Client's Testimonial

"Developers.dev isn't just an outsourcing firm; they're an integrated part of our engineering organization. Their .NET Modernization and AI/ML pods allowed us to tackle parallel workstreams that would have been impossible otherwise. We reduced our time-to-market for our new AI analytics suite by two full quarters. The quality and commitment of their in-house team are unparalleled."

Sarah Jenkins, VP of Engineering, MarketingLeap Inc.

Client Overview

A US-based, venture-backed SaaS company with a $20M ARR, providing a marketing automation platform for mid-market businesses. They were struggling to keep pace with enterprise competitors, facing pressure from their board to release new AI-powered features to increase their average revenue per user (ARPU) and reduce churn. The high cost and slow pace of hiring senior .NET and Python developers in their local market was their primary bottleneck.

Problem

The client's core engineering team was at full capacity maintaining the existing platform, leaving no bandwidth to develop a new, mission-critical AI-powered analytics suite. Their inability to innovate was causing them to lose deals to larger competitors and was putting their next funding round at risk.

Key Challenges

Talent Scarcity:

Inability to find and affordably hire local developers with expertise in both legacy .NET and modern Python ML frameworks.

Speed to Market:

Intense pressure to launch the new feature suite within six months to present at their annual user conference.

Integration Risk:

Concerns about how an external team would integrate with their existing Agile workflows and company culture.

Maintaining Quality:

The need to ensure that accelerating development did not lead to an increase in technical debt or a decrease in code quality.

Our Solution

Developers.dev proposed a two-pronged solution with dedicated PODs.

⚙️ .NET Modernization Pod

A team of 4 senior .NET developers and 1 QA was deployed to refactor and modernize parts of the client's core application, creating the necessary APIs and performance headroom for the new features.

🧠 AI/ML Rapid-Prototype Pod

A parallel team of 3 Python developers, 1 data scientist, and 1 UI/UX expert focused exclusively on building the new AI analytics suite, from data modeling to front-end visualization.

🔗 Seamless Integration

We assigned a dedicated delivery manager who acted as a single point of contact, ensuring seamless integration with the client's Jira, Slack, and CI/CD pipelines.

🤝 Process Alignment

Our teams operated within the client's existing two-week sprint cycle, participating in all Agile ceremonies, including daily stand-ups, sprint planning, and retrospectives.

Implementation and Execution

Month 1

Conducted a paid 2-week trial and deep-dive workshop to align on architecture and roadmap.

Month 2

The two PODs were fully onboarded and integrated into the client's systems.

Month 3

The .NET pod successfully refactored the core data-access layer and built the required APIs. The AI/ML pod delivered a functional prototype.

Month 4

The two workstreams were integrated, allowing the AI module to pull data from the modernized core application.

Month 5

A comprehensive QA automation suite was built and executed, ensuring robust test coverage.

Month 6

The new feature suite was deployed to a beta group of customers, on schedule for the conference.

Positive Outcome

📈 40% Faster Delivery

The project was completed in 6 months, compared to the client's internal estimate of 10 months, a 40% acceleration.

🚀 Successful Launch

The new AI suite was the star of their user conference, leading to a 15% increase in upgrade revenue from existing clients within the first quarter.

📉 Reduced Churn

Beta users of the new feature showed a 50% lower churn rate than the company average.

💰 Cost Savings

The client saved an estimated 45% in salary and overhead costs compared to hiring the equivalent team locally.

Why Choose Us

✅ Vetted, In-house Experts

We have a dedicated POD with deep expertise in both IoT hardware integration and cloud software development.

🛡️ Verifiable Process Maturity

We managed the entire project, from hardware selection to cloud architecture and custom software.

🤝 Zero-Risk Talent Guarantee

We started by understanding the business risk and designed a technology solution to solve it.

🔒 Full IP & Data Security

Our architects are experts in building systems that handle high-volume, real-time data streams.

🌿 An Ecosystem, Not a Body Shop

We built a solution tailored perfectly to MedHaul's unique workflow, not a one-size-fits-all product.

🤖 AI-Augmented Delivery

The AWS platform can scale to handle tens of thousands of devices as MedHaul grows.

🌐 Global Delivery, Local Presence

The solution provides the immutable, verifiable log that the industry demands.

🏆 Proven Track Record Since 2007

The platform transformed their operations from reactive to proactive.

💡 Deep & Broad Tech Expertise

The investment in the platform paid for itself within the first six months through saved product and reduced insurance costs.

Conclusion

By providing highly specialized, parallel teams within a mature and integrated delivery framework, Developers.dev enabled the client to overcome their resource constraints, accelerate their innovation pipeline, and achieve a significant competitive advantage in the market. This case demonstrates the power of our POD-based approach to solving complex, time-sensitive business challenges.

How a Strategic Staff Augmentation POD Helped a SaaS Leader Accelerate Feature Delivery by 40%

Industry Software as a Service (SaaS) - Marketing Automation