Start with the business problem,
not the technology

AI and data can create real business value, but only when there is a clear reason for using them.

Megnity helps organizations identify where data and AI can make a practical difference, understand what needs to be in place and turn the right opportunities into a plan for delivery.

For Life Sciences organizations, we also consider the compliance, governance, validation and human oversight required from the beginning.

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Where to start

Find the opportunities worth pursuing

Not every process needs AI.

We start by understanding where teams are losing time, where information is difficult to use and where better data could improve a decision or workflow.

From there, we help identify opportunities where AI, analytics or better-connected data can create meaningful value.

What we look for
  • Where teams are losing time
  • Where information is difficult to use
  • Where better data improves decisions

Data readiness

Understand whether your data is ready

AI depends on the information behind it.

Before choosing models or building agents, we look at where the required data lives, how reliable it is, who can access it and how it needs to connect.

This helps identify gaps that need to be addressed before the organization invests further.

Explore data engineering and analytics

Data readiness check

  • Where the data lives Ready
  • How reliable it is Partial
  • Who can access it Partial
  • How it needs to connect Gap

Gaps identified before further investment

Prioritization

Prioritize the right use cases

A long list of AI ideas isn’t a strategy.

We help evaluate potential use cases based on business value, feasibility, data readiness, risk and the effort required to put them into everyday use.

This gives teams a clearer way to decide what to pursue now, what needs more preparation and what isn’t worth pursuing.

Evaluated on

Business valueFeasibilityData readinessRiskEffort to deploy

Sorted into

  • Pursue now 3
  • Needs more preparation 2
  • Not worth pursuing 1

Each idea sorted by the criteria above · illustrative

Roadmap

Turn priorities into a practical roadmap

Identifying an opportunity is only the beginning.

We help teams understand what it would take to deliver each use case, including the data, technology, integrations, people and controls involved.

For Life Sciences organizations, that could mean evaluating AI-assisted medical inquiries, improving HCP engagement or connecting information across commercial and clinical systems.

The outcome is a clearer understanding of what can move forward, what needs preparation and where investment is likely to create value.

Delivery path

  1. Understand Identify the business problems, priorities and people involved.
  2. Assess Review existing data, systems, processes and readiness.
  3. Prioritize Select opportunities based on value, feasibility and risk.
  4. Design Define the data, technology, governance and delivery approach.
  5. Prove Test the most valuable ideas with focused use cases.
  6. Scale Take successful use cases into everyday business processes.

From strategy to delivery

Take the next step with the right partner

Megnity works across Salesforce, Data 360, Databricks and Claude.

We help teams move from identifying opportunities to building and supporting solutions, with the right expertise, technology and delivery approach.

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A practical starting point for implementation

  • A prioritized shortlist of use cases
  • An assessment of data and technology readiness
  • Key risks, dependencies and governance considerations
  • A phased implementation roadmap
  • An initial business case to support decision-making

The right approach

Define where AI fits

Sometimes the answer is an AI agent.

Sometimes it is better analytics, automation, integration or simply making existing information easier to access.

We help determine the right approach based on the problem rather than beginning with a predetermined technology.

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Matched to the problem

  • An AI agent Selected
  • Better analytics Available
  • Automation Available
  • Integration Available
  • Easier access to information Available

The approach follows the problem · illustrative

Data foundation

Build the data foundation

Useful data may sit across Salesforce, enterprise applications, data platforms and specialized business systems.

We help define how that information should be connected, governed and made available for analytics and AI.

Our work can bring together technologies including Salesforce Data 360 and Databricks as part of the wider data environment.

Explore our platforms
Reporting · Analytics · AI
Salesforce
Data 360
Databricks
Enterprise applications and business systems

Governance

Plan for governance from the beginning

Questions around access, security, data use and human oversight become more important as AI moves closer to business processes.

We help define who can access information, where AI can be used, where review is required and how the organization maintains appropriate control.

Explore validation and compliance

Decided up front

  • Who can access information
  • Where AI can be used
  • Where review is required
  • How control is maintained

For regulated environments, validation and traceability can become part of the strategy

Strategy to delivery

Move from strategy to something people can use

A strategy document has limited value if it never reaches the people doing the work.

We connect strategy with delivery so the priorities identified can move into prototypes, implementation and production when the organization is ready.

This also gives teams an opportunity to learn from early use cases before expanding further.

From strategy to everyday use

  1. Strategy Plan The prioritized use cases and roadmap.
  2. Prototypes Prove The most valuable ideas tested first.
  3. Implementation Build Delivered into the real environment.
  4. Production Run In everyday use, learning before scaling.

Wider environment

Strategy that connects to the wider technology environment

The goal isn’t to introduce all of them.

It’s to determine what the business actually needs and how the pieces should work together.

  • Salesforce and Data 360
  • Databricks
  • Claude
  • Agentforce
  • Enterprise data and applications
  • Analytics and reporting
  • Integration
  • Governance and validation

Deliverables

What you take away

Our AI and data strategy work helps teams move from a list of possibilities to a practical plan.

The goal is to give your team the clarity to decide what to pursue, what needs preparation and what comes next.

Depending on the engagement, this can include:

  • A prioritized shortlist of AI and data use cases
  • An assessment of data and technology readiness
  • Key risks, dependencies and governance considerations
  • A phased implementation roadmap
  • An initial business case to support investment decisions

Where to begin

Have plenty of AI ideas but aren’t sure where to start?

Tell us what you’re trying to improve and what your current data and technology environment looks like. We’ll help you identify the opportunities worth taking forward.

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