We’re excited that the Telegraph ran a story about Seldon today! This is the first mention of Seldon in the national press since we came our of stealth last month.
“Other companies only offer black box solutions,” he said. “They hide all the technology that’s happening underneath the surface so you’re forced to keep pushing your data into these systems.”
Seldon is building a “glass-walled platform” in order to accelerate the development of its system. Black box versions take much longer to build; with open-source, hundreds of developers help by creating “add-ons” – unique pieces of code that make the system relevant to their business.
Read the full story by Rebecca Burn-Callander.
Thanks to the organisers of City Meets Tech for selecting Seldon to pitch last week at Level39 in Canary Wharf. It’s a fantastic event that helps to bridge the gap between start-ups and people in the finance world who want to engage with startups in various capacities.
Here’s an extract:
So why is Seldon different? Billion-dollar companies are hooking their customers into monolithic proprietary black box platforms. And they want to break free. This is why Seldon is going open source…
The thing is: modern organisations want more control and are investing in data science right now. We’re shipping an enterprise-grade platform based on three years and a couple of million pounds R&D and building an ecosystem around it. We’re unleashing a glass wall data science stack and it is a game changer.
You can read the full pitch on Medium – apparently it takes 3 minutes!
Seldon @ City Meets Tech
In a few days, we will be shipping a virtual machine with Seldon’s infrastructure preconfigured and ready to switch on for testing with your data.
Meanwhile here are some recent updates:
To be the first to get access to the closed alpha and stay in touch with project developments, please sign up for free here.
We are building Seldon to make life easier for data scientists and developers who want to harness the power of predictive analytics. We bring with us a 3 year heritage of R&D associated with providing content personalisation at scale with some of the world’s leading brands. Seldon is built to give in-house data science teams more flexibility to customise algorithms and integrate the predictive outputs with their internal systems.
The core use case in these initial releases will be to provide personalised experiences through content and product recommendations. Our roadmap prioritisation of these will be heavily influenced by your demand. So we would love to hear how you want to use Seldon as a platform now and in the future.
This month we be shipping our closed alpha (version 0.1) to . This first release will be a virtual machine with all of Seldon’s infrastructure preconfigured and ready to switch on for testing. It will include a movie recommender demo app that uses the MovieLens dataset, and a Swagger API explorer.
This initial release is for testing purposes only. It’s a single VM that contains all of Seldon’s infrastructure. We are planning to ship production-ready Docker containers around March.
Here’s a quick heads up of what to expect in the following releases. We reserve the right to tweak this, and will keep you posted of any changes:
- Version 0.1: VM including MovieLens demo and API explorer, which can adapt to your data.
- Version 0.2: Docker containers with orchestration. Consul for elegant configuration. Grafana stats.
- Version 0.3: Data config API and GUI. Algorithm optimisation via multi-armed bandit.
- Version 0.4: 1st source code release. Pluggable architecture so that you can integrate your algorithms with Seldon using a common API.
The won’t be publicly released, so please sign up for free here for the closed beta to get early access.
While we are just about to make the first releases of Seldon’s open platform, some of the world’s largest companies are already using our API to provide predictive functionality such as content recommendations at scale. If you want to get started quickly with a project using Seldon Cloud, then please let us know.