CodeFutures

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Overview

$5,000+

Min Project Size

$100 - $149/hr

Avg Hourly Rate

2 - 9

Employees

2001

Year Founded

ABOUT CODEFUTURES

Providing everlasting value to our clients

Originally a supplier of database performance tools that streamlined the development of database applications, CodeFutures products were utilized by numerous prominent companies including FedEx, HSBC, T-Mobile, Lehman Brothers, General Electric, JP Morgan Chase, Walt Disney, Wells Fargo Bank, Kraft Foods, Bank of America, Lockheed Martin, ABN AMRO Bank, Verizon, Compass Bank, Siemens, and United Airlines. Drawing on their extensive industry expertise, CodeFutures now offers professional services and solutions related to strategy, consulting, technology, and operations. Having served over 40 companies across a diverse range of industries, CodeFutures has delivered significant value to many organizations.

Tech Stack

Amazon Application Development FrameworkGoogle app engineAzure PlatformWordPressNodeJSReactAngularReact NativeDjangoRuby on RailsJavaScriptC#+6 more

Languages Spoken

English

HIGHLIGHTS

$5,000+

Min Project Size

$100 - $149/hr

Avg Hourly Rate

2 - 9

Employees

2001

Year Founded

Services

Focus

Industries

Clients

Services Provided

10% Cloud Consulting & SI

8% IT Staff Augmentation

7% Other IT Consulting and SI

25% Custom Web Application Development

25% Cloud Infrastructure Setup (AWS / GCP / Azure)

25% Other Design

Portfolio

Recht Associates Builds an Intelligent Platform

Unknown

The objective was to develop a highly adaptable user interface that streamlines automated data processing, aggregation, and analysis. After navigating through these processes, any potentially problematic transactions could be pinpointed and exported to an Excel file for an analyst's review. CodeFutures initiated the project by exploring the data to gain a better understanding of how to identify missed commissions and gaps in Recht Associates' processed transaction history. A data processing plan was formulated based on insights from Recht's manual methods and further examination of the raw transaction data: - Using specified unique identifiers and aggregation functions, automatically transform raw data into a time-series transaction sheet for each unique buyer, seller, or part - Automate period-over-period transaction verification and analysis through machine learning algorithms and transaction comparisons - Narrow down relevant transaction data from millions of entries to a few thousand, focusing on those considered potentially erroneous according to user-defined criteria. This strategy has been implemented as a desktop business intelligence application. The frontend, built with the React and Electron JavaScript frameworks, is intended to be user-friendly for everyone within the organization. Users have the freedom to customize the analytics, aggregation methods, and checks applied to the data. The data processing and backend APIs are handled by Python scripts that run on an AWS EC2 server, which also stores the relevant raw transaction data. On the frontend, user-customized analytics are presented in reports featuring statistics, charts, and a table of the identified erroneous transactions. Users can download satisfactory reports as Excel spreadsheets for further analysis. *Additional features are continuously being developed.

SPARK Neuro Builds the First Portable TBI Tracker

Unknown

The project was primarily split into two sections. The team also engaged in daily stand-up meetings with SPARK to provide real-time updates on their progress and make adjustments as needed. Effective communication was essential for this solution, given the numerous components that needed to work together smoothly. The application was designed with user-friendliness in mind, prioritizing a seamless experience for both doctors and patients. The outcome was a straightforward yet powerful tool that required only a one-click setup to connect to the EEG machine. It guided doctors through the necessary procedures for having patients perform tasks and automatically uploaded the collected data to a SPARK Neuro server.

Enabling 30x Growth to a $100M ARR Enterprise

Unknown

At the beginning of the project, CodeFutures conducted a discovery and analysis phase to evaluate the existing architecture prior to making any recommendations. Critical bottlenecks were found in four key areas: service capacity, product delivery, operations and support, and compliance and security. The initiative was subsequently broken down into seven minimum viable products (MVPs), each addressing a significant challenge for the business. The proposed program resulted in Holon gaining the capacity to achieve a fourfold return on their infrastructure investment within the next three years. Holon can now concentrate on their technology and business growth without concerns about scalability.

Projects & Clients

Project Size & Rate

Minimum Project Size

$5,000+

Average Hourly Rate

$100 - $149/hr

Pricing Snapshot

Min Project Size

$5,000+

Avg Hourly Rate

$100 - $149/hr

Cost Rating

N/A

What Clients Have Said

"CodeFutures delivers quality projects within budget and timeline expectations based on verified client feedback."

Based on verified reviews and internal benchmark data

PROJECT BUDGETS

No budget data yet — reviewers either haven't shared a project budget or kept theirs confidential.

Select a service

Cloud Consulting & SI

IT Staff Augmentation

Other IT Consulting and SI

Custom Web Application Development

Cloud Infrastructure Setup (AWS / GCP / Azure)

Other Design

Industry Recognitions

85 Best Colorado Big Data Startups & Companies

View source

Locations

Headquarters

10011 West 120th Avenue

Broomfield, Colorado, United States 80021

+19494849249

Headquarters

1729 North First Street United States 95112

San Jose, California, United States 95112

+19494849249

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