Q&A with Greg Skerry, Solutions Architect at Altoros

  • TeqAtlas
  • Jul 06
  • Interview
Q&A with Greg Skerry, Solutions Architect at Altoros

TeqAtlas talked to Greg Skerry - Enterprise Blockchain Solutions Architect at Altoros about implementing high-end technologies in businesses, most prominent use cases and challenges they faced while implementing an emerging technology like Blockchain and Artificial Intelligence.

1. What technology solutions in your product line obtained the greatest number of use cases among small & medium businesses?

Within the permissioned blockchain space, we find the frameworks under the Hyperledger project (particularly Hyperledger Fabric) are well-suited to handle the needs of a wide range of business scenarios and use-cases. The modular design and configurable nature of Hyperledger Fabric gives it perhaps the widest adaptability.

2. What kind of challenges do these solutions solve for your clients?

We're seeing blockchain solutions used to tackle a range of enterprise challenges, from increasing efficiency and transparency of back-office functions to supporting new-to-market platforms and services. Some of the notable industry verticals utilizing permissioned blockchain continue to be areas such as supply-chain and trade finance.

3. What business operations are the most applicable for Distributed Ledger and Artificial Intelligence?

Using the supply-chain example as a jumping-off point, it is frequently going to be operations involving multiple, unrelated parties, that currently struggle to find a reliable, efficient and uncontested source-of-truth. Managing pooled or collective data today with traditional technologies generally means one of two things: (a) lots of costly (in time and capital) verifications and redundancies across multiple systems and/or (b) centralized data systems controlled by a single party involved, disenfranchising partners and just as often leading to costly disputes. DLT offers a high potential return in these fact-patterns.

4. What do businesses need to be aware of and what challenges can they face while implementing an emerging technology like Blockchain and Artificial Intelligence?

Really at the end of the day, it's an interesting tension between the appeal of decentralized ownership, vs the cost and effort associated with taking on that data ownership. There is a range of approaches and design patterns that can be used to strike the right balance of hands-on and hands-off management of blockchain nodes in production. It's just a classic question of how much ownership you want to turn over for the sake of convenience.

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5. Implementing high-end technologies impacts the legacy system of any company. What major upgrade of the legacy systems have your clients had to go through? What were the main challenges and how were they solved?

As counterintuitive as it might be, blockchain is not all that disruptive to most legacy systems, in the sense that it really can't be layered on top of centralized paradigms and so it will be deployed in parallel the vast majority of the time. Likewise from an integration perspective blockchain doesn't necessarily mean upgrades to legacy systems. The most common patch we see deployed is the creation of interfaces (APIs) between legacy and blockchain networks prototypes, in order for them to communicate and sync. For clients that might have antiquated or no existing cloud infrastructure, then sometimes there is some required ramp-up effort just to provide an environment to host blockchain nodes.

6. What would you say is the most disruptive and revolutionary project you have worked on for a client? What were the main struggles and major outcomes?

We're currently working with a global retailer to implement blockchain infrastructure across its order management system, touching its entire network of suppliers and purchasing customers. Seeing the potential to greatly reduce processing time and errors, while increasing transparency across a global supply-chain is inspiring.

7. What clients have benefited the most from your solution (ROI growth, cost reduction, etc)? Could you describe the most prominent cases?

While quickly reiterating that Altoros is a professional services model, generally, the clients that have benefited most from adopting blockchain technology have been in that common fact-pattern (operating within a fragmented supply-chain with multiple other participants, and suffering from required redundancy and inefficiency of verification amongst themselves, or being dependent on a single influential participant with a monopoly on the data infrastructure of the space). When blockchain is successfully implemented, we see those redundancies removed, and costs associated with settlements, verification and disputes drop off dramatically. Relative to many centralized data technologies, blockchain is also better self-maintaining over a long horizon.

8. What areas do you think are the most applicable for the combination of these technologies?

So I'll quickly caveat being an unapologetic skeptic of 'buzzword mashups', and when I hear Blockchain & AI together, I do generally probe as to what the motivation and driving business need is to combine these technologies. With that said, blockchain is, by nature, a very promising large-scale and widely-available data store, so the use of AI in this sphere is very likely to continue and increase over time, for that reason alone. If we consider blockchain as part of any general data pipeline, then there are varying scenarios inbound and outbound. Inbound: being an immutable database, the old adage garbage-in-garbage-out is as pertinent as ever. AI algorithms can be used to apply data cleaning and other filters to ensure what ends up on-chain is as clean, light and error-free as possible. Outbound: again, if we consider blockchain to be a wide (even global) and open data store, then the AI analytics applications are fairly uncapped. Getting clinical and other health data available on blockchain, for example, might mean unprecedented opportunities for analytical breakthroughs, driven by AI. Again, it's not that there's an inherent link between blockchain and AI as technologies per se, but perhaps just more that each advances the end goals of the other. It's a good example of this humerous pattern we've noted within the blockchain space; that frequently its power is really in its ability to consolidate everyone into a single (decentralized) framework. Takes the mind an extra second to process sometimes.

9. According to your practice, what kind of consulting do you usually provide your clients with? What are the typical piece of knowledge and expertise that the average client lacks in terms of Blockchain technology adoption?

Altoros enjoys a depth of expertise in a wide range of cutting-edge technologies, allowing us to bring value to clients in multiple domains. e.g. our team has just recently released cited research around zero-knowledge-proofs and their application in blockchain. We're also a long-standing leader in cloud infrastructure technology (e.g. being a cloud foundry leading member), and have both R&D and deployment teams advancing the applications of TensorFlow and other AI technologies. For blockchain, clients are frequently attempting to sort out the pros and cons of various (rapidly evolving) technology options. We help them determine, for example, whether blockchain is the right solution at all (sometimes it is not); whether open-chain technologies (e.g. Ethereum, EOS, etc) make the most sense, vs. permissioned options like Hyperledger and Corda; and moving into design and deployment, we assist with infrastructure heavy-lifting and automation, leveraging our expertise with tools like k8s, etc.