrieval from multiple source systems with different schemas and update patterns.

Regulatory and Compliance Context

Florida supply chain organizations with international trade operations face CBP (Customs and Border Protection) requirements, ISF (Importer Security Filing) obligations, and country-specific import/export documentation requirements.

A RAG system that retrieves customs documentation needs to handle jurisdictional specificity: the correct answer for a shipment from Brazil is not the same as the correct answer for a shipment from the EU.

FAQs

Why Is RAG a Good Fit for Supply Chain Organizations?

Supply chain knowledge bases are high-velocity: tariff schedules, carrier availability, port procedures, and customs requirements change continuously.

RAG keeps retrieval and generation separate so knowledge can be updated without retraining the underlying model.

What Does a Supply Chain RAG System Actually Do?

A supply chain RAG system retrieves relevant operational data at query time and uses a language model to generate a grounded response.

Common use cases include carrier rate lookup, shipment status retrieval, and customs documentation.

How Long Does It Take to Build a Supply Chain RAG System?

A production-ready supply chain RAG system for a defined use case typically takes six to twelve weeks.

More complex knowledge bases with multiple source systems or real-time data integration extend the timeline.

What Is the Cost of a Supply Chain RAG Implementation?

RAG implementation costs for supply chain organizations typically run $30,000 to $150,000 depending on knowledge base complexity and integration requirements.

Mid-market specialists like Phos AI Labs start from $10,000 for an AI Readiness Audit.

How Do You Evaluate Whether a RAG System Is Working for Supply Chain?

Evaluate on retrieval accuracy, response groundedness, and data freshness. Does the system return the correct carrier rate, HS code, or port procedure?

Establish these metrics before go-live and monitor them weekly.