Better Knowledge Faster

Better Knowledge Faster

We provide a variety of consulting services related to machine learning and complex ultra-low latency analytics on big data. By leveraging a variety of hybrid architectures, we effectively combine complimentary technologies and methods to address challenges that are beyond the capabilities of more traditional approaches. The methods and technologies applied result in “better knowledge faster.”

What We Do


The method of operating on data-in-motion in which data is operated on immediately as it arrives without the requirement that it first be stored in some kind of database is an alternative to batch processing.

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Some aspects of the solutions based on a software-based analysis framework are that they need to act more “intelligent” and be more tolerant of uncertainty than traditional solutions.

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An obvious and important use for data-in-motion stream processing is for medical monitoring.  More data is being generated today than ever and most if it is underutilized.

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Sharpe Engineering has developed and created multiple implementations of a signal processing pipeline that has been effective at operating on a wide range of time series data to detect and discriminate targets, biomarkers, and other patterns.

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Get To Know Us


Sharpe Engineering Inc. is a software engineering company based in Colorado Springs, Colorado, specializing in the application of advanced technologies to address complex problem spaces. We provide comprehensive software engineering solutions encompassing analysis, planning, design, implementation, testing, and deployment.

We contribute in both managerial and technical capacities across projects that span from enterprise application integration to custom vertical solution development and deployment. We have experience working with people and teams at all organizational levels, from individual developers to C-level executives, and we effectively bridge communication between technical and non-technical personnel.

Our ongoing investigations focus on methodologies to elicit emergent behaviors from large language models. These methodologies include complex hierarchical prompts, multi-step prompting, meta-prompting, and intrinsic motivation. We are also conducting research to develop a multi-modal generative AI agent specifically designed for hyper-local microclimate and activity-specific weather evaluations.

Our previous projects have tackled "big data" challenges that demanded complex analytics with low latency performance. We have served clients such as Bank of America, Verizon, Walmart, CenterPoint Energy, Detroit Energy, The Weather Company, the US Navy, IBM, and the Children’s Hospital of Philadelphia.

We offer consulting services related to various complex hybrid architectures that combine complementary technologies and methods to overcome challenges unaddressed by traditional approaches. These methods and technologies empower us to produce "better knowledge faster".

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