Greywing (YC W21) – Automated ship operations focused on crew

Hey HN! We're Nick & Hrishi, founders of Greywing (https://grey-wing.com). Greywing is software that optimizes operating a vessel in the high seas, focused on seafarers and crew changes. We take the information you (a ship manager) have about a vessel (route, plans, crew composition), plus information externally available (piracy, flights, fuel costs), and tell you where to route your vessel and what the best choices are for the crew, and the purchases you're making.

Maritime is a surprisingly decentralized industry, even in 2021. Large vessels (container ships, gas tankers) are complex entities, with a single vessel operated simultaneously by multiple companies (ship managers, charterers, technical managers, crew managers) domiciled in different countries. These companies manage flights, fuel purchases and consumption, cargo and charters, crew welfare, and a hundred other things that go into completing a single trip. Once a trip is done, most of these things change before the next voyage.

There is often no central source of truth for any of this data, let alone systems that connect one to the other. Parties involved—travel managers, port agents, vessel captains—communicate over email, with no clear idea of what the other hand is doing. This means that a single crew change can take up to a week to decide, with no clear idea if it was the optimal outcome. Crew changes had been getting more complex for a while, with increasing budgets and slowdowns, but Covid turned this into a humanitarian crisis [1], with over 800,000 seafarers stuck at sea or unable to work for more than a year.

Vessels are often short-staffed and overworked due to lack of space, so crew operate on three to six month contracts and spend about the same amount of time on land. As crew rotate, you have an exchange of oncoming crew (onsigners) with outgoing crew (offsigners). Crew managers try to do this with minimal disruption to the route, while making sure the crew don’t overstay contracts and the vessel consumes fewer resources (fuel, flights, etc). Crew managers work with imperfect information under time pressure, and the wrong decision (or no decision) can cost thousands of dollars and have strong impacts. Tired crew that haven’t been home in a long time make mistakes (and these mistakes have increased in recent past), but deviating too far from cargo requirements will take a vessel off-hire.

A bit about us: Nick is a maritime native, having worked on vessels and done many of the jobs we serve today, all the way up to running a maritime startup for 10 years. I (Hrishi) spent most of my career in a diverse set of industries, from fast-moving ones like crypto and robotics to the other end of that spectrum with reinsurance and semiconductor ball bonders. We met in Singapore after Nick uprooted his life to start something new. Having seen the effects of 2008 on the maritime industry, we felt that we could build software that increased the resiliency of shipping to systemic shocks. We started in 2019, and as it turns out a pretty big shock was around the corner. Since then, our goal has been to solve problems with human-augmentation, by automating as much as possible and then getting out of the way of the people who operate a vessel.

Having started in maritime security, one of our first successes was in building a real-time dataset for piracy around the world. Incidents are usually reported to local authorities, and published in pdf bulletins on separate sites. The next step was turning this into structured data, and connecting it to an internal database of ports, as well as a routing tool that we had to build from scratch. By the time we focused on crew and the effects of Covid, we had most of the tools we needed to tackle the issue, and it became a job of incrementally adding connections to our data around airports, flight prices, agency costs, fuel consumption, so on.

We combine this information to provide immediate guidance on where a vessel should go, and what actions it should take along the way. We use the data at our disposal, both public and private, to optimize for the best route for the vessel so it can change crew, while burning the least fuel, spending less on flights, and where immigration and port restrictions are open [2]. It's basically n-dimensional pathfinding, once you’ve got clean relational data. We do this through our intelligence tool CRY4 (named after [3]), and to date we estimate that we’ve saved our customers over 20,000 USD per vessel per year.

So far, we've automated over 50,000 crew changes and are now monitoring more than a thousand vessels, while saving our customers more than 20,000 USD per vessel per year. We've had users turn to Greywing to evacuate critically wounded crew as fast as possible, organize nation-wide exercises to conduct charter flights to alleviate some of the still-building pressure around ports, among other things we've written about [4]. We're humbled by the effect software has had on this problem, and some days it's still surreal to think of code that didn't exist 6 months ago making a difference in maintaining global trade networks.

We'd love your feedback on what we've built. We've just expanded to a team of three, and are hiring frontend developers. Our priorities are UX and algorithms - solve problems with good software, and build interfaces that make those solutions useful. We’d love to hear any feedback you have, and are happy to answer any questions!

[1] https://hrishioa.github.io/one-million-mariners/

[2] https://blog.grey-wing.com/why-deep-tech-is-the-future-of-ma...

[3] https://www.pnas.org/content/116/39/19449

[4] https://blog.grey-wing.com/a-vessel-manager-us-2-5-million-7...



Get Top 5 Posts of the Week



best of all time best of today best of yesterday best of this week best of this month best of last month best of this year best of 2020 best of 2019 yc s21 yc w21 yc s20 yc w20 yc s19 yc w19 yc s18 yc w18 yc all-time 3d algorithms animation android [ai] artificial-intelligence api augmented-reality big data bitcoin blockchain book bootstrap bot css c chart chess chrome extension cli command line compiler crypto covid-19 cryptography data deep learning elexir ether excel framework game git go html ios iphone java js javascript jobs kubernetes learn linux lisp mac machine-learning most successful neural net nft node optimisation parser performance privacy python raspberry pi react retro review my ruby rust saas scraper security sql tensor flow terminal travel virtual reality visualisation vue windows young talents


andrey azimov by Andrey Azimov