Data & Market Engineering

Architecting Marketplaces

Data & Market Engineering.

Shaping markets, designing the institutional form, and implementing the supporting technology fabric is what we do at Zasai. Applying systems thinking, challenging the orthodoxy of market systems, and applying new models of data engineering with cryptography and machine-learning.

Analysis of information in near real-time enable new ways to organise but it also presents many new challenges. Not just technical but also accessibility, security, regulatory, ethical, and privacy challenges. All these challenges motivate our work.

Market Design

Market engineering is the principal design and implementation of market platforms. The design and engineering of markets takes into account the various aspects of economics, the legal structure, the surrounding environment, and coordination (or allocation) problems being solved. In this context market stands for a set of rules that define the exchange of information between participants. The market enables them to interact, or cooperate, at minimal cost. We bring a wealth of knowledge to help you think strategically and to design your platform.

Data Engineering

Data analytics tools enable new market opportunities and with it opportunities for platforms (Market places) that just weren’t possible a decade ago. However extracting actionable insight from a volume and variety of data in a way that market participants can interact with the results requires a data processing pipeline that is engineered to the particular problem and market context. Data engineering builds the infrastructure and systems needed to transform data into a useful format for analysis. At Zasai we bring the expertise in building the data pipelines for operational and analytical processing of large streams of data in near real-time.

Computational Contracts

Companies and all commercial arrangements are a network of contracts. In this sense computational law applies data analytics, data mining, and machine learning to in the practice of law. But to architect accountable and secure market systems we’re focused on operational matters too. In particular the design of domain specific languages for the writing, analysis, executing and performance of commercial contracts. That is merging the world of programming language design to the task of legal commercial contracts.

"A market is a set of humanly devised rules that structure the interaction and exchange of information by self-interested participants in order to carry out exchange transactions at a relatively low cost."

Gimpel et. al.

What we do

Working at the cutting edge of digital technology, markets, and the interaction with society means no one project fits nicely into a neat box. Tasks vary, customer focus change, and technology stacks are assessed based on the problem.  We can write code but our particular technology stack may not be the best choice for the given context so we’ll find the people that know a particular technology stack. 

Data Markets

The sale and use of data has been a venerable business. Notable in the history of data sharing is Lloyd's Coffee House insurance market in the 17th century and Paul Reuter’s transmission of stock exchange prices between Paris and London. Today Data markets are a form of data distributor, where consumers and publishers self-select and negotiate use of data.

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Design Research

A design-lead product process is so important to successful outcomes that we mandate it on all projects we work on. If for only one reason we prefer to build the right thing, not just anything. It is still surprising how often we get asked to build it; for whatever ‘it’ is. So we find ourselves advising a lot on customer and product strategy and doing service, product, and user experience design. 

Product Management

At the intersection between business, technology and service/user experience. Product management plays the role of defining and communicating the product vision, the customers’ needs, and manage how they co-evolve according to a strategy. Product management is the custodian of the product road-map. Making sure the road-map is shared and understood by all stakeholders. 

Agile Development

New product development often involves a lot of uncertainty. Customer needs, market evolution, technology choices, organisational context, and team skills. There is no way we can get the mix 100% right. Rather rafting over a waterfall, we cross the river by feeling the stones. Taking a step at a time and adapting to the feed-back. Effective product development is about shared understanding and agile methods minimise project risk.

Software Development

Our main language toolset combines the use of Erlang/OTP, OCaml and Reason. We use Kotlin when working in a JVM environment and Dart for Web. Also building secure and fault-tolerent systems are important to us, so formal methods are important to us. When it comes to leveraging a cloud platform our preference and knowledge is centred on Google cloud platform.

Smart-Contracts & Blockchains

Revisiting software architecture for pervasive computing- making it accountable, making it legal.

While the idea of mechanised legal analysis is not new, its prospects are better than ever due to recent technological developments including progress in Computational Logic, the growth of the Internet, and the proliferation of autonomous systems (such as self-driving cars and robots)

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Algorithmic Ethics and Accountability

Far from being a thing of the future, automated decision-making informed by algorithms (ADM) is already widespread phenomenon. It is used in contexts as varied as advanced driver assistance systems, where cars are caused to brake in case of danger, and software packages that decide whether or not a person is eligible for a bank loan.

Automation is set to play a part in every area of life, politics, and law.

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Recent Talk: Data Commons

Governing Information Reuse in Common

The May 2017 Economist issue is about— “The World’s Most Valuable Resource...”— and makes the case that a Networked Data Economy is not a goods economy. That there are economies of “data” scale in quantity and quality that data companies enjoy.

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