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Food market intelligence

Food intelligence forcommercial growth

Discover which ingredients are used across food manufacturers, foodservice brands and restaurants — and understand how ingredients are used across the food industry through real market data.

A cheeseburger with a glossy brioche bun and melted cheese against a dark restaurant background (editorial photograph).

Editorial photo · not an analysis finding

Research sample

Avcılar, Istanbul · Burger menus

Which ingredients appear most often in burger menus?

Analysis of 199 burger menu items across 11 restaurants in Avcılar.

11
restaurants
199
burger menu items

Top 5 ingredients by restaurant coverage

  1. Pickles10 / 11
  2. Caramelised onion7 / 11
  3. Cheddar7 / 11
  4. Tomato6 / 11
  5. Crispy onion6 / 11

In this sample, pickles appear in the burger menus of 10 of the 11 restaurants.

Source: Avcılar burger category study · delivery-platform listings, read by hand · a sample, not the whole market

02PRODUCT & INGREDIENT INTELLIGENCE

See what products are made of

Explore which ingredients recur across protein bar products, how formulations differ, and how nutrition profiles vary across the analysed sample.

15
analysed products
6
brands in the sample

15-product pilot sample. Compiled from publicly available online product information; not verified from the packaging, and ingredient lists may be partial. Four products' values were converted from serving size to 100 g. Not a market census. Data sources →

Restaurant menus · packaged products · ingredientsFrom menus to products, and from products to ingredients, read the food market through a shared data language.

Rectangular chocolate-coated bars with nut and coconut toppings on baking parchment (editorial photograph).

Editorial image · not an analysis finding · Photo: Polina Tankilevitch / Pexels

Most frequently observed ingredients

Most frequently observed ingredients in the 15-product sample

Product coverage, based on the recorded ingredient text

  1. Date8 / 15 products
  2. Milk protein concentrate8 / 15 products
  3. Whey protein concentrate8 / 15 products
  4. Peanut paste7 / 15 products
  5. Cocoa butter6 / 15 products
  6. Maltitol6 / 15 products
  7. Hydrolysed collagen5 / 15 products

Product coverage = the number of analysed products containing the ingredient. Not usage quantity, market share or brand count.

Nutrition dimensions · per 100 g

Median

Protein

g

Fibre

g

Sugars

g

Energy

kcal

Range and median across the 15 products; four products' values are converted from serving size to 100 g. Each metric is read on its own scale, with no combined score.

03The problem

The market is big. The information is scattered.

The answers sit on menus, product pages, shelves and catalogue lists. One question means stitching many sources together by hand.

A professional kitchen with stainless-steel cabinets, hanging ladles and stacked plates.

01Selling

Who can I sell my product to?

  • In which restaurants or segments could my product make sense?
  • Which menus and products does an ingredient appear in?
Raw food ingredients in bulk before processing.

02Sourcing

Who can I source from for my product?

  • Who makes the ingredient my product is built on?
  • Which suppliers exist in Türkiye and abroad?
  • Can I reach a catalogue, technical product data, MOQ or pricing?

03The market

How is the market taking shape?

  • Who actually makes the product?
  • Which claims do competing products use?
  • How is the category taking shape on the shelf?

Swipe to see the other questions

The answers exist. They are not in one place.

04Where the data comes from

We read the market from connected, real signals, not from a single source

From menus to shelves, from products to manufacturers, we bring scattered food data together in one intelligence network.

We separate what we know, what we infer, and what is not yet known.

Every claim retains its evidence basis.

  1. 01

    Restaurant and menu

    What is offered, and where?

  2. 02

    Product and SKU

    What do brands bring to market?

  3. 03

    Manufacturer

    Who actually makes the product?

  4. 04

    Shelf / retail

    Category, assortment, price and claim signals, where the record has them.

  5. 05

    Research / evidence

    Observed data, inference and sector knowledge stay separate.

Research coverage

2,040
Restaurant listings
93,479
Menu items analyzed
11
Cities covered
221
Ingredient & Product Concepts

Food Intelligence menu research corpus · 93,479 menu items across 11 cities · snapshot 10 Sep 2026

Evidence classes

  • 01Observed

    Seen directly in the source or dataset.

  • 02Sectoral Knowledge

    Context supported by industry knowledge.

  • 03Inferred

    An interpretation derived from the available evidence.

  • 04Potential

    A possible commercial fit or opportunity signal. Not buyer intent, a quote request or an order.

Data processing flowObservationStructuringMatchingInferenceCommercial reading

05The core chain

One chain, from restaurant to opportunity

  1. A professional kitchen with stainless-steel cabinets, hanging ladles and stacked plates.

    01

    Restaurant

    Where is the market activity?

  2. 02

    Menu

    What is on offer?

  3. Raw food ingredients in bulk before processing.

    03

    Ingredient

    Which ingredients are used?

  4. 04

    Manufacturer / product

    Who could supply it?

  5. 05

    Opportunity

    Where is the commercial connection?

Who can sell what to whom, and why?

Appearing on a menu does not mean a purchasing need. A potential match is not a confirmed buyer.

06Working views

One data network, different commercial questions

Not four products. The same connected data, read with the question your job asks.

Commercial questions

  1. 01Selling

    Who can I sell my product to?

  2. 02Sourcing

    Who can I source from for my product?

  3. 03The market

    How is the category taking shape?

  4. 04Research

    Which signals point to new opportunities?

Working views

  • Manufacturer / supplier

    Working view: Sell and source

    • Find target restaurants
    • See where a product is used
    • Discover suitable segments
    • Compare your range with observed market patterns

    Sourcing

    • Who makes the ingredient?Product direction
    • Is there an alternative abroad?Pilot
    • Is there a catalogue?Product direction
    • Is there a technical sheet?Product direction
    • Is there an MOQ?Product direction
    • Is there price information?Product direction

    Catalogue, MOQ and price information is not on every record. It is shown only where the source has it; what is missing stays unknown.

  • Restaurant / procurement

    Working view: Procurement

    • Search suppliers
    • Compare products and SKUs
    • See alternative products
    • Research manufacturers
    • Build a shortlist

  • Brand / category

    Working view: Category

    • Follow competing products
    • Read the claim structure
    • See product trends
    • Check shelf visibility
    • Compare category and segments

  • Researcher / analyst

    Working view: Analysis

    • Restaurant, menu and ingredient analysis
    • Manufacturer analysis
    • Market Insights
    • Evidence and provenance
    • Reports and export, where supported

The views open in the Dashboard in stages. Coverage varies by record and source, and no view presents information as present when the record does not have it.

07Product preview

The working surface in the Dashboard

The Dashboard's record logic, on real research.

DashboardPreview
  • Category: Burger
  • Area: Avcılar
  • Source: Research

Avcılar · 11 burger restaurants · 199 menu items read

IngredientRestaurants
Pickles10 / 11
Cheddar7 / 11
Caramelised onion7 / 11

The fields of a restaurant record

  • Restaurant
  • Cuisine
  • Service model
  • Menu item count
  • Ingredient
  • Evidence class

The table shows summary counts only; individual restaurants are not listed here.

Preview. The Dashboard is not yet connected to this deployment.

Go to the Dashboard

08Featured intelligence

Signature research

All research

09Mirpua Intelligence + AI

Ask Food Intelligence

Product direction

Months of structured data, evidence, identity, menu, ingredient, product and manufacturer work will one day be reachable in plain language. That capability is not live today; what follows is a description of where we are heading.

  1. 01Question
  2. 02Mirpua
  3. 03Data
  4. 04Evidence
  5. 05Answer
  6. 06Dashboard

Example question

Show cheddar use in burger restaurants in Ankara.

Not working yet.

The principle

The AI is not the source of truth. The database and the backend are.

The AI understands the question, calls the right tool, brings back an evidence-backed result, explains it and hands off to the Dashboard. It never has unrestricted, arbitrary SQL access to the database; it works only through permissioned tools and APIs.

Available today

  • The central search and its handoff to the Dashboard
  • Market Insights: published research
  • The restaurant, ingredient, retail and manufacturer areas of analysis
  • Evidence classes and provenance

AI-assisted, product direction

  • Find Italian restaurants in Istanbul that use mozzarella.
  • Which restaurant segments could this manufacturer's range overlap with?
  • Which brands and claims exist in the protein bar category?
+3
  • Show the manufacturers of this ingredient in Türkiye and abroad.
  • Compare five competing products by content and claims.
  • What market signals exist for this product?
How the AI is meant to behave
  1. 01Understands the intent
  2. 02Extracts the entities, geography and filters
  3. 03Calls controlled Food Intelligence tools or APIs
  4. 04Retrieves structured results
  5. 05Preserves evidence and provenance
  6. 06Explains the result clearly
  7. 07Hands off to the relevant Dashboard context
The future architecture
  1. 01User
  2. 02Plain-language question
  3. 03Mirpua AI
  4. 04Governed API / read model
  5. 05Food Intelligence data
  6. 06Evidence-backed answer
  7. 07Dashboard action

10Membership and access

Membership options for food market analysis

Start with open market evidence; then join, go deeper with Pro, or take a single report. Discover is open today, the rest are not open yet; tell us which one you need.

  1. 01

    Open today

    Discover

    Public, no account needed

    • Published research
    • Restaurant, ingredient, retail and manufacturer analysis areas
    • Evidence classes and source trail
    See the research

  2. 02

    Soon

    Join

    Standard membershipSave, follow, a selected workspace

    Planned scope

    • Saving and following
    • Selected workspace features
    • Limited search and results
    Ask about membership

  3. 03

    Soon

    Pro

    Pro membershipDeep analysis, comparison, export

    Planned scope

    • Deeper results
    • Advanced filters
    • Comparison and export
    • Saved work
    • Premium research
    • AI-assisted analysis
    Explore Pro

  4. 04

    On request

    Buy a report

    Report purchaseOne report, without Pro

    Planned scope

    • Access to a specific report
    • No membership needed
    • With its method and scope
    Request report access

Swipe to see the other options

Scope, limits and prices have not been decided. Today no access needs an account or a payment.

The report purchase flow

  1. Report
  2. Price
  3. Payment
  4. Verification
  5. Entitlement
  6. Access

Soon. Access will open only through an entitlement the server verifies; a parameter in the address bar or browser storage never opens anything.

An enterprise solution is not a membership tier; it is a separate conversation for specific needs.

  • Commercial exploration
  • Market intelligence
  • Custom research
Request an enterprise solution

11Frequently asked

Questions before you start

The answers are written for the situation today. What is unknown is left unknown.

  • What is Food Intelligence?

    A layer of food-market analysis that connects restaurant menus, products, ingredients and manufacturers, separated by evidence class. The aim is to put scattered data into a form that can answer a commercial question.

  • Where does the data come from?

    From public restaurant and menu listings, product and retail observations, manufacturer information and structured research studies. Every published figure has its source on record.

  • Does Mirpua know what a restaurant actually buys?

    No. An ingredient seen on a menu is not a purchase record or a current need. We do not offer information on purchase volume or intent.

  • How can I find a manufacturer or supplier?

    The manufacturer area of analysis and the pilot work in the Dashboard are being prepared for this. We do not offer a verified supplier directory; candidates whose identity is unresolved are not shown as verified manufacturers.

  • Are price, catalogue, MOQ and technical product data on every record?

    No. This information is shown only where the source has it; what is missing stays unknown. We do not claim price, catalogue or MOQ coverage across all records.

  • What will separate Standard from Pro?

    Standard membership is planned as entry-level access and Pro as deeper, recurring access. Scope, limits and prices have not been decided and neither is open today; you can write to us for information.

  • Can I buy a report without Pro?

    Yes, that is the design: a report will be available on its own, without a membership. The payment flow is not open yet; today you can request report access. Access will open only through an entitlement the server verifies.

  • What data will AI answers be based on?

    The AI capability is not live yet. By design it will query governed Food Intelligence data only through permissioned tools and APIs, and keep evidence and provenance in the answer. It will have no free SQL access to the database.

See all questions (6)
  • How are restaurant and menu data built?

    Menus are read from public listings with a fidelity-to-source rule. Ingredients are matched to menu items with a rule-based dictionary. In the Avcılar burger study the listings were extracted by hand.

  • What is the difference between observed and inferred information?

    Observed is what the source shows directly, such as a menu naming cheddar. Inferred is a relationship derived from what was observed. The two are never given the same label.

  • How is an opportunity identified?

    An opportunity is a connection between observed data, for example an ingredient appearing on many menus. It is a potential match, not a confirmed buyer or an existing commercial relationship. We do not offer an automated match score.

  • Which cities and countries are covered?

    The published research snapshot covers 11 cities. The Avcılar burger study covers a single district. Coverage outside Türkiye is at pilot stage and varies by record.

  • Can I see examples of products and manufacturers abroad?

    The pilot work in the Dashboard includes candidate manufacturers from abroad for review. They are unverified candidates and are not listed by company name on the public site.

  • What is the difference between the website and the Dashboard?

    The website explains Food Intelligence, publishes research and provides access. The Dashboard is where you work with the data. The Dashboard is not yet connected to this deployment; until it is, a search is passed on but not run.

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