Audit an AI Company Brief for Unsupported Claims

Audit claims instead of judging the writing style

Readability is not a truth test. A hesitant sentence can be well supported, while an elegant paragraph can contain several unsupported steps. Start by highlighting claims about the company: what it sells, whom it serves, where it operates, which technology it uses, who leads it, and what business conditions might make an offer relevant. Leave purely organizational phrases outside the claim ledger.

NIST's Generative AI Profile describes confabulation as confidently presented erroneous content and notes that generated logic or citations can also be misleading. That risk motivates source review, but the practical method here does not require guessing how a model produced the error. Review the final claim against the available evidence, whether the text was generated, manually written, or assembled from several systems.

Choose a unit small enough to judge. 'The company recently expanded its European ecommerce operation and needs retention support' contains at least three claims: an expansion, a market or operating scope, and a need. The first two may be factual questions; the last may be a sales hypothesis. Auditing the whole sentence as a single true-or-false item makes it easy for supported context to shelter an unsupported conclusion.

References: NIST AI 600-1: Generative Artificial Intelligence Profile ↗

Preserve the draft and build a claim ledger

Save the reviewed brief as a versioned artifact before editing it. Record its company identifier, research date, supplied input, intended offer, and source list. If the brief includes a score, keep the score and criteria version as well. A later correction to a factual premise may change the recommendation, so the original chain of reasoning needs to remain inspectable.

Create one ledger row per material claim. Useful columns include claim_id, original_text, claim_type, company_scope, cited_source, source_date, review_date, support_status, corrected_text, downstream_effect, and reviewer_note. The ledger is an audit aid, not a requirement to burden the final reader with every intermediate annotation. Its purpose is to make corrections reproducible.

Prioritize claims that affect eligibility, scoring, contact selection, or external messaging. A mistaken adjective may be harmless; a wrong platform, invented funding event, or misidentified buyer can change the entire campaign. This priority ordering helps a small team spend review time where a false claim would be most consequential, while still reserving a pass for the rest of the narrative.

Separate observation, inference, and recommendation

An observation reports what a source supports: the company advertises a subscription product, publishes a named role, or lists a service location. An inference connects observations to a possible explanation: the subscription model may make retention analysis relevant. A recommendation proposes an action: ask whether repeat purchase measurement is a current priority. Each type can be useful, but they should not be presented as interchangeable facts.

Look for language that smuggles an inference into an observation. Words such as struggling, underperforming, fragmented, ready, and urgently often require more evidence than the brief provides. A public form with several fields does not establish internal administrative burden. A platform tag does not establish dissatisfaction. A recent vacancy does not establish net headcount growth.

Use explicit wording when the conclusion is provisional. 'The public workflow suggests a discovery question about handoffs' is more defensible than 'The company wastes time on manual handoffs.' The narrower wording still helps a salesperson prepare. It also leaves room for the prospect to explain that the apparent problem is already solved, intentional, or irrelevant.

Check that the citation supports the sentence

Open the cited page and locate the actual supporting passage. A page title or search snippet is not enough when the claim depends on details in the body. Confirm that the source says what the brief says rather than merely mentioning a related topic. If the brief claims the company sells to hospitals, a page about a hospital charity donation does not support the customer classification.

Watch for citation drift across paragraphs. A source attached to the first sentence may appear to support several later claims that were never present in the source. Split the paragraph and attach evidence locally. A source list containing five credible websites does not automatically substantiate every statement in the dossier, especially when the strongest claims are recommendations generated from those pages.

Record partial support carefully. A source may justify 'offers implementation services' but not 'specializes in enterprise implementation.' The correction can preserve the supported core while removing the unsupported scale or emphasis. Avoid an all-or-nothing approach that either accepts the embellished sentence or discards useful research entirely.

Verify the company and the surface being described

Match the source to the intended company identifier, not just a similar name. Check branding, domain ownership clues, business description, and any supplied disambiguating information. A convincing brief about the wrong company is still wrong. This failure often propagates because once the initial identity is accepted, every later source appears to reinforce the mistaken profile.

Distinguish parents, subsidiaries, brands, and individual websites. A group can operate a consumer brand and an industrial subsidiary with different buyers and technology. A platform visible on a campaign microsite does not establish the corporate stack. The brief should state whether a claim concerns a particular web property, operating business, or corporate group.

When the evidence spans several entities, represent the relationships rather than collapsing them. A sentence such as 'The parent owns Brand A, whose store shows the observed commerce trace' preserves scope. It is more useful than assigning the platform to every company in the group. If ownership itself is uncertain, keep that relationship unresolved rather than using it as a bridge for further claims.

Check temporal language and source age

Words such as current, recently, now, expanding, and migrating introduce time claims. Look for an event date, source publication date, and observation date. A page read today may describe an old project. A case study published recently may recount a migration completed much earlier. The date of access should not silently become the date of the business event.

Rewrite unsupported recency language into a dated observation. 'A company announcement dated March describes a new office' is auditable. 'The company is rapidly expanding' adds a pace and continuing condition that may not be supported. If the exact event date is unknown, say so. Removing a false timing claim can change whether the information is a useful sales trigger.

Compare conflicting sources by scope as well as recency. A newer page may be less specific than an older detailed one, and neither necessarily settles the present state. If a role or platform cannot be established as current, mark it historical or unresolved. Do not let the need for a crisp brief override the evidence boundary.

Worked example: audit a fictional account brief

Consider this illustrative draft about the fictional merchant Larkwell Home: 'Larkwell is a fast-growing Shopify Plus brand with weak repeat purchase performance. Its new operations director controls the retention budget, making it a high-intent prospect for lifecycle marketing.' The sources are a current storefront, an old agency project page, a leadership biography, and a product subscription page.

Break the text into claims. The storefront supports that Larkwell sells home products online. The agency page mentions Shopify without establishing the current Plus plan. The subscription page supports a recurring-purchase offer but says nothing about actual retention performance. The leadership biography supports a named operations role but not control of the marketing budget. None of the sources establishes buying intent.

The corrected brief can remain commercially useful: 'Larkwell operates an online home-products store and advertises a subscription option. Public evidence reviewed does not establish its current Shopify plan or retention performance. The operations director is a possible stakeholder, while budget ownership remains unconfirmed. A discovery question could explore how the subscription program's lifecycle reporting is handled.'

Worked example: a correct source attached to the wrong entity

The fictional North Quay Group has a corporate site, a logistics subsidiary, and a retail brand. A brief for the logistics subsidiary says it operates a consumer ecommerce store and uses a particular marketing platform. The citations are real within the fictional scenario: they describe the retail brand accurately. The failure is not invented source content; it is an unsupported transfer across the group.

The reviewer first identifies the requested operating company and traces each cited domain. The retail storefront belongs to a sibling brand, while the logistics subsidiary's own pages describe warehousing and fulfillment services. The group relationship may be relevant context, but it does not establish that the logistics company is itself the merchant or uses the retail brand's marketing system.

Correct the entity map, then revisit all dependent judgments. A score for a retention agency may fall because the target is a service provider rather than a merchant. A logistics technology offer may become more relevant. The lesson is to repair the premise and recalculate the recommendation, rather than merely changing one sentence while leaving the old score and contact rationale intact.

Find unsupported assumptions inside scores

Inspect the scorecard inputs after reviewing the prose. A narrative correction is incomplete if the score still contains points for the removed claim. Trace each material criterion to its evidence. If a score includes 'growing team,' 'legacy platform,' or 'high purchase readiness,' ask whether those concepts have defined rules and supported observations.

Keep model judgment visible. A seller-specific score can be useful for prioritization without being an objective measurement of company quality. Document which criteria are mandatory, which are preferences, and how unknowns are treated. If the offer changes, the score may change even when every company fact stays the same. That is a feature of offer-relative evaluation, not an inconsistency to conceal.

Look for circular explanations. 'This is a high-fit company because its fit score is high' provides no evidence. The explanation should identify the actual product, buyer, operational context, and exclusions that drive the result. If the reviewer cannot reconstruct the decision from the supported inputs, the score is not yet auditable.

Correct the brief without erasing the audit trail

Use a small set of dispositions: retain, narrow, relabel as inference, mark unresolved, remove, or request further evidence. Record the reason next to the claim. These categories are easier to act on than a general 'needs improvement' comment and help distinguish writing corrections from research corrections.

Apply changes to dependent artifacts together. A wrong company match can affect the table, dossier, score, suggested buyer, and outreach preview. A current-role correction can affect routing. A removed pain claim can affect the proposed opening line. Treat the dossier as a connected set of decisions rather than a text document whose paragraphs can be fixed independently.

Retain the original version and a concise correction log for the team. The final reader usually needs the corrected brief and material uncertainty, not a long history of every edit. The internal record should still show whether a failure came from source selection, extraction, entity matching, reasoning, or export. That distinction makes the next process improvement more targeted.

Calibrate reviewers and investigate recurring failures

Have two reviewers independently judge a small common set of claims before dividing a large audit. Compare disagreements about current evidence, entity scope, and the boundary between fact and inference. Resolve the definitions with concrete examples. Agreement on the rule is more valuable than forcing agreement on a score without understanding the underlying difference.

Track recurring failure categories. If many briefs infer company-wide software from a single tag, improve the scope rule. If roles are repeatedly assigned from old biographies, improve freshness handling. If sources are relevant but do not support the cited sentence, improve claim-to-source mapping. A repeated pattern deserves a broader check of the affected population.

Do not evaluate the process only on whether reviewers can find errors. Also ask whether the corrected brief remains useful for the buyer's decision. An audit that removes every interpretation can leave a pile of disconnected facts. Keep reasonable inferences and recommendations, but label them and expose their premises. The objective is supported judgment, not the elimination of judgment.

Release a brief someone can safely use

Before release, read the corrected brief as a salesperson would. Can the reader distinguish facts from questions? Can they find evidence for the claims most likely to appear in an email? Is the recommended stakeholder described with appropriate uncertainty? Does the score explain relevance without implying purchase intent? This final use-oriented pass catches problems that a mechanically complete ledger can miss.

Make the release decision explicit. A brief may be ready, ready with stated limitations, or held for a blocking issue. An unresolved optional field need not stop all use, while an unresolved company identity should. Preserve the reason so that a later user does not mistake a provisional dossier for a fully settled profile.

• Freeze the reviewed version and record the intended company, offer, and research date.
• Split compound statements into individually testable claims.
• Open sources and compare the exact claim with the supporting passage.
• Check company identity, parent relationships, web-property scope, and dates.
• Relabel hypotheses and remove unsupported statements about pain, performance, or intent.
• Recalculate scores and revise outreach previews when their premises change.
• Retain material unknowns and define what further evidence would resolve them.
• Release only after the final brief communicates its evidence boundaries clearly.