Actionable Statistical Inferance

Inferistics employs the latest scientific and academic advancements in Artificial Intelligence (AI). We employ a hybrid approach of Machine Learning (ML) techniques and data to tailor solutions to domain-specific solutions.

Utilizing Open-Source models and fine-tuned customization, we achieve more accurate results specific to an individual organization’s scope of unique challenges.

Applicable Results

Inferistics focuses on productionizable and maintainable solutions covering the complete stack of AI development. From data sourcing, engineering, and sustainability to front-end integrations into your organization’s workflows.

Data Acquisition & Engineering

Covering the dirty work of acquiring data, normalizing, and efficient storage designed for AI model building and consumption.

State-of-the-Art Techniques

Applying you data to the latest Deep Learning Networks and Advanced Decision Tree science.

Technical Integration

Integrating AI inferences seamlesly into existing production systems, offering full automation and expert knowlege augmentation.

Advisory

Practical recommendations for edge cases and realistic expectations in a field filled with excessive hype and propaganda.

Inferistics' Philosophy

Inferistic's focuses on domain-specific challenges at a scale that produce actionable results. Our implementation philosophy focuses on quality and the minimizing long-maintenance of completed solutions. We prefer to demonstrate how these high quality solutions will earn your confidence for follow-on work covering new domain challenges.

Together we have over 40 years of deep industry experience seeking to solve the most complex problems with simplicity, scalability and maintainability. We pride ourselves in the quality of our work to earn additional opportunities - rather than having long term support requirements necessary to adopt our solutioins.

Over our many years of experience, we have collectively made many mistakes - and learned from them. This experience enables us to know when a solution is optimal and tempered us to know when further R&D is required.

- "We have made the mistakes so you do not have to."