Frequently asked questions

General AI models draw from a broad, unverified training corpus: a mix of web content, vendor marketing, and academic theory. None of it is curated for operational accuracy, and general models have no reliable knowledge of current industry benchmarks, carrier rate structures, AS/RS ROI norms, or WMS integration patterns.

Highbay draws exclusively from a practitioner-written vault maintained by people who have run warehouses, negotiated 3PL contracts, designed conveyor systems, and built WMS integrations. Every answer cites the specific vault article it drew from so you can verify it and go deeper. The difference is accountability: a source you can audit, not a black-box training corpus.

Search returns a mix of vendor content, academic papers, and blog posts written for SEO. None of it calibrated for operational accuracy or your specific decision context. A consultant is expensive, slow to engage, and often unavailable for the low-stakes questions that slow down day-to-day decisions.

Highbay is on demand, practitioner-grade and free. Ask a question at 11pm before a morning meeting and get a cited, methodology-backed answer in seconds.

Operations managers, logistics analysts, supply chain directors, and their teams at 3PLs, distributors, manufacturers, and consulting firms. Also:

• DC managers evaluating automation or layout changes
• Network designers comparing carrier modes, DC locations, or fulfillment strategies
• Project managers working through RFPs, vendor evaluations, or operational audits
• Consultants who need a fast methodology reference or a second opinion

It is not a general-purpose AI. It assumes operational context and uses practitioner terminology throughout. It is not designed for academic research or entry-level learning.

You type a logistics or supply chain question in plain language, the same way you'd ask a subject-matter expert. The system retrieves the most relevant sections from the practitioner vault, writes a direct, practitioner-level response, and returns it with inline citations to the source articles.

Responses are grounded in what the vault knows. If coverage is weak on a topic, the answer flags that explicitly rather than guessing or filling gaps from general AI training data.

Each response includes:

• A direct answer to your question
• The methodology or reasoning behind it
• Inline citations to the specific vault articles used
• Relevant caveats and decision variables to consider

Responses are not generic AI paragraphs; they reflect how a practitioner would actually frame the question. Signed out, answers use Support mode: clear and direct. Signed in, they use Principal mode, which frames the trade-offs, challenges assumptions and proposes next steps.

Persona mode controls the depth and framing of answers from Ask.

• Support: clear, direct answers with explanations. Good for operations staff validating a decision or learning a topic.
• Principal: senior practitioner framing: evaluates your situation, challenges assumptions, identifies risks you may not have considered, and proposes structured next steps. Good for directors and consultants running project-scale engagements.

The system says so. Answers explicitly flag when vault coverage is partial or absent. The platform will not fill gaps with guesses or general AI output. If a topic is not well covered, you will see a clear statement to that effect along with what the vault does cover on the adjacent topic.

Accuracy flagging is non-negotiable by design. We would rather tell you we don't know than give you a confident wrong answer.

The Engagement Hub is the project-scale layer of Highbay. Where Ask handles individual questions, the Engagement Hub runs structured consulting engagements: guided workflows that walk you through a complete operational analysis using a defined methodology, and produce a structured output document you can use directly in internal reviews or client presentations.

Think of it as the difference between asking a consultant a question and hiring them to run an engagement. The Engagement Hub gives you the structure of the latter at a fraction of the cost.

Current engagement archetypes include:

• DC Diagnostic: structured assessment of a distribution center's operational gaps and improvement opportunities
• Automation ROI: inputs collection, model build, sensitivity analysis, and a defensible recommendation
• Inventory Optimization: safety stock policy, SKU segmentation, and replenishment framework
• Network Redesign: node strategy, mode analysis, and footprint recommendation
• S&OP Maturity: process assessment and maturity roadmap
• Freight Rationalization: lane analysis, carrier scorecard, and negotiation prep
• 3PL Selection: RFP framework, scorecard development, and shortlist recommendation
• WMS / TMS Selection: requirements capture, vendor evaluation matrix, and selection rationale

Each archetype follows a practitioner-defined framework: it collects your inputs, classifies your situation, walks through the methodology step by step, and builds the output incrementally.

Supply chain directors, operations consultants, and project managers working on decisions that are too large and complex for a single Q&A exchange. If you are running a DC assessment, building an automation business case, or evaluating 3PL partners, the Engagement Hub provides the structure to do it methodically rather than ad hoc.

It is particularly valuable for consulting teams who need to produce repeatable, defensible deliverables efficiently, and for internal teams who want to run a rigorous process without the cost of an external engagement.

Highbay is a tool for logistics engineers, built and maintained by practitioners at Applied Continuity LLC, which operates it as Highbay. It started as a paid product; we decided it does more good as a free one.

There is no card and no trial. A fair-use limit on questions keeps running costs sensible. Highbay earns its keep through paid project support from independent logistics engineers, and integrations come with that work. See /services.

Every answer and calculator states where its figures come from, and vault pages carry their sources. Benchmarks move, though, and every operation is different.

Check a figure against its source before it goes into a client deliverable or a capital request. If you find one that is wrong or out of date, let us know and we will correct the vault.

Yes. Engineers from the Highbay Network provide front-end studies, RFP support, implementation management, commissioning and go-live, and client advocacy at $150 to $250 per hour, depending on the work. Every engagement starts with a scoping call and a written estimate, and Highbay holds the contract.

Yes, as part of a paid engagement. We set it up for your organization and invoice it directly. Answers then draw on your own content alongside Highbay's, visible only to your team.

No. Signed out, you can read every knowledge-base page, use and export every calculator, and ask three questions a day. A free account adds more questions, follow-up conversations, methods, and the workspace for projects, engagements and debriefs. Highbay is provided as-is with no uptime or backup guarantee, so do not store confidential client data in the workspace, and use Export on your account page to keep your own copy.

Yes. Your queries are not visible to other users, not shared with third parties, and not used to generate content for anyone else. We collect aggregate usage data (query volume, feature usage) to improve the tool. We do not sell data or use it for advertising.

No. Your queries are never used to train any AI model, Anthropic's or otherwise. They are processed to generate your answer and are not retained for model training purposes.

If your organization requires a Data Processing Agreement (DPA), email support@highbay.io.