the construct of a commodity futures exchange. Most simply it enables real-time, dynamic ridesharing on a very large scale in any type of vehicle which carries passengers or freight. Using mathematical optimisation techniques (based on heuristics and genetic algorithms) the Transit Exchange examines and aggregates origin-destination requests for transport from dispersed users in both space and time (who may or may not know one another) and applies operational concepts and knowhow garnered from successful prior deployments, Texxi provides a relevant trip package suggestions for ridesharing to those users and the vehicle operators in the locality. The Transit Exchange also generates income for municipal road operators from the very market making functions used to fill the empty seats in the fleet or vehicles operated in the “transportspace”. Now congestion pricing, road pricing and vehicle pricing charges can all be applied to users and a negative congestion charge implemented so as to not adversely affect the poorest in society. Predictive Analytics permit the transport users to choose when to travel and the transport service providers to place their assets in the most logical positions to best serve demand. If an investor was to deploy an amount of money into the Transit Exchange, then through the market making protocols in solving NP-hard problems related to Large Scale Dynamic Real-time Ridesharing a set of returns with varying yield-to-maturities can be replicated, providing an alternative to money-market funds and instantiated through the mechanism of a blockchain coin offering. Rather than relying on the rather nebulous promise of perpetual cryptographic security of a blockchain ledger, the provable work done has solved a pressing and current problem in the real world and done so in a manner that was transparent. High Liquidity investable security instruments (Transit Exchange Bill or TE-Bills) can thus be made available via the Transit Exchange. Its original purpose. To store value represented by demand for travel in a locality. Hence we will have a computational-crypto-currency backed by a commodity called “transport demand”. From 1968 - 2010, many academics in many of the top Universities in the world said that dynamic, real-time, ridesharing was not yet possible. Texxi proved it was possible in 2006 and in 2008, using the idea of a futures exchange, a dynamic social network map and genetic algorithms to solve an otherwise intractable solution. SAAS, Computational-CryptoCurrency, Artifical Intelligence, Predictive Analytics, Social Network, Mobile, MAAS, Demand Repsonsive Transport