Computer System Validation for life sciencesClear evidence. Confident decisions.
Validation, thoughtfully connected

Good systems deserve good evidence.

StitchGx helps life sciences teams plan, execute, and document Computer System Validation—connecting requirements, testing, evidence, and change across the system lifecycle.

Validationone connected lifecycle
01Requirements
02Risk
03Test & evidence
04Review & approve
05Change
From first assessment to ongoing change
Practical expertiseExperienced people, clear validation work
Connected evidenceWork products linked across the lifecycle
Human-led decisionsAI can assist; accountable people decide
The lifecycle

One connected thread of validation work.

Bring the system context, the work performed, and the evidence that supports decisions into a clear, reviewable picture.

01 / UNDERSTAND

Know the system

Establish intended use, boundaries, stakeholders, dependencies, and risk before deciding what validation work is appropriate.

02 / EXECUTE

Do the work

Plan requirements, risk controls, testing, and reviews. Connect relevant development work and test artifacts as they are created.

03 / MAINTAIN

Keep evidence current

Assess changes, resolve gaps, maintain traceability, and make the record easier to review when the system evolves.

What we do

Support where your team needs it.

From a focused assessment to a broader validation engagement, StitchGx works with your people, procedures, and existing systems.

01

System inventory & project setup

Bring system context, intended use, ownership, boundaries, and validation scope into focus at the start of the work.

02

Validation planning & execution

Structure requirements, risk-based testing, evidence, reviews, and reporting around your intended use and quality procedures.

03

Traceability & evidence

Connect development work products, test results, and supporting records to the validation decisions they help inform.

04

Change & lifecycle support

Assess changes, review potential impact, and help teams maintain a clear validation record as systems evolve.

AI, with a clear role

Useful assistance.
Human accountability.

AI can help organize information, draft working materials, and surface possible evidence gaps. It should make the work easier to review—not make validation decisions on your behalf.

“Every suggestion should point back to its source. A qualified person reviews the work before it becomes part of the controlled record.”StitchGx design principle
Source-linkedShow the records behind a suggestion.
Region-awareRespect customer data-processing requirements.
Human-reviewedPeople retain approval and decision authority.
Working together

Start with your process, then make the evidence work.

Good validation is a team effort. We begin with how your systems are used, what your procedures require, and where your current workflow creates friction.

01

Understand the context

System, intended use, stakeholders, risk, and existing ways of working.

02

Agree the plan

Scope, responsibilities, evidence expectations, and practical milestones.

03

Work in the open

Clear status, traceable records, and timely review as work progresses.

04

Leave a usable record

Organized outcomes and evidence your team can maintain after the engagement.

Let’s begin with the work

What does your validation process need to connect?

Tell us about your system, project, or evidence challenge. We’ll start with your context and what your team needs to accomplish.

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