How we're different.

Most of the delay in enterprise software isn't the coding. It's waiting on access and environments, handoffs between teams, and ambiguous requirements addressed months later. Here is how we take each of those out: how we deliver, where we build, and who does the work.

  1. How we deliver
  2. Where we build
  3. Who does the work
A MadeLabs engineer points at a laptop screen while Adam Broadbent and Nicholas Barger follow along in the MadeLabs office
Working through a change together in the MadeLabs office

Enhanced Delivery

Most of the delay isn't the coding. It's waiting, and rework found late. Pick a phase to see what changes.

Delivery phases

Traditional

With MadeLabs

Selected phaseOther phases

Requirements

The usual way

Every requirement goes into a spec up front, then gets handed over. Unclear requirements can surface months later, in user acceptance testing.

The MadeLabs way

We start from your code and your RFP or PRD and build a prototype before kickoff. Then a two-day on-site: day one walks through your current process, day two the new one, with the prototype changed live in the room.

Any unclear requirements surface on day one, not in UAT.

From real work

At a recent on-site, the business corrected a field from “transportation method” to “delivery method.” It was fixed in the prototype, in the room, in minutes.

Design

The usual way

Static mockups are handed from design to engineering, then reinterpreted.

The MadeLabs way

Design happens in the working prototype, and a senior engineer sets the architecture before the first feature.

What you approve is what gets built.

From real work

On a recent project, we built the prototype from the client’s PRDs with their own component library. Their business users reviewed screens that looked and worked like the finished application.

Build

The usual way

Weeks go to waiting on environments, access requests and shared test systems.

The MadeLabs way

A small senior team builds in our lab, set up to match your environment, with Claude Code and our own agents and checks. Work arrives as pull requests.

AI-generated code is peer-reviewed by an engineer.

From real work

On a recent project, a working version ran in our lab within four weeks of kickoff.

Test

The usual way

Manual QA happens at the end, and slow or flaky test suites get skipped.

The MadeLabs way

Tests are written alongside the code and run on every change.

Problems are caught while the code is fresh, not in a test phase at the end.

From real work

On a recent project, tests ran on every change. The result was the application’s first release with no defects.

Release

The usual way

Change boards, tickets to operations and release weekends.

The MadeLabs way

Releases go through your own pipeline and your own review.

Your controls apply where code enters your environment.

From real work

On a recent project, each pull request went live when it was approved. Feature flags and deployment gates protected each change, and no release waited weeks for approval.

Feedback

The usual way

Feedback arrives quarterly, by survey or support ticket.

The MadeLabs way

Monitoring and real user behavior feed straight into the next iteration.

Each loop removes a step or prevents an error.

From real work

On a recent project, Sentry reported the same error more than once. An agent triaged it and opened a pull request with a fix. An engineer reviewed the fix and merged it.

Build in our lab, ship in yours

Lab is in our name. It’s where we make things: production-quality software, built fast, outside the queues and access rules that slow work down inside a company. Then it enters your systems the way everything else does, through your own review. Here are the two ways, in under a minute.

The usual way

  1. A vendor team moves in and starts by asking for access.
  2. Laptops, environments and approvals come one at a time, and the build stops for each.
  3. To work inside, they need accounts on your systems, so your controls loosen or the project slows.
  4. Everything lands in one big merge near the end. Then the rework starts.

In the MadeLabs lab

  1. Lab is in our name. It's where we make things, in a working copy of your environment.
  2. We build from day one, at production quality, with none of your internal queues in the way.
  3. We don't need accounts on your systems while we build, so there is far less to secure.
  4. We don't save integration for the end. Small changes reach your real pipeline from the first weeks.
  5. Senior engineers work with AI tools, automations and models in our own process, so the work is faster and more reliable.
  6. Every change enters your company as a pull request, approved by your reviewers under your controls, unchanged.
  7. At the end you own all of it: the code, the infrastructure, the pipeline, the tests and the docs.

Built in our lab, proven against your systems early, approved by your people, owned by you.

On a recent project, a working version ran in our lab within four weeks of kickoff.

A Team that Executes

AI changes how many people a project needs, and who they should be. You work directly with the people doing the work.

Traditional Development

  • Account manager
  • Project manager
  • Business analyst
  • Architect, part-time
Developers, often rotating
  • Separate QA team

The MadeLabs Way

  • Product specialistWorks with your business directly
  • Lead engineerArchitecture and technical direction
  • EngineerBuilds, tests, documents
  • EngineerBuilds, tests, documents

Every name known before work begins, and the same team throughout.

Who you talk to

The usual way

An account manager, who relays to a project manager, who relays to the team.

The MadeLabs way

The people doing the work.

Requirements

The usual way

An analyst writes a spec, and developers interpret it later.

The MadeLabs way

The product specialist works with your business and turns what they need into a backlog the team builds from.

Quality

The usual way

A separate QA team finds the problems near the end.

The MadeLabs way

Owned by the whole pod, every day. Tests are written with the code, human reviewed before hitting production.

Where AI fits

The usual way

Bolted on, or banned, depending on the developer.

The MadeLabs way

Built into the pod from the ground up. AI does much of the code writing; people own accountability of the quality and outcome that ships.

Continuity

The usual way

People rotate on and off, and each change costs you ramp-up time.

The MadeLabs way

The same people from the first day to the last. What they learn about your business stays on your project.

Tell us what technology needs to do for your business

Prefer to talk now(888) 369-1330
  1. We reply within one business day.To set up a first conversation.
  2. We listen first.The goal, the constraints and the timeline.
  3. We give you a plain recommendation.Where we'd start, and why.