CREATING A COMPETITIVE ADVANTAGE THAT INCREASES WITH TIME.

EnergyX

EnergyX is unlocking the power of edge compute. Their X-MDC modular data center brings immersion-cooled high-power compute directly to virtually any energy source, eliminating the need for expensive infrastructure. The X-MDC uses up to 40% less energy than traditional centers, creating a much smaller carbon footprint. At the same time, its novel design delivers up to 40% more computing power. The result is powerful compute that is efficient, stable, secure—and actually affordable. 

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Petrolog

Petrolog is an artificial lift controller company that has IoT and AI functionality. They provide producers with the ability to get telemetry (communications) at each well while also controlling the dynamic lift functions of the well itself.

The controller optimizes how the well produces by learning the most efficient cycle for each individual well. This generates additional production at the well, reduces the amount of energy required to lift the fluids for the well and gives visibility to the operator at any time for each well.

This visibility allows pumpers to easily determine which wells are running and those that may have mechanical issues that need to be addressed. They can then plan each day according to the needs of the field, this is called pumping by exception. The ability to monitor each well remotely adds significant value for the producer and can create human resource savings above the production increases and power decreases provided by Petrolog.

Once Petrolog controllers are installed, RTI has created a beachhead into producer operations. Every installation provides us with the ability to control well production and report a vast amount of data. This is critical to realizing our overall simulation, optimization, and automation strategy.

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Tacit

Closing Soon

Tacit is a cloud-based knowledge platform focused on capturing, preserving and scaling “undocumented” or tribal knowledge necessary for driving mission-critical outcomes. Tacit will make it easy for industrial workforces to use the devices they already own + leverage emerging head-worn devices (“HMDs”) and other form factors to access data, knowledge bases and live expertise to improve equipment availability, compliance and, above all, safety.

In their phase 2 Tacit Network, Tacit is building a human network marketplace that allows retired (experts) individuals to work remotely from the comfort of their home on-demand and in real-time. Tacit combines HMD and smartphone/tablet technology, human mapping to assets/locations and AI into an attractive pragmatic offering that is simple and intuitive for users.

This uniquely fits with RTI in that Tacit can provide a visualization tool for the field relative to the solutions that we are bringing to market. For example, if we have a real-time surface model of all the equipment and a bottleneck was occurring, the field could quickly determine where the problem exists and address it.

Altered Silicon

Closing Soon

Altered Silicon is a company focused on mapping AI compute loads for Field Programmable Gate-Array computers (FPGAs), and Application Specific Integrated Chips (ASICs). Machine Learning and AI algorithms are usually best trained on GPUs, Graphical Processing Units.

GPUs accelerate operations that can be parallelized. For example, if a company had a large reservoir model that needed computational power, the tasks could be delegated to a vast array of GPUs to quickly solve the problem.

FPGAs are boards that can be reprogramed for very specific configurations, such as AND and OR gates. Consequently, once the example reservoir model begins to utilize specific repeatable instructions, they can be mapped to a card. This can provide a 5X-50X increase in computational power at ¼ the power and 1/5 of the density within a data center.

These efficiencies equate to huge savings.

ASICs take the process one step further and the code is basically created in silicon. ASICs take the processing increase, power decrease and density to the next log scale level. The competitive advantages created by FPGAs and ASICs for AI companies are vast.

Essentially, if a company has quality AI products and implements these types of hardware, they could corner the market in their specific AI category. This can easily be seen in the crypto mining market.

WellDatabase

Closing Soon

WellDatabase, a competitor to IHS and DrillingInfo, is unique in its ability to ingest, normalize, correlate, and effectuate data. 

WellDatabase has excellent functionality for its users for about half the cost of its competitors. They have automated data integration processes that reduce cost, limit data error and facilitate rapid data cleansing as new, more relevant data is accessed.

Additionally, their data model was purpose built from the ground up with “big data” in mind which is the opposite of their competitors. The analytics engine that WellDatabase has created is second to none in the industry. They can forecast well by well production by utilizing best fit models trained on massive amounts of data that also includes production volatility analysis. Their analytics engine is up to 10X cheaper that the competitors while being a seamless interface to the UI.

WellDatabase provides RTI with a data platform to build around and can assist in integrating our various portfolio companies’ data. In order to achieve quality AI results, we must gather and process a tremendous amount of data. WellDatabase can be our conduit.

Temp

Another initial investment is a $1 million position in the Keystone FH1 data center in Pennsylvania, strategically positioned adjacent to New York City and other eastern markets. This facility is a hyperscale, mega-powered data center that will offer 45MW of dedicated white space to customers that is easily segregated into tranches of 5, 10 or 15 MW depending on customer needs.

Our position will allow us to extract favorable rates for our other technology company investments, creating a synergy that will create a competitive advantage that will drive performance for our overall fund.

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