Tight → Curated → Open, On Purpose
Most manufacturers do not need one chatbot for every task. You need a governable way to pick the right answer mode for the risk, the user, and the workflow. Tight starts with only your vetted product corpus. Curated adds vetted industry context. Open adds controlled web context when you must understand evolving jobsite conditions or market shifts.
This is not theory. It is workable governace that lets product leaders, sales enablement, support, compliance, and IT choose speed where safe and certainty where required. It also creates a clear audit trail that matches how inspectors and customers ask for evidence.
Tier 1: Tight Mode For Facts That Bind
Allowed sources: current internal master data only. Examples include PIM or MDM attributes, approved Product Data Sheets, SDS, ERP price books, approved installation instructions, warranty terms, and certification letters stored in your QMS.
Citation rules: every answer must cite document IDs and versions. If the claim cannot be directly supported, the assistant replies with “I don’t know” and explains which internal artifact is missing. No blending with outside content.
Refusal and escalation: refusal on any red line topic, including ratings, certifications, and hazmat handling. Route unresolved items to Technical Services or Product Management with a prefilled evidence pack and links to the missing records.
Where to use it: quoting and CPQ inputs, catalog attributes, dimensional fits, thermal ratings, warranty language, and compliance claims. These areas face regulatory expectations for traceability that map cleanly to NIST’s Govern and Map functions in the AI RMF (see the NIST AI RMF and Playbook, updated February 2025).
Tier 2: Curated Mode For Solutioning And Context
Allowed sources: Tier 1 plus a vendor-vetted library of industry references. Examples include approved code excerpts, harmonized standards summaries, official regulator FAQs, and manufacturer position papers that have been SME reviewed.
Citation rules: first cite the internal source for product facts, then the curated reference for context. If curated guidance conflicts with Tier 1 data, the assistant flags the conflict and defaults to Tier 1. The model still answers “I don’t know” when neither source supports the claim.
Refusal and escalation: escalate to domain SMEs for interpretation questions, such as whether a competitor’s datasheet implies functional equivalence. Log all conflicts and decisions to your audit store.
Where to use it: solution design notes, competitive positioning, RFP response context, compatibility considerations that depend on code or typical assemblies.
Tier 3: Open Mode For Market And Field Discovery
Allowed sources: Tier 1 and Tier 2, plus controlled web search. Use an allowlist of official regulators, standards bodies, and government pages. Apply a denylist for forums and marketing sites when claims could mislead. Require snapshots of every cited page at time of use.
Citation rules: always cite the live URL and store a static snapshot with timestamp. Apply recency checks to reject content older than a defined window, for example 24 months, unless a human waives it. If a web claim affects safety or specifications, the assistant must confirm alignment with the internal master before suggesting action.
Refusal and escalation: refuse any safety-critical instruction that depends solely on the web. Escalate to Tech Services with the captured sources. Use a visible disclaimer for exploratory answers.
Where to use it: market discovery, jobsite insights, evolving code discussions, and early-stage competitive landscaping. The EU AI Act’s staged obligations began applying in 2025 and continue into 2026 to 2027, which makes documented provenance and governance essential for EU-facing teams (EU timeline, 2025–2027, Official AI Act text, 2024).
Workflow Examples You Can Run This Quarter
Quoting and CPQ inputs, Tier 1: The assistant confirms a roofing membrane’s thickness, roll width, and fire rating from the PIM record and cites the current PDS version. If an attribute is missing, it refuses and files a data gap ticket.
Compliance claims, Tier 1: The assistant assembles an evidence pack for an RFP matrix using the approved SDS, declaration letters, and warranty PDFs. It refuses to cite third-party brochures for safety claims.
Solutioning and competitive context, Tier 2: A rep asks if our polymer-modified mortar can replace a competitor’s mix for exterior use in coastal conditions. The assistant cites our internal formulation and installation spec, then adds a curated link to a code requirement summary reviewed by our SME.
Market or field discovery, Tier 3: Sales ops asks what changed in vapor barrier discussions in the last year. The assistant summarizes regulator and standard body pages that passed the allowlist and recency checks, links the snapshots, and labels the output exploratory.
Guardrails That Matter In Practice
- Mandatory citations in every tier, with document IDs, versions, URLs, and snapshot links.
- Confidence thresholds per workflow. Low confidence routes to human review before the answer is visible to customers.
- Red line topics where the model must refuse and escalate. Examples include ratings, certifications, SDS or hazmat handling, structural load ratings, and warranty scope changes.
- Audit logging that tracks prompts, model versions, retrieval sets, human edits, and final answer IDs. NIST encourages documentation and traceability as part of trustworthy AI outcomes (AI RMF 1.0).
- Source snapshots for Tier 2 and 3, stored with immutability controls and retention aligned to your QMS.
- Web allowlist and denylist, with recency checks and domain reputation rules. Prefer official regulators and standards bodies for anything safety relevant.
Liability, Spec Drift, And How To Stop It
Outdated SDS or PDS language creates real exposure. OSHA’s Hazard Communication Standard requires manufacturers to ensure SDS information accurately reflects the scientific evidence and to update within three months when new significant information is found (29 CFR 1910.1200(g)(5)). Your Tier 1 must always cross-check claims against the latest internal master before answering.
Document control reduces drift. ISO 9001 expects organizations to control documented information so it is available where needed and adequately protected, and a 2026 revision is in motion, so quality teams should expect renewed scrutiny of change control and record keeping (ISO 9001 revision update, 2025, ISO/DIS 9001, 2026). Build automated checks that compare retrieved passages to the current master record and block answers when versions diverge.
Practical tip: run a nightly job that revalidates every cached citation in your answer store. If a source version increments, expire downstream answers and trigger re-review.
Why Niche Manufacturing Agents Win In Tier 2
General LLMs are broad. They do not know your domain schema, attribute names, or the way your SKUs encode performance. A niche agent can use your ontology, unit rules, material families, and compatibility matrices to ground retrieval and drastically cut hallucinated product claims. NIST’s Generative AI Profile emphasizes provenance, evaluation, and content attribution, which is easier when your knowledge is controlled and structured (NIST GenAI Profile, 2024).
Teams also move faster. A curated library that maps to your taxonomy lets the agent propose substitutions, show cross-references, and surface code constraints without leaving Tier 2 safety.
Operating Rules Per Tier
Tier 1, allowed sources: internal PIM or MDM, approved PDS, SDS, warranty, controlled installation guides, ERP price and availability, certificates of conformity stored in QMS. Always cite version and effective date. Refuse on missing data. Escalate to Product or Tech Services.
Tier 2, allowed sources: Tier 1 plus SME-vetted regulators and standards summaries, internal application notes, and competitor facts that were source-verified. Cite internal fact first, then the curated source. Escalate when curated and internal conflict.
Tier 3, allowed sources: Tier 1 and 2 plus allowlisted regulators and standards bodies. Store snapshots, apply recency checks, and label exploratory outputs. Never override Tier 1 product facts with web text.
What Changes In 2026 And Why It Matters
If you sell into the EU, the AI Act continues phasing in obligations through 2026 and 2027, including transparency rules and enforcement readiness. Governance and obligations for general-purpose models started in August 2025, with broader rules applying by August 2026 and embedded high-risk product rules by August 2027 (Commission timeline, 2026). This makes logging, traceability, and refusal-on-uncertainty not just good hygiene but a compliance ally.
Implementation In 60 Days
Week 1 to 2, pick the workflows and assign a tier per workflow. Start with CPQ and compliance in Tier 1, solutioning in Tier 2, discovery in Tier 3.
Week 3 to 4, stand up retrieval from your PIM or MDM and QMS, and add citation capture to every answer. Turn on the “I don’t know” branch with a human review queue.
Week 5 to 6, publish the allowlist, denylist, and recency rules. Add snapshotting and audit logging. Pilot on five high-volume questions, then move to your top ten CPQ attributes.
Small Operational Details That Pay Off
- Show the citation preview in the chat so reps can open the PDS page instantly.
- Use confidence thresholds tuned per workflow. For CPQ, require a higher bar than for market discovery.
- Treat audit logs as quality records. Align retention with your QMS and expected customer warranty horizons.
- Train the assistant to ask clarifying questions when an answer would cross a red line topic.
The Payoff Without Over-Promising
You will not eliminate every error, and you should not try to automate judgment. What you can do is reduce wrong specs, make refusals helpful, and keep auditors satisfied that your process meets contemporary expectations for traceability and governance. The first rules of the EU AI Act already apply, and more arrive through 2026 to 2027, so the timing is right to make this model your default for safe scale (EU AI Act first rules, 2025).
