small correction - we are not an outsourced providers - about 40-60% of the building process is machine operated - the rest is human - and those humans come from our network of devshops - but we don't outsource it to them - we pick the individual engineers we want to work on the problem basis our rating system. (https://snag.gy/XgJfny.jpg) will show you what experience our Capacity Partners see.
Here is where we use AI/Expert/Heuristics (pls note I am not the AI expert but trying to be as transparent as possible)
- Pricing is a Supervised Learning Model.
- Custom Features are a Convolutional Neural Net + NLP.
- Resource Allocation (we tap into capacity of other dev shops) is an OR/ML combination.
- Sequencing of what to do is an ML/SL problem.
- Complexity is a Clustering Problem.
- Grading Devs is a Static Code Analysis (industry standard) + NLP Problem.
- Quality Early Warning is a Supervised Learning + Heuristics (we identify early potential problems based on a developer + feature set history analysis)
- Templates being updated based on features being added by onward customers.
---> Building Blocks
- Features are one or many building blocks
- They communicate through an ESB thats allows a smarter way of messaging between individual areas.
- The ESB allows us to "plug n play" -> today it still needs human stitching but that a scale problem we are looking to fix.
We are step 5 out of 12 steps of the way through the final vision - and the above are at varying stages of deployment (some early, some more established).
You've hit it on the nail - assembling code or building a programmatically controlled ESB is not rocket science - asking the right questions, and being able to get people to spec without knowing "how to code" or "understanding" tech is much harder. This is where have spent a large portion of our time in building out the "Studio" where you can choose templates, or problem sets and then we organize "features" and "workflow" logic behind it. The entire lifecycle is designed around the idea of an assembly process rather than a consulting - so its more prescriptive (we ask a lot of questions upfront) - its important to note that you still get connected to a human product manager, and there are designers from the capacity side (we work with over 100 dev shops around the world that give us designers and developers).
Hey Matt, please email me s at engineer dot ai and I'd love to see how we messed this up. Clearly we didn't do a good enough job and I want to make sure we make it right.
Hey man, I am the CEO at Engineer.ai - it's not vapourware but also not the holy grail - marketing put up a gate just because, well, we want to make sure we deliver a strong experience - given dropbox also had a gate - I think we took a leaf out of their book. As far as customers, we built a number of projects (186 so far through the platform) and this includes the BBC Click Audience App, the in game auction SDK that was for the SF Giants (a startup was our customers) and other clients include Virgin, Future Group and a bunch of other SMEs or the SME in big companies. You can email me s at engineer dot ai and I'll make sure to get it activated so you can see. Here is also a video demo without any marketing blah blah on it - https://youtu.be/dCk66hrlLmM
