01 / Customer question
The commercial context
Trust depends on the claims AI repeats.
Consumers may ask AI about ingredients, health needs and product comparisons before they buy. An answer can exaggerate a benefit or describe a different formulation from the product on sale. Accurate discovery needs evidence and approved market-specific claims.
OTC medicines, supplements, food, sports nutrition and fitness services have different requirements. We assess the relevant product and audience rather than applying one claims or commerce approach to every business. Popularity is not evidence that a benefit can be claimed.
Customer journeys
Evaluate ingredient, need and audience questions.
We build the assessment around specific questions, audiences and markets. These examples show the kinds of journeys we can examine; the final scope follows your priorities.
02 / Customer question
Are ingredients, allergens, serving/dosage information and relevant warnings correct?
03 / Customer question
Does a comparison avoid unsupported disease claims or inappropriate personal advice?
How SWLR can help
Connect discovery with approved claims and product data.
01
Claims and scenario evaluation
We evaluate ingredient, need and audience questions against approved references. Findings identify material exaggerations, omissions and unsupported claims within the agreed products and markets.
You receive: Material-claims baseline and issue register.
02
Product and channel reconciliation
We reconcile formulation, product-page, feed and retailer information. The priorities connect accurate ingredients and intended use with applicable approved claims and platform eligibility.
You receive: Approved-claims register and data/content priorities.
03
Consumer-care readiness
We assess product knowledge and review for consumer-care assistance. Adverse-event handling, personal questions and specialist escalation are scoped with the qualified owners relevant to the business.
You receive: Care-assistant pilot and review design.
Internal AI readiness
Give brand and care teams evidence they can use.
Brand and care teams need a current approved-reference framework and a reliable update process when formulations change. We assess scientific or regulatory review, retailer updates, knowledge permissions and staff enablement.
Nutrition claims, health claims and diagnosis or treatment advice are different matters. A pilot defines those boundaries and the appropriate hand-off. Evaluation considers claim integrity, applicable warnings and task quality as well as productivity or purchase-related measures.
A practical first engagement
Consumer Health AI Claims & Discovery Assessment
We agree the business track, market, products and formulations, audiences, approved claims and channels. You receive discovery and material-claim findings, a reference map, data and content priorities, review requirements and options for eligible discovery or consumer-care pilots.
01
Agree the scope
We define the business questions, references, AI surfaces and teams involved. Access requirements and dependencies are agreed before the assessment begins.
02
Review the evidence together
Findings distinguish observed answer behaviour from the underlying content, data or workflow issue. Your teams help establish which changes are material and feasible.
03
Choose the next action
The roadmap sets out priorities, owners, dependencies and validation. Where a pilot makes sense, we scope the implementation and evaluation work with the relevant teams.
Evaluation
Measure the changes that matter.
We agree the criteria before making changes. Answer samples are recorded with their questions, market, surface and date. Repeat checks help show patterns within that scope; commercial outcomes and internal workflow gains need their own evaluation with your teams.
Substantiated representation
Ingredient and allergen accuracy
Market applicability
Consumer-care quality
Part of Ayima
Technical search expertise. Practical enterprise thinking.
SWLR brings an AI visibility and readiness remit to Ayima's enterprise search background. We connect the business question to the content, data, access and technical work behind it, then help teams prioritise the next steps.
Common questions
Before we begin.
Can we improve discovery without making stronger claims?
Yes. Clearer approved information, correct product identities and better references can support accurate discovery. The objective is appropriate representation of the evidence and product, not stronger or more frequently repeated claims.
Will all our products qualify for AI shopping?
Eligibility depends on the product, market and platform. Medicines, supplements, foods and services do not necessarily share the same rules or integration routes. We assess eligibility before planning a shopping pilot.
How do you handle personal health questions?
We define the approved information an assistant can explain and the questions that require qualified advice or escalation. A consumer-care workflow should not turn product information into diagnosis or unsupported personal treatment guidance.
FMCG / Consumer Packaged GoodsAssess how AI recommends your products for real needs and occasions, then improve the data connecting brand discovery with retail availability.Healthcare, Pharma & MedTechAssess how AI represents your services, evidence and approved information, and identify suitable workflows for accountable adoption.
Signal → Evidence → Action
Start with the questions that matter.
Discuss your products, markets and the approved claims and information behind them.