Understand
Define the intended use, business process and regulatory context.
Validated delivery
Build for regulated environments from the beginning
In Life Sciences, a solution needs to do more than work.
Teams also need confidence that the system, data and processes are controlled, documented and appropriate for how they will be used.
Megnity brings validation considerations into Salesforce, data and AI delivery from the beginning rather than treating them as a final step before go-live.
Intended use
Start with the intended use
Not every system or process requires the same level of validation.
We begin by understanding how the solution will be used, what business processes it supports and where regulated activities may be involved.
This helps determine the appropriate validation approach before development begins.
Built in, not bolted on
Build validation into delivery
Validation becomes harder when it is considered only after a solution has already been built.
We incorporate validation activities into the delivery process so requirements, configuration, testing and documentation develop alongside the solution.
This helps reduce unnecessary work later and keeps business, technology and quality teams better aligned.
Working prototypes
Confirm requirements through working prototypes
Documents alone don’t always show how a process will work in practice.
Where appropriate, we give users an opportunity to review working Salesforce prototypes using sample data before requirements and scope are finalized.
This helps teams identify gaps earlier, confirm what they need and reduce avoidable changes during implementation.
How we govern our own effort
Trace what matters, document what’s proportionate
Traceability
Keep requirements and testing connected
Teams need to understand what was required, what was built and how it was tested.
We help maintain traceability between requirements, solution design and testing so there is a clearer record of how the solution meets its intended use.
The level of documentation and testing is based on the system and the risk involved.
Ownership
Megnity helps prepare and organize the evidence needed to support validation. Your quality unit reviews and approves that evidence and remains responsible for the validation decision under your organization’s procedures.
Risk based
Take a risk based approach
More documentation doesn’t automatically mean better validation.
We focus effort where failure could have the greatest impact and apply controls appropriate to the process and technology involved.
This helps teams maintain the required oversight without adding unnecessary complexity to every change.
Data integrity
Consider data throughout the process
A validated system still depends on reliable data.
We treat data quality, migration, access and integrity as part of delivery, particularly when information is moving between Salesforce, data platforms and other enterprise systems.
Testing can then cover not only whether the system works, but whether the right information moves and behaves as expected.
Beyond one system
Validation has to reach past a single system
Cross-platform
Validate integrations, not just individual systems
Life Sciences processes often cross multiple platforms.
A workflow may begin in Salesforce, use information from another enterprise system and continue through an integration or data platform.
We consider these dependencies when defining the validation approach so the complete business process can be assessed where required.
AI governance
Bring the right controls to AI
AI introduces different considerations from traditional application functionality.
The way information is accessed, generated, reviewed and used needs to be understood before AI becomes part of a regulated or sensitive workflow.
Controls
We help establish appropriate permissions, review points, human oversight and governance around AI-supported processes.
After go-live
Support change after go-live
Validation doesn’t end when a system launches.
Salesforce releases, configuration changes, new integrations and evolving business processes can affect how a regulated system works.
We help teams assess the impact of these changes, identify the testing required and maintain the relevant documentation and evidence through the appropriate change-control process.
This helps organizations continue improving their systems while maintaining the controls required for their validated state.
How we deliver
Our approach
Assess
Identify risk and determine the appropriate level of validation.
Design
Build requirements, controls and validation into the solution approach.
Build
Configure and integrate the solution with traceability in mind.
Test
Verify the functionality, data and relevant business processes.
Document
Maintain the evidence required for the agreed validation approach.
Support
Manage future changes with appropriate controls.
Platforms
Validation that fits the technology and the process
Our validated delivery capabilities can support work across:
- Platform
- Salesforce
- Platform
- Life Sciences
- Data
- Data 360
- Data
- Databricks
- AI
- AI and agent workflows
- Integration
- Integrations and data migrations
The validation approach depends on the intended use, risk and requirements of each environment.
Next step
Building or changing a system in a regulated environment?
Tell us what you’re implementing and how it will be used.
We’ll help you understand how validation can be built into the delivery from the beginning.