DIG-IN · The Data Layer of Food Services
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Restaurant intelligence · 12+ markets

The Data Layer of Food Services.

One verified dataset of every restaurant, café and bar on the map, for FMCG brands, technology platforms and restaurants.

Scope a pilot →See the dataDownload the deck (PDF)
Restaurant bar counter with an espresso machine, shelves of spirits and glasses, and a brand sign above
Photo: Haberdoedas / Unsplash
1.8M+venues analysed in 12+ markets
150M+data points, updated continuously
100K+images read by our AI every day
50+sources unified per venue

01 · The problem

Food services run on broken data.

Venues don’t provide data. They leak it: menus, photos, reviews, maps, bookings. Brands, platforms and cities all decide on partial, stale views of the same street.

FragmentedDozens of sources, none complete.
InaccurateHours, menus and prices go stale.
LimitedVenues with no website go unseen.
ProtectedThe best signals sit in silos.
68%

of operators have no centralized data at all. There is no Bloomberg for food services. We’re building it.

Sources: Mordor Intelligence 2025, Statista 2024, Grand View Research 2024

02 · How it’s made

Discover. See. Enrich. Verify.

Four proprietary engines turn the map into one 360° record per venue.

01

Discover

Grid-scan every venue across the map, including the ones with no website.

  • Web crawling, 100+ sources daily
  • Geo-mapping
02

See

Computer vision reads every photo: signs, brands, equipment, seating.

  • 100K+ images daily
  • Brand & object detection
03

Enrich

Menus, prices, reviews and platform presence, all structured.

  • OCR + NLP menu extraction
  • LLM sentiment & synthesis
04

Verify

One venue becomes one record, checked before it ships.

  • Entity resolution
  • Daily change detection

Many sources. One verified record.

Online sources scanned monthly and reconciled, physical audits on a regular cycle.

Sources · online + on site

Maps & reviewsRatings, reviews
MenusDishes, prices
Delivery & bookingApps, fees, tables
WebsitesHours, links, info
Social mediaPosts, followers
Guest photosBrands, room, kit
TrafficFootfall, peak hours
Field auditsPhysical, on site

How

Scanned every monthChange detected daily

Read by AIText, menus and photos

Audited on siteRegular presence checks

Analysed & extrapolatedGaps filled, trends modelled

Per venue1 record

253 data points

  • Traffic
  • Menus & prices
  • Online presence
  • Social media
  • Photos
  • Physical presence

The reveal

We see what others can’t.

One guest photo, read by our AI.

12Insights
7Brands
1Photo
Restaurant interior in Lisbon. DIG-IN marks seven brands (Johnnie Walker, Sagres, Sagres Bohemia, Absolut, Lipton Ice Tea, Paladin, Hellmann’s) and operational signals: TV, POS, open kitchen, tiled mural and 16 tables of two.
1Johnnie Walker
2Sagres Bohemia
3Lipton Ice Tea
4Sagres · uniform
5Absolut
6Paladin · Hellmann’s
7Sagres · 5 taps
8TV · media space
9Mural · selfie spot
10Open kitchen
11POS
1216 tables of 2
Brand detectedOperational signal100K+ photos read a day

03 · The data

Os Courenses, Alvalade. Since 1992.

A real read of a Minho house with 122 seats, against the 21 food & drink venues our scan found within 500 m.

Reputation4.5★2,706 Google reviews · 93.5% at 4–5★ · Tripadvisor 4.2 (325), #623 of 6,643 in Lisbon
Share of voice#2 of 21By reviews within 500 m, behind Tico Tico (5,172) · #3 of 13 on rating among venues with 300+ reviews
Peak demandWed–Sat, 1 pmThe busiest it gets, waits up to 15 min · Mon–Tue peak at 8 pm · closed Sunday
SignatureCozidoTop topic in Google reviews (35 mentions) · served Thursday and Saturday lunch
Menu economics€17.56Average of 36 mains · same 23 dishes up about 18% since 2022 · café €1.30, imperial €1.50
ChannelsPhone onlyNo booking channel or delivery app found · the old website domain now redirects to a spam site

Sources: DIG-IN Google Maps scan, Tripadvisor, printed menu of 18 Mar 2026 and 17 Nov 2022 · read 25 Oct 2026 · footfall for Alvalade to follow

253 data points per venue, in five lenses.

Five lenses, 21 categories. Clients switch categories on or off, exactly as in step 2 of the pilot request. The foundation always comes with it.

Why DIG-IN

Accessible and updated dataset vs traditional consulting

How we differ from traditional data consultancies.

 Traditional consultanciesDIG-IN
CoverageA sample, extrapolatedThe full universe of venues
FreshnessAnnual studiesReconciled every month
Price & useHigh-ticket strategic consultingAccessible, for action now

From €1 per establishment analysed · start with one zone

04 · Who it’s for

Three worlds, one dataset.

Brands, platforms and restaurants compete on the same street with different blind spots. Choose yours.

05 · The product

One dataset. Three ways in.

The same verified record, delivered the way your team works. Also as raw JSON / GeoJSON, with real-time alerts on openings, closures and changes.

GET /venues/os-courenses { "rating": 4.5, "reviews": 2706, "delivery": [], "since": 1992 }

API

A live venue feed into your CRM, product or BI stack.

  • REST
  • JSON / GeoJSON
  • Webhooks

Dashboard

Self-serve maps, rankings and alerts for sales, marketing and strategy.

  • Maps
  • Benchmarks
  • Alerts

Report

Custom or white-label studies, ready to present or hand to your clients.

  • PDF
  • White-label
  • Quarterly

06 · Proof

Trusted where getting it wrong is expensive.

500+clients across brands, restaurants and platforms
85%+client retention rate
12+markets across Europe and Brazil
Brands, hospitality & institutional entities

Coca-Cola Europacific Partners · Heineken · Sogrape · Vila Galé · Turismo de Portugal · Gramado City Hall

About DIG-IN

Profitable, and scaling across Europe.

2021

MBO

Founded through the management buyout of a global platform.

THEN

Portugal

The full universe of our home market.

NEXT

Spain & Germany

First expansion beyond Portugal.

TODAY

Europe & Brazil

12+ markets across Europe and Brazil.

15people
7+years in food tech, on average
2×revenue, doubling
3×EBITDA, tripling
At breakeven

Two rounds raised, now preparing our Series A. We raise only to grow further and become the number one player.

07 · Team & how we work

Built by people who’ve run food tech.

Nuno Fernandes
CEONuno Fernandes

Ex-Zomato, IKEA. Restaurant tech, data and sales.

Steven Murray
CMOSteven Murray

Ex-Zomato, Webfluential, Swish. Strategy and expansion.

Francisco Soares
CTOFrancisco Soares

Ex-Outdare, eTnos. Restaurant, logistics and data tech.

From €1per establishment analysed · usage-based SaaS · start with one zone

08 · Request a pilot

Scope a pilot in three steps.

Pick a city and drop a zone, choose the data points you need, and send it to us. We come back within 48 hours with the venue count, a sample and a proposal.

Open the pilot request on its own page ↗ · to share with your team

I’m scoping this for
Drag to move · click to place the zone
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