Our Work



Increased Revenue from Job Boards for a Prestigious Media Company

A prestigious media company provides its customers a valuable recruitment service, with job ads online, and an online tool for job seekers to upload their documents and manage their job search. A key challenge in generating revenue from the recruiting tool is matching job ads with candidates.


Synaptiq leveraged its deep expertise in machine learning classification and natural language processing to develop a supervised machine learning solution that uses existing profiles to learn a probabilistic mapping from resume/vita text and job ad text to job categories. This included the development of a machine learning-based classification system that intelligently categorizes documents that users upload.


Both of these efforts greatly improved the relevance of matches between jobs and applicants, leading to more effective ads for institutions, higher revenues for the customer, and follow on work for Synaptiq.

Big Data and Machine Learning Applications for DevOps and Security

A provider of global satellite imaging and geospatial monitoring data partnered with Synaptiq to support one of their large government agency clients. The agency wanted to bring together hundreds of stovepipe analytics projects, data sources and tools into a common cloud-based framework. This would allow them to more effectively unlock the potential of machine learning and advanced analytics to exploit synergies across the organization.


Synaptiq leveraged its extensive expertise in infrastructure for massive data environments to develop core big data and machine learning capabilities, successfully addressing the agency’s key challenges. Synaptiq built a scalable big data pipeline that aggregates various cloud data sources from hundreds of Amazon resources into a data lake used for time series analysis. The system was built using Amazon Kinesis, Spark EMR, Amazon S3 and CloudFormation.

Synaptiq constructed a deep reinforcement learning system that automatically optimizes cloud resources based on user defined specifications of what's important. The machine figures out "how" by learning optimal control policies. Synaptiq also performed feature engineering, constructed a probabilistic supervised machine learning system that identifies false positive software vulnerabilities from software scanning results, and designed a simple user experience that displays a significantly reduced set of ranked vulnerabilities. 


The solutions were demonstrated to the agency and follow on work has begun to prepare the solutions for production and address other agency challenges using machine learning.

Data Science and Strategy in Personalized Medicine

A funded startup in the personalized medicine space contacted Synaptiq to quickly explore their rich dataset for preliminary insights that may open new revenue opportunities.


Synaptiq delivered a comprehensive set of summary statistics , performed multivariate analysis to find correlations and anomalies in their data, and pinpointed interesting insights. The team also assessed the company’s investment plans, product user experience, and technology backend.


Synaptiq presented a strategy and multi-phase plan to the rapidly growing healthcare startup, recommending improvements to their existing data capture system, outlining future analytics capabilities, and areas for further data exploration.  The team is working on preparing for the next project.

Valuation of Machine Learning Technology in a Mobile App

A leading market research firm was hired to perform due diligence on an intelligent mobile app company. The firm hired Synaptiq to evaluate the machine learning technology in the mobile app.


Synaptiq conducted an extensive review of patents held by the company as well as prior art, compared that to state-of-the-art approaches in the current scientific literature, and produced a detailed comparative and evaluative report.  That report situated the company’s IP with respect to the rest of the field, and explained what the barriers are to another company trying to overtake their position in the market.  

Synaptiq conducted interviews with all key technical personnel to assess their competence in the relevant technologies running the gamut from user interface design to back-end development to machine learning.


Synaptiq’s findings were incorporated into an overall due diligence document to determine the company’s valuation.




Synaptiq distinguished itself from other vendors because of their focus on business results. They applied their machine learning solutions and saved my company hundreds of thousands of dollars in manual work we performed annually.
— CTO, Leading Media Company