labs@atheron:~/industries/food-beverage/ai$ train agent --grounded

AI food label review

Allergens checked first, so your specialist decides faster.

Label review is careful, repetitive reading, which is work a model can do first so a specialist can decide faster. The agent never approves a label; it lists what it found and why. At a few labels a week, a frontier model through its API is the cheapest way to run it.

Start a project See the example projects

// what matters here

What is different in this industry.

Your rules, not the model's

Your team writes down the rules it applies, and the agent cites the rule behind each issue, so a finding can be checked rather than trusted.

Both languages at once

English and French panels are compared line by line, so a change made in one language and missed in the other is flagged before print.

The specialist decides

Every issue is accepted or dismissed by a person, and the dismissed ones become cases in the next evaluation run.

Recipes handled with care

Only the label and the recipe for that product are sent, under the provider's business data terms. If your formulas cannot leave your network, an open-source model runs in your own cloud.

// example projects

Priced examples for this service.

Each one is hypothetical, labelled as such, and priced live from our rate card. Open any of them in the estimator and make it yours.

Example projectWeb appAIFrontier model

Label and allergen review agent

Hypothetical. Not a client, not a result.

// The problem

A beverage and snack maker reformulates often, and each change means a regulatory specialist checks label artwork, ingredients and allergen statements against the recipe by hand.

// What we would build

An agent that reads the label artwork and the recipe, checks ingredient order, allergen statements, bilingual text and nutrition facts against the rules your team has written down, and lists each issue with the rule it comes from for the specialist to decide. It runs on a frontier model through its API, which reads artwork well and costs little at a few labels a week; if your recipes are a closely held secret, an open-source model in your own cloud is the alternative.

// What is in it

Label artwork and recipe uploaded together, as PDF or image
Ingredient order checked against the recipe's weights
Priority allergen and gluten statements checked
English and French text compared side by side
Each issue cited to its rule, for the specialist to accept or dismiss
Evaluation set of past labels with known issues, run before every change

// Stack

Frontier model API with vision
Python
Next.js
PostgreSQL
DigitalOcean

// estimate

Build: ≈ US$88,200 to US$135,000, delivered within 22 weeksCAD 125,600 to 192,100
Hosting: ≈ US$218 a monthCAD 310 a month
Support: ≈ US$1,000 a monthCAD 1,425 a month

Prices in your currency are estimates from today's Bank of Canada rate. All invoicing is in CAD or USD.

AI route: Frontier model
Model running cost: ≈ US$42 a monthCAD 60 a month

Timeline by milestone

Discovery: 2.9 to 3.4 weeks
Specification and evaluation plan: 0.4 weeks
Design approved: 2.4 to 3.9 weeks
Core features: 1.4 to 1.9 weeks
Full build: 0.9 to 1.4 weeks
Working pilot: 3.9 to 6.4 weeks
Testing and fixes: 0.9 to 1.9 weeks
Launch: 0.9 to 1.4 weeks
Production: 0.9 to 1.4 weeks

How it is paid

Deposit 20%: CAD 25,120 to 38,420
Discovery 2%: CAD 2,512 to 3,842
Specification and evaluation plan 10.2%: CAD 12,811.20 to 19,594.20
Design approved 2%: CAD 2,512 to 3,842
Core features 6.2%: CAD 7,787.20 to 11,910.20
Full build 4.1%: CAD 5,149.60 to 7,876.10
Working pilot 30.7%: CAD 38,559.20 to 58,974.70
Testing and fixes 2%: CAD 2,512 to 3,842
Launch 2%: CAD 2,512 to 3,842
Production 10.8%: CAD 13,564.80 to 20,746.80
Holdback, 30 days after launch (10%): CAD 12,560 to 19,210

Start from this example

// questions

Questions we get about this.

Can the label agent approve labels for us?

No, and it should not. It does the first careful read and lists issues with their source; a qualified person on your team signs off.

Does it know the labelling rules for every market?

It works from the rules your team provides for each market, such as Canada's Food and Drug Regulations or US FDA labelling rules. We do not give regulatory advice.

What happens when labelling rules change?

Your specialist updates the written rules, the evaluation set is run again, and the agent applies the new version from then on, with the date recorded.

Back to the industry: Food and beverage About the service: AI agents and models

// next

Not quite your project?

Tell us what you have in mind. We will come back to you with a range and the questions that would narrow it. Or book a call and talk it through.

Start a project Book a call