Agile Delivery for Data & AI Projects
Move faster with a focused, flexible team.
Here’s the problem with traditional fixed-scope projects: requirements change. You learn more as you build, priorities shift, new opportunities appear, and competitors force you to adapt. But every change comes with friction—change orders, timeline resets, and scope debates.
There’s a better way. Our POD (Product-Oriented Delivery) model gives you a dedicated cross-functional team that works your prioritized backlog continuously. You set the priorities, we deliver. No change orders. No scope arguments. Just steady progress toward your goals.
What Is the POD Model?
POD stands for Product-Oriented Delivery, and it’s an agile approach to delivering complex projects where requirements evolve as you learn. Instead of defining everything upfront and locking into a fixed scope, you get a dedicated team that works through your prioritized backlog sprint by sprint.
Think of it like having an internal team, but without the overhead of hiring, managing, and retaining full-time employees. You get experienced data engineers, AI specialists, cloud architects, and DevOps engineers who work exclusively on your projects, guided by a dedicated Scrum Master or Project Manager.
The key difference from traditional projects is flexibility. When you learn something new or priorities change, you simply adjust the backlog. The team adapts immediately without contract renegotiations or change order delays.
The POD Model
How It Works
Component 1
Dedicated Cross-Functional Team
You get a team with all the skills needed for your project—data engineers, AI/ML specialists, cloud architects, DevOps engineers, and a Scrum Master or Project Manager. The team composition matches your needs and can adjust as the project evolves.
This isn’t a shared resource pool where you’re competing for attention. This is your team, dedicated to your projects, learning your business, and building institutional knowledge over time.
Component 2
Customer-Managed Backlog
You own the backlog and control the priorities. You decide what gets built next based on business value, changing requirements, or new opportunities. The team provides input on technical feasibility and effort estimates, but you make the final prioritization decisions.
This gives you maximum flexibility to adapt as you learn. Discovered a better approach? Adjust the backlog. Competitor launched a feature you need? Reprioritize. New data source became available? Add it to the backlog.
Component 3
Daily Standups and Continuous Delivery
The team meets daily to coordinate work, identify blockers, and maintain momentum. You’re invited to participate as much or as little as you want, but you always know what’s happening and what’s coming next.
Work is delivered continuously in short sprints (typically two weeks). You see progress regularly, provide feedback quickly, and course-correct when needed. No waiting months for a big reveal—you get working software every sprint.
Component 4
No Fixed Scope Constraints
Traditional projects lock you into a defined scope. If you want to change something, you need a change order. With POD, there’s no fixed scope—just a backlog that evolves as your needs evolve.
This doesn’t mean unlimited scope or budget. It means flexibility within a defined capacity. You’re paying for the team’s time and expertise, and you direct how that capacity is used.
Component 5
Scrum Master/ PM Included
Every POD includes a dedicated Scrum Master or Project Manager who facilitates the process, removes blockers, and ensures the team operates efficiently. You don’t need to manage the team day-to-day—that’s our job. You focus on priorities and business decisions.
Component 6
North Star Objective
While the backlog is flexible, every POD has a North Star objective—the overarching goal that guides all work. This might be “build a data platform that consolidates customer information” or “implement AI-powered document processing” or “migrate to AWS and modernize applications.”
The North Star keeps everyone aligned on what success looks like, even as the specific path to get there evolves.
Why Choose POD Delivery?
Quick Gains, Rapid Iteration
POD teams move fast because they’re not waiting for approvals, change orders, or contract amendments. When priorities change, the team adapts immediately. When you learn something new, you can act on it in the next sprint.
We’ve seen POD teams deliver more value in three months than traditional projects deliver in six, simply because they can adapt quickly and avoid the delays that come with rigid processes.
Adapt Priorities Without Change Orders
Requirements change. Markets shift. Competitors move. With POD, you can adapt without the friction of change orders and contract renegotiations.
Discovered a better technical approach? Implement it. Business priorities shifted? Adjust the backlog. New opportunity emerged? Add it to the queue. The team adapts seamlessly because flexibility is built into the model.
Highly-Skilled Resources, Tight Backlog Management
POD teams are composed of senior engineers who’ve done this before. They know how to build data platforms, implement AI solutions, and architect cloud infrastructure. You’re not paying for junior resources to learn on your project.
The Scrum Master or PM ensures the backlog is well-groomed, work is properly estimated, and the team operates efficiently. You get maximum value from every sprint.
Daily Communication, Clear Expectations
We build analytics capabilities that help you understand how customers use your product, predict which customers are at risk of churning, identify upsell and cross-sell opportunities, and optimize product features based on usage patterns.
Better analytics lead to better product decisions, higher retention, and increased revenue per customer.
Monthly Engagement, No Surprise Fees
POD engagements are typically structured as monthly commitments with predictable costs. You know what you’re paying each month, and you can adjust or end the engagement with reasonable notice.
No surprise change order fees. No scope creep charges. No hidden costs. Just a predictable monthly investment in a dedicated team.
When POD Makes Sense
Cloud Migrations
Migration Complexity Without the Chaos
Cloud migrations uncover surprises—hidden dependencies, extra refactoring, modernization opportunities. POD adapts as you learn, so you can reprioritize without derailing the plan.
Data & Analytics Projects
Built for Exploratory Data Work
Data projects evolve fast as insights emerge and stakeholders ask new questions. POD lets the team pivot quickly while you keep priorities aligned to the business.
AI/ML Development
Designed for Iteration and Experimentation
AI/ML success comes from testing, learning, and refining—not guessing upfront. POD supports rapid iteration so you can adjust direction without contract friction.
Cloud Modernizations
Modernize Incrementally, Improve Continuously
Modernization isn’t one-size-fits-all—some services get containerized, others go serverless, others get refactored. POD tackles it step-by-step, optimizing as you go.
Ongoing Product Development
A Team That Grows With Your Product
POD gives you a dedicated team that learns your codebase and business over time. You get faster delivery, better continuity, and a true extension of your org.
POD vs. Traditional Fixed-Fee Projects
| Innovative POD | Traditional Fixed-Fee | |
| Flexible backlog that evolves | Scope | Fixed scope defined upfron |
| Continuous delivery every sprint | Delivery | Milestone-based delivery |
| Adjust backlog immediately | Changes | Change orders required |
| Daily standups, continuous engagement | Collaboration | Periodic check-ins and reviews |
| Adaptive planning sprint-by-sprint | Planning | Upfront planning with detailed requirements |
| Shared risk, adapt as you learn | Risk | Client bears risk of wrong requirements |
| Ongoing engagement, adjust as needed | Timeline | Fixed timeline with defined end date |
| Monthly team cost, predictable | Cost Structure | Fixed total cost, change orders extra |
| Complex projects with evolving needs | Best For | Well-defined projects with stable requirements |
What's Included in a POD
Typical POD Composition
A typical POD includes four to eight team members depending on your needs. The exact composition varies by project, but commonly includes:
Data Engineers
Build data pipelines, implement ETL workflows, design data architectures
AI/ML Engineers
Develop machine learning models, implement AI solutions, build intelligent workflows
Cloud Architects
Design AWS infrastructure, implement security and compliance, optimize for cost and performance
DevOps Engineers
Build CI/CD pipelines, implement infrastructure as code, set up monitoring and observability
Scrum Master/Project Manager
Facilitate agile processes, remove blockers, coordinate with stakeholders
Subject Matter Experts (SME)
Provide specialized expertise as needed (security, networking, specific AWS services)
POD in Action
Data Platform Development
A healthcare technology company needed to build a data platform that consolidated patient information from multiple sources. Requirements were unclear at the start—they knew they needed to bring data together, but the specific transformations, quality rules, and analytics requirements emerged as they worked with the data.
A POD team worked through the backlog iteratively, building pipelines for one data source at a time, learning what worked, and adjusting the approach. Over six months, they built a comprehensive data platform that now processes millions of patient records daily. The flexibility of POD was essential because requirements evolved significantly as stakeholders saw initial results.
AWS Migration and Modernization
A financial services company needed to migrate from on-premises to AWS while modernizing applications. The initial assessment identified 50+ applications, but priorities shifted as the migration progressed based on business needs and technical discoveries.
A POD team handled the migration and modernization over nine months, adapting the sequence and approach based on what they learned. Some applications were lift-and-shift, others were containerized, and a few were completely re-architected. The flexibility to adjust priorities and approaches was critical to success.
How POD
Engagements
Work
Engagement Structure
POD engagements are typically structured as monthly commitments. You commit to a team for a defined period (usually three to six months minimum), with the option to extend, adjust team size, or conclude the engagement with reasonable notice.
Pricing is based on team composition and size. A typical POD with four to six team members costs significantly less than hiring those same roles as full-time employees, and you avoid the overhead of recruiting, onboarding, and managing the team.
Getting Started
Starting a POD engagement typically takes two to three weeks from decision to team kickoff. We work with you to understand your North Star objective, define initial backlog items, and assemble the right team for your needs.
The first sprint focuses on setup, discovery, and establishing processes. By the second sprint, the team is delivering working software and making meaningful progress toward your goals.
Ready to Start Your POD Engagement?
If you have a complex Data and AI project with evolving requirements, or if you need ongoing development capacity without the overhead of hiring a full team, POD might be the right model for you.
Let’s have a conversation about your project, your goals, and whether POD makes sense for your situation. We’ll be honest about whether POD is the right fit or if a different engagement model would serve you better.