Treselle Systems

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Treselle Systems is a technology services and product development company headquartered in Campbell, Calif., with offices in Durham, N.C., Singapore, London, and Chennai, India. They have about 85 employees that do web development, big data consulting, and SI consulting. They were founded in 2004 and focus primarily on enterprise clients. 

Client Insights

Industry Expertise

This provider has not added their industry expertise.

Client Size Distribution

This provider has not added their client sizes.

Common Project Size

$200K-$999K 1 project

$1,000,000-$9,999,999 1 project

Clients

  • Discern

Highlights from Recent Projects

Overall Rating

5.0
2 Reviews

Treselle Systems partnered with Discern, a data marketplace, to manage the volatility of their growth and provide highly skilled resources. They successfully built and designed an intuitive search engine, implemented embedded interactive analytics capabilities, and developed intelligent agents to notify users of significant changes in the data. The team also worked with structured and unstructured databases and utilized the Amazon Cloud. The partnership started in November 2012 and continues to this day, with Discern investing approximately $45,000 per month in Treselle Systems.

In another project, Treselle Systems was contracted by a financial data company to assist with their data processing solutions. They took over the company's Amazon Web Services infrastructure and handled data scraping and processing, site security, and other related aspects. They developed tools for data scraping, wrote an elaborate natural language processing system for drug and device trials, and implemented algorithms for data organization and cleaning. The team at Treselle Systems also automated previously manual processes like linear regression models, predictive models, and clustering tables. The company has been working with Treselle Systems since November 2012 and spends around $50,000 per month on their services.

Timeliness

5.0

Service Excellence

5.0

Value

5.0

Would Recommend

5.0