AWS-native  ·  Business-specific AI  ·  Fast path to pilot

Know exactly where AI
fits your business.

CARECustom AI Readiness — is a focused assessment that helps your team identify the right AI use cases, evaluate data readiness, and see what business-specific AI can actually deliver, with a clear AWS-aligned path from discovery to pilot.

Your data Your workflows Your priorities Your AWS path
How CARE turns your inputs into a clear AI roadmap
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Your Business Data
CRM, documents, tickets, knowledge bases, product data
CARE Assessment
Custom AI Readiness, data evaluation & trial framing with 4MINDS
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Your AI Roadmap
Use cases, data readiness, AWS architecture, pilot plan
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Full deliverables packageBusiness, data, technical, and roadmap outputs
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4-phase engagementDiscovery through readout in a single structured arc
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AWS-native architectureBedrock, SageMaker, and adjacent services guidance
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Pilot-ready recommendationPrioritized first use case with success criteria
Highlights

Answers the real questions
before you commit.

CARE takes teams from AI interest to a concrete plan — covering where to start, what data to use, and what implementation looks like in AWS.

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Business-first AI discovery

Surface the most practical, high-value use cases based on your actual workflows, pain points, and priorities — not generic AI trends.

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Data evaluation & trial framing

Assess your data sources for readiness and see firsthand how quickly that data can be brought into 4MINDS for a real, business-specific AI trial.

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AWS-aligned architecture

Leave with a high-level implementation path showing how 4MINDS fits your AWS environment — including Bedrock, SageMaker, and adjacent services.

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Roadmap & stakeholder alignment

A sequenced plan covering pilot, MVP, and broader rollout — framed for both business and technical audiences so your team can move forward together.

How It Works

Four phases. One clear outcome.

CARE is a focused, collaborative engagement — not open-ended consulting. Each phase builds directly on the last.

01

Stakeholder Discovery

Align on business goals, technical constraints, current data landscape, and target outcomes for AI.

02

Data & Workflow Review

Assess the inputs, systems, and data sources most relevant to a potential first AI use case.

03

Use Case Shaping

Prioritize opportunities that are high-value and realistic — based on your actual data, context, and constraints.

04

Readout & Recommendations

Deliver findings, architecture direction, and a phased roadmap for moving straight to implementation.

What's Included

A guided working session,
not open-ended consulting.

Business goals & use case prioritizationAlign on the problems worth solving and rank the AI opportunities with the clearest path to value.
Data readiness & trial framingEvaluate your sources for fit, then see how fast that data can be used in a real 4MINDS trial.
AWS implementation directionA high-level architecture path for your environment, including Bedrock and SageMaker guidance.
Stakeholder readout & next stepsDocumented findings and recommendations your team can act on — across business and technical stakeholders.
Why It Matters

From vague AI interest
to a focused, winnable plan.

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Turns curiosity into clarityCARE helps teams stop debating abstract AI ideas and start focusing on concrete, high-value opportunities.
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Aligns stakeholders earlyBusiness and technical teams leave with a shared view of where AI fits, what data is needed, and what comes next.
Accelerates path to pilotRather than dragging through unstructured discovery, CARE gets teams to a real recommendation quickly.
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Ties AI to AWS executionThe output is not just a list of ideas — it’s an AWS-aligned path forward grounded in implementation.
Deliverables

What your team gets
at the end of CARE.

Each section below maps to a concrete output from the assessment. This is meant to leave your team with usable next steps, not just a good conversation.

Executive summary of assessment findings
Prioritized list of recommended AI use cases
Business problem and opportunity mapping
Recommended first pilot motion
Success criteria and value hypotheses
Data readiness evaluation for relevant sources
Review of the inputs needed for an initial 4MINDS trial
High-level 4MINDS and AWS architecture recommendation
Service fit guidance for Bedrock, SageMaker, and adjacent AWS components
Implementation assumptions, dependencies, and constraints
Phased roadmap for pilot, MVP, and broader rollout
Recommended next steps for proof of value
Stakeholder alignment readout
Optional follow-on implementation scoping discussion
Ideal Fit

Best for teams moving from
AI interest to execution.

CARE is particularly useful for organizations that want a clearer view of where custom AI will create value — before they commit to a bigger implementation.

Exploring custom AI for the first time Looking for a practical starting point Already investing in AWS Needing business + technical alignment Validating before a broader build Turning AI interest into a roadmap
Outcome

A clearer view of what business-specific AI should look like in your environment.

By the end of CARE, your team will understand where custom AI can create value, how quickly 4MINDS can work with your data, and what the most practical AWS-aligned path to implementation looks like.

A prioritized first use case
A clear data-readiness view
An AWS-aligned architecture direction
Business, technical, and exec stakeholders in alignment
Get Started

Start with CARE.
Leave with a real plan.

Most AI engagements produce more questions than answers. CARE is designed to do the opposite — leaving your team with prioritized use cases, a data readiness view, and a clear AWS path forward. Qualified teams can move directly from assessment into a live trial.