We had the opportunity to attend the first C3IoT analyst day at their headquarters in Redwood City. The office itself is worth mentioning as it’s a nice departure from the often bland offices in Silicon Valley, with lots of greenery, a floor crossing light alcove and a lot of wood.
Here is the 1 slide condensation (if the slide doesn’t show up, check here):
Want to read on? Here you go:
Unique model driven architecture – C3IoT has built its platform with integration in mind. While traditional platforms create and then integrate, C3IoT starts with integration to create a new combined data storage, that enables Analytics, Machine Learning and C3IoT Apps. Taking advantage of a type based system, it’s fast and easy for enterprises to integrate their data and then create insight applications. The integration first approach is unique in the enterprise software industry, and acknowledges that no enterprise starts from scratch in 2017 (and beyond).
C3IoT is more than IoT – In contrast to the vendor name, C3IoT’s platform does more than ‘just’ IoT – it very much can power all seven generic next generation application use case that we track at Constellation (next to IoT, Tame the Internet, Revolutionize Inter Enterprise, Data as a Service, Digitize Value Chains, Re-Invent Communication, and Innovate the Human Machine Interface). The vendor will have to clarify its broader scope to the markets, the good news is, that C3IoT already has customers implementing beyond IoT use cases.
Broad platform support – C3IoT made the announcement of supporting AWS at last year’s reinvent conference, by now it has added support for Microsoft’s Azure. No surprise as the C3IoT customer base is formed of large multi-national enterprises, that all have their respective bets on different IaaS. It’s good to see that C3IoT with a relatively small employee base can provide its platform on different IaaS platforms so quickly. On the Machine Learning side, C3IoT is also supporting a wide variety of libraries and is adding more. As typical for these days of Machine Learning, Tensorflow support is crucial.
Good customer adoption – Small companies are not in the cross hairs for C3IoT. The vendor prefers large strategic relationships with large multinational enterprises. But large does not mean slow, as the first use cases with C3IoT go live in a few months, sometimes in a few weeks. Growth of know-how is crucial for C3IoT, so projects are often started in a jointly staffed center of expertise, with a customer’s developers and data scientist gradually taking on more responsibility. During the analyst day two large enterprises had over two dozen employees being trained at C3IoT headquarters. For 2018 the vendor plans to push education in high gear, planning a MooC course.
MyPOV
Overall C3IoT has shown that it has an appealing approach and architecture to enable enterprises to build next generation applications. Most PaaS offerings in the market start with build first, integrate next. Enterprise software has been built with that approach for a long time, but that has led to fractioned applications and functional silos. The nature of the C3IoT applications has a strong holistic approach to an enterprise’s data and automation, and therefore requires starting with integration into a data storage (if you wish a data lake) first, then built analytics, Machine Learning or applications on top of that information base. Usually approaches like this took years to build, often being too slow to keep up with the transactional source systems. The fast implementation times of C3IoT customers are encouraging that the vendor has provided a platform that may have broken the tide on this.On the concern side, C3IoT is a relatively small vendor, with limited resources that must support a large solution footprint and a demanding customer base. Single projects that the C3IoT platform powers typically required a headcount larger than C3IoT’s complete employee base. Truly a David vs a Goliath task scenario, which C3IoT can only solve with scaling know how and 3rd party resources rapidly on its platform. Training customers directly is going to be too slow, so the train the trainer and center of expertise approaches are promising. Adoption by the large SI firms will help, too. But likely C3IoT will stand and fall by the adoption of its planned 2018 MooC offering.
On the flipside, having adoption challenges is a good problem to have for a vendor that has a working platform, products and is well funded. It’s now key for C3IoT to overcome the resource shortage it needs to address to become a truly successful enterprise platform. It has the DNA for it – from architecture, platform, funding and executive leadership. Time to show it in 2018.
