What we solve
Marine vision is easy to describe and hard to picture. So rather than describe it, we built it. Every panel below is a working demonstration you can drag, tap and re-run — drawn live in your browser, with no video files and nothing sent anywhere.
TASK 01 · Interactive
A long-range camera spends most of its pixels on empty sea. The contact you actually care about lands on a few dozen of them. Super-resolution reconstructs detail from that handful of pixels — enough to tell a fishing skiff from a fast attack craft at a range where the raw frame shows only a smudge. It is what turns detection range into identification range, without buying a longer lens.
TASK 02 · Interactive
At 0.02 lux the sensor is amplifying its own electrical noise as hard as it amplifies the scene. Push the gain and the frame fills with grain that a detector will happily report as contacts. Our denoising runs before anything else in the pipeline, combining information across consecutive frames and across the spatial neighbourhood, so the detector sees signal rather than sensor.
TASK 03 · Interactive
The events that matter most are the ones you have least footage of: a man overboard in sea state 6, a dark skiff closing at night in rain. You cannot schedule those to happen in front of a camera. We generate them — whole labelled frames across light, sea state, visibility and rain — so a model meets the hard case in training rather than for the first time on watch.
TASK 04 · Interactive
Detection is where every operational argument actually happens, and the argument is always about the threshold. Set it high and the watch stops trusting the alarms because there are too many. Set it low and you miss the thing you installed the system for. Move the slider below and you can see the trade being made — this is the conversation we have with every customer before a single box is mounted.
TASK 05 · Interactive
A box says roughly where something is. A mask says exactly which pixels are hull, which are wake, which are sea and which are the coastline behind. That precision is what lets us measure waterline fouling, judge whether a contact is aground or afloat, find the horizon in a rolling frame, and hand a clean sea/sky boundary to the tracker.
TASK 06 · Interactive
This is the task the company exists for. AIS is a cooperative system: it tells you about vessels that choose to be told about. The traffic that fills Indian coastal waters — country craft, gillnetters, dhows, anything that has switched its transponder off — is electronically silent, and radar loses it in sea clutter because it is low, small and often wooden. Switch the picture below from AIS to fused vision and count what appears.
TASK 07 · Interactive
Perception is only worth the money if it changes a decision. Our planner takes the chart, the depth contours, the restricted areas and the weather, and produces a passage that respects all of them — then re-plans when the picture changes. Note what happens when you tighten every constraint at once: it reports that no safe route exists rather than quietly routing you across a shoal.
TASK 08 · Interactive
India's deep-sea mineral programme covers an allotted area in the Central Indian Ocean Basin that no survey team can inspect frame by frame. An AUV carrying multispectral and acoustic sensors returns tens of thousands of seabed images per sortie. We score every cell for anomaly, rank the blocks and hand geologists a shortlist — so expensive ship time is spent confirming candidates, not finding them.
TASK 09 · Interactive
Every port expansion and offshore project in India needs a biodiversity baseline, and protected species carry hard legal consequences under the Wildlife Protection Act. Reviewing ROV footage by hand costs roughly forty minutes per hour of video. The same detection and classification stack that finds vessels finds fauna, flags the protected ones, and produces a defensible count with the frame reference attached.
How to read these. Each panel is an honest illustration of the task and the trade-offs it involves — not a recording of our production models. The imagery is generated procedurally in your browser, so the scenes are synthetic and the figures in the readouts are representative rather than measured. Real performance is established at trials, on your platform, against acceptance criteria we agree in writing beforehand. We would rather show you the shape of the problem here and the actual numbers on the water.
One stack
These are not nine products. Restoration, detection, segmentation and tracking are stages of a single pipeline, and the same pipeline runs whether the camera is on a mast, on an ROV or on a gantry over a dry dock. That is why a shipyard inspection tool and a coastal surveillance system share a codebase: a weld seam and a wake are both edges, and a nodule field and a fishing fleet are both anomalies against a noisy background.
It is also why we can take on an unusual task quickly. If your problem is a marine image with something in it worth finding, the honest answer is usually that we already have most of the stack and need to train the last layer.
Start a conversation
Send us your operating profile and we will come back with a sensor plan, an integration route and a trials schedule — usually within two working days.