Decide with computer vision
Sena Computer Vision runs AI image recognition on geo-verified photos, so each decision rests on the evidence.
- 190+ countries
- 5M+ consumer network
- 250+ integrations
geo ✓
geo ✓
geo ✓
screenSite 14 · 2 Sep · 09:14Site records arrive late
Many decisions depend on what sits at a real place: a building, a charging station, a hotel, a campus. The decision needs that place as it is today.
Checks wait on schedules
A check needs a person at the site, so headcount caps the number of checks.
Estimates hide their method
An estimate comes from records that predate the question, and its method stays sealed.
The reading ages fast
The check finishes after the site has moved on, and the decision often lands first.
Computer vision sees the real-world
Computer vision is the ability to read an image and name what is in it. Computer vision turns a single photo into answers a team can act on, from a roof's condition to a working charger to a hotel's guest areas.
It reads any object
Sena's AI image recognition reads any object in an image, based on the team's question. An unusual object comes through when the question asks for it.
- Signs, doors, chargers, and vehicles all run through one recognition system
- A checklist returns its own list, and Sena returns what the question asks for
It names what it found
The model names each object the question asks about.
- Each name links back to its photo
- Tuned categories return the most detail
It records what it named
Recording starts once the objects have names. Depending on the question, the record is a count, a price on display, a condition, or whether something is there at all.
- Counts show presence and coverage
- A displayed price comes straight off the photo
- An absent item records as absent
roofwindowmailboxAddress A · Miami · 2 SepWhat Sena Computer Vision does
Sena is a Decision AI with access to real-world data. Its computer vision solutions run on an object-agnostic recognition system, so capture and checks work the same way across industries. Extraction runs deepest where Sena has tuned its models.
Capture works across industries
09:14 · geo ✓Capture on request.
Sena orchestrates capture through a 5M+ consumer network across 190+ countries. Each photo arrives geo-verified, with its date and location.
Each image passes QA first.
Sena checks each image and declines captures that are outdated or below standard. Automatic checks and human review both sit in the flow.
screenplug09:14Fields from any object.
Sena turns what a photo shows into fields. The question sets which fields come back.
Every field traces back.
Each field opens onto its source photo, with the date and location beside it.
CPG extraction runs deepest
Consumer packaged goods (CPG) carry the deepest extraction today, because that is where Sena has tuned its models.
packStore 0417Category-tuned models.
Sena fine-tunes its models for specific product categories, so a model that knows the category reads an irregular pack. Tuned categories return the deepest read, and each project names the categories it covers.
Exact SKU matching.
Sena matches product photos to an exact SKU in tuned categories, so one product keeps one name.
Store 0417Outlet metrics from the photo.
Sena reads price, share of space, new listings, and availability from the image. It names the outlets where a product gains share and where it loses it.
Money won or lost.
Sena frames the result as money won or lost, in a board-ready deck in PDF and PowerPoint.
Sync back to systems.
Sena writes the fields into ERP, CRM, and other systems across 250+ integrations.
- Charger 2
- Working
- Screen
- 3.57 kW
- Photo
- linked ↗
One photo becomes answers
One photo goes in and comes back as a row of fields. Each field links to its photo, so the meeting settles the call on the evidence.
12Store 0417 · 2 Sep · 18:42What the photos answer
Sena's computer vision solutions deliver more than a photo. Each capture carries a geo-verified location and a date, so every field shows what sits at the site, where it sits, and the source behind it.
roof · intactAddress A · 2 Sep
missing shinglesAddress B · 2 SepPricing each risk on condition
Computer vision in insurance lets underwriters price each risk on the building's recorded condition, address by address, with a geo-verified photo behind every field.
bare wall, no lightsYour hotel · 2 SepheadboardlightsRival · London · 2 SepScoping a renovation locally
Renovation budgets match what guests find at each competing hotel, with a date and location on every element.
#1 Site 14Working ✓
#2 Site 9Partly
#3 Site 22Broken ✕Choosing sites drivers use
Charger sites rank on whether each charger works and what drivers find in the last thirty meters, station by station.
0417 ✓0533 ✓
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0640 ✕Verified store coverage
Reported store coverage sits beside verified presence, outlet by outlet and SKU by SKU, with the photo behind each one.
Every field shows its photo
Three checks stand between a wrong field and a decision. Two run inside Sena. The third runs in the meeting, where the photo sits behind every figure.
chargercar · out2 Sep · 09:14
- 01
Before a photo counts.
QA screens each capture against the standard.
- 02
While Sena names objects.
Anything outside the question drops out, so an unrelated object stays out of the count.
- 03
After the fields return.
Every field opens onto its photo, so a reviewer can check the reading against the evidence.
Three questions come next
Consumer Activity
What people chose, where, and what came next, captured when a question needs it.
Open Consumer Activity Sena moduleConnect
How uploaded files and the photos answer one question together.
Open Connect Sena moduleIntegrations
Which systems Sena connects to, with Salesforce and HubSpot among the 250+ integrations.
Open IntegrationsStart with one question
The demo builds a scenario from the team's industry, country, and department, then runs Sena on it.
Looking for an enterprise solution? Let's talk.
Questions teams ask before demos
01What is computer vision, and what is it used for?
Computer vision reads images and returns structured data. Teams use it to check a real-world site: a building's condition, whether a charger works, what a hotel delivers, or a displayed price. Sena runs it on geo-verified photos, so every field arrives with a date, a location, and the image behind it.
02How does image recognition work?
Image recognition finds the objects in a photo and names each one. Sena returns the items a question asks for as fields, with the date, the location, and a link back to the photo.
03Can AI identify what is in a photo?
AI image recognition can identify and name the objects in a photo. The hard part is a photo from a real site, where light varies, objects overlap, and signs sit at angles. Sena checks each capture before it counts, and fine-tunes its models to a category that needs more depth.
04Does Sena Computer Vision work beyond CPG?
Sena's computer vision solutions capture, check, and return fields the same way across industries, from insurance and hospitality to EV charging. Extraction runs deepest in consumer packaged goods (CPG) today, where Sena fine-tunes its models for specific product categories. Sena matches products in the tuned categories to an exact SKU. Other categories return a general read, and tuning another category runs as a scoped project.
05When does capture run?
Capture runs on request. A team asks a question, the capture runs against it, and the photos come back for that question. A fresh set runs when the team asks again.
06Where do the photos come from?
Sena orchestrates capture through a 5M+ consumer network across 190+ countries, and each capture answers the team's question.
07What happens to a photo that is too dark or blurred?
Automatic checks and human review decline a dark or blurred photo before it becomes a field.
08How is this different from OCR?
OCR returns the text in an image, and Sena returns the objects in it. Sena names each object and returns fields with the image attached, and text in the frame is one input among several.
09Can Sena work with photos a team already holds?
Sena works with photos a team already holds as a scoped project, because Sena tunes the model to the category first. That tuning takes engineering time.
10How does a team check a number?
Every field opens onto the photo it came from. The image carries its date and location, so a reviewer can confirm or correct a reading against the evidence.