endorsedCompleted

AI-Powered Research Web App for TalentNeuron

Services Covered:

AI and Machine Learning • Custom Software Development • Website Development • API Development • UI/UX Design • Application Integration

Industry

Human Resources & Staffing

Duration

12 months

Budget

200K - 999K

Start Date

1 October 2024

Team Size

6-10 Employees

Engagement Model

Onshore

Project Capability Score (PCS)

77/100

Good

Project Capability Score (PCS) estimates how capable TangoCode Inc is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

TalentNeuron

New York City, United States of America

Project Summary

TangoCode partnered with a workforce analytics company to design and build an AI-enabled research web application, covering discovery, architecture, implementation, integration, and deployment. The engagement delivered a research automation platform, AWS-based data pipelines, AI/ML intelligence modules, and a customer portal with dashboards and enterprise integrations. The solution reduced manual research effort, sped turnaround times, improved accuracy, and enabled scalable, SaaS-style delivery of research services.

Key Challenges

Build an automated, AI-powered research web application
Improve the customer experience for research and insights delivery
Reduce manual effort, time, and cost associated with traditional research workflows

Project Deliverables

Research automation platform (web-based intake and delivery system)
Data pipeline and AWS-based cloud architecture
AI/ML intelligence modules for role classification, skills extraction, and matching
Customer portal and UI/UX dashboards for report tracking and analytics visualization
Enterprise integrations including REST APIs and Salesforce connectivity
Quality engineering, testing, documentation, and knowledge transfer

Project Solution

TangoCode partnered as an embedded product engineering team to design, build, and scale an AI-enabled workforce intelligence platform. They delivered end-to-end product development including discovery and architecture, implementation of AWS-based data ingestion and transformation pipelines, AI/ML modules for role classification and skills extraction, a customer-facing portal with dashboards and self-serve capabilities, REST API integrations (including Salesforce), and QA, testing, documentation, and knowledge transfer to support maintainability and handoff.

Project Outcome

~60–70% reduction in manual research effort through automation of ingestion, report generation, and delivery workflows
Turnaround time reduced from days or weeks to hours for many standard research requests
3–4x increase in request-handling capacity without adding headcount
Improved data accuracy and consistency via standardized pipelines and validation
Faster client onboarding through structured intake forms and Salesforce integrations
Enhanced customer experience via a centralized portal for requests, tracking, and downloads

Platforms

Cloud
Web
AI/ML Platform

Tech Stack

Amazon Web Services (AWS)
RESTful API
Jira

Client Endorsement

Overall Review Rating

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“TangoCode's work reduced the client's manual research effort by 60-70%, increased request-handling capacity by 3-4 times, and cut turnaround time from days or weeks to hours. They also improved data accuracy and consistency, streamlined client onboarding, and enhanced customer experience.”
RajaGopal Kesiraju
Director of Product Management
Date: 02/01/2026