Predictable Delivery, Backed by Process
Clear milestones, early visibility into risks, and regular communication keep delivery under control from day one of our engagement.
Projects successfully delivered
Of new business comes from client referrals
Clients partner with us for 6+ years
Delivery time improved with AI
From growing companies to global enterprises, teams rely on Stack Builders to build software that performs reliably and supports measurable business outcomes.
Whether you’re launching a new product, improving core software, or bringing AI into your systems, we help move technical priorities into production with senior-level execution tied to clear business goals.
Build and modernize software aligned to your business goals, from new products to legacy systems.
AI systems built for real-world impact, from data readiness and custom models to agents and computer vision.
Deliver secure, scalable software with stronger DevOps, architecture, and systems built for reliability and compliance.
Software delivery is high-stakes, and AI has raised the bar. Stack Builders brings disciplined engineering standards and a proven delivery process to help teams balance speed, quality, and long-term reliability.
Clear milestones, early visibility into risks, and regular communication keep delivery under control from day one of our engagement.
Senior nearshore engineers work closely with your team, move work forward, and add capacity without extra oversight or headcount.
Our team uses AI to accelerate planning, coding, review, and documentation, but the process is guided by experienced engineers who know what quality looks like.
We learn your business, users, data, and constraints before choosing the technical path. This keeps AI and software decisions grounded in real outcomes.
We work with teams across many diverse industries where software, data, and AI play a critical role in growth and operations. Here are a few of the environments we know well.
Platforms in this industry require durable, dependable systems that can outlast and perform under pressure. We’ve supported production systems tied to high-security environments, including 3M+ lines of Haskell, helping maintain stable, secure software where system failure is not an acceptable option.
Marketing teams often struggle with fragmented data, manual campaign management, and limited visibility into performance. We’ve built advertising and e-commerce platforms that integrate ad systems, customer data, and internal tools, helping teams use cleaner data and AI-ready foundations for better performance decisions.
Financial systems must handle complex transactions, integrations, and regulatory pressure without increasing production risk. We’ve worked on insurtech and money movement platforms, including a TypeScript rewrite that helped identify 15% more bugs early in delivery.
Telecommunications teams need real-time performance, uptime, and reliable integrations across complex networks. We’ve supported globally distributed systems integrating thousands of APIs across Asia, Europe, and the U.S., helping create stronger foundations for automation, AI-enabled services, and customer-facing platforms.
Health and wellness platforms depend on accurate data, user trust, and consistent digital experiences. We’ve supported genomics, medical expenditure analysis, and personalized education platforms, helping teams improve reliability in data-heavy systems where AI can support better insights over time.
Our clients work with us when software quality, technical judgment, and long-term reliability matter. Their words reflect the kind of partnership we aim to build: clear, accountable, and focused on real outcomes.
“As a company Twilio is always seeking expert functional programming software consultants and we are thrilled with the level of professionalism and expertise the Stack Builders team brings to the table. Their consultants were not only technically proficient but also excellent communicators. They take the time to understand our unique needs and provide tailored solutions that align with our business objectives.”
“Stack Builders has been a fantastic partner in helping to augment and enhance our development efforts. In particular, Stack Builders developers have long been a cornerstone of the team developing our e-commerce platform, embedded alongside our own software engineers. They are great teammates, consistently produce high-quality work, and demonstrate a level of professionalism and commitment to our company's work and mission that far exceeds expectations.”
“GRC Solutions has worked with Stack Builders since 2016 on our Adaptive learning platform. We engaged their services as they have on staff a team of Haskell developers along with other full stack devs that understand our products and our business. Stack Builders are an integral part of our business and a trusted partner.”
“Stack Builders has been a superb partner on Spireworks as we’ve developed a number of solutions that complete our unique technical requirements.”
We use formal methods, modern frameworks, and cloud-native tools to build high-assurance systems. Every technology choice is made to ensure optimal performance and longevity.
Let AI Debug DynamoDB Without Giving It Your AWS Credentials
Our latest Quito Lambda showcases how to use LocalStack to test AI-assisted DynamoDB fixes locally. The session offers a practical approach to AI-assisted debugging: give the agent a repeatable test environment that exposes meaningful failures, and control where its commands can operate.
Design is Not Dead: The Designer as the AI Director
AI can generate interfaces faster than ever, but speed alone does not create usable, accessible, production-ready products. This blog explores why designers are becoming AI directors, guiding tools like Claude with the right systems, constraints, and human judgment.
Modernizing Legacy Software With Spec-Driven Development
Spec-Driven Development gives teams a structured way to use AI in legacy software modernization while preserving business requirements, technical constraints, and human oversight. By combining durable specifications with incremental delivery and measurable validation, teams can make AI-assisted modernization more reliable, controlled, and repeatable.
Massiv vs. Accelerate: Two Paths to High-Performance CPU Computing in Haskell
Programmers commonly use languages like Python, or C/C++ for those seeking higher performance, to handle array manipulation with libraries such as NumPy, SciPy, or deep learning frameworks like TensorFlow. Although Haskell is not a mainstream language, some developers favor its functional paradigm and strong typing. Importantly, Haskell offers its own libraries for high-performance array manipulation. This article will introduce two of the most popular Haskell libraries for this purpose, Massiv
Let AI Debug DynamoDB Without Giving It Your AWS Credentials
Our latest Quito Lambda showcases how to use LocalStack to test AI-assisted DynamoDB fixes locally. The session offers a practical approach to AI-assisted debugging: give the agent a repeatable test environment that exposes meaningful failures, and control where its commands can operate.
Let AI Debug DynamoDB Without Giving It Your AWS Credentials
Our latest Quito Lambda showcases how to use LocalStack to test AI-assisted DynamoDB fixes locally. The session offers a practical approach to AI-assisted debugging: give the agent a repeatable test environment that exposes meaningful failures, and control where its commands can operate.
Design is Not Dead: The Designer as the AI Director
AI can generate interfaces faster than ever, but speed alone does not create usable, accessible, production-ready products. This blog explores why designers are becoming AI directors, guiding tools like Claude with the right systems, constraints, and human judgment.
Design is Not Dead: The Designer as the AI Director
AI can generate interfaces faster than ever, but speed alone does not create usable, accessible, production-ready products. This blog explores why designers are becoming AI directors, guiding tools like Claude with the right systems, constraints, and human judgment.
Modernizing Legacy Software With Spec-Driven Development
Spec-Driven Development gives teams a structured way to use AI in legacy software modernization while preserving business requirements, technical constraints, and human oversight. By combining durable specifications with incremental delivery and measurable validation, teams can make AI-assisted modernization more reliable, controlled, and repeatable.
Modernizing Legacy Software With Spec-Driven Development
Spec-Driven Development gives teams a structured way to use AI in legacy software modernization while preserving business requirements, technical constraints, and human oversight. By combining durable specifications with incremental delivery and measurable validation, teams can make AI-assisted modernization more reliable, controlled, and repeatable.
Massiv vs. Accelerate: Two Paths to High-Performance CPU Computing in Haskell
Programmers commonly use languages like Python, or C/C++ for those seeking higher performance, to handle array manipulation with libraries such as NumPy, SciPy, or deep learning frameworks like TensorFlow. Although Haskell is not a mainstream language, some developers favor its functional paradigm and strong typing. Importantly, Haskell offers its own libraries for high-performance array manipulation. This article will introduce two of the most popular Haskell libraries for this purpose, Massiv
Massiv vs. Accelerate: Two Paths to High-Performance CPU Computing in Haskell
Programmers commonly use languages like Python, or C/C++ for those seeking higher performance, to handle array manipulation with libraries such as NumPy, SciPy, or deep learning frameworks like TensorFlow. Although Haskell is not a mainstream language, some developers favor its functional paradigm and strong typing. Importantly, Haskell offers its own libraries for high-performance array manipulation. This article will introduce two of the most popular Haskell libraries for this purpose, Massiv