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Data-Ready Blueprint
cloud fronts new logo
Data - Ready BluePrint

AI That Knows Your Business, Not Just Your Technology

CloudFronts runs your AI program, from identifying high-impact use cases to building, deploying, and optimizing AI solutions and agents that deliver measurable business outcomes.

Talk to an Expert About Your AI Program

Your AI Roadmap. Delivered Through a Managed Services Agreement.

Most organizations already have the right technology foundation in place, whether it's Dynamics 365, Azure, Databricks, or other business platforms. The challenge is identifying the AI use cases that deliver real business value and having the expertise to build, optimize, and scale them effectively.

CloudFronts AI Managed Services is a 12-month engagement with a fixed monthly capacity model. We work with you across the entire AI lifecycle, from discovery and use case identification to agent development, deployment, adoption tracking, and continuous optimization. By leveraging your existing applications and data, we help you implement AI solutions that are aligned with business goals, fully scoped, documented, and approved.

Purpose of the AI-MSA

Establish an annual AI Managed Services model where CloudFronts partners with you across the full AI lifecycle

Identify & Prioritize

Discover and rank high-impact AI use cases aligned to business goals.

Design & Build

Architect, prototype, and configure AI agents for customer applications.

Deploy & Support

Production deployment with managed support within agreed monthly hours.

Continuously Improve

Iterative tuning, adoption tracking, and enhancement of approved AI solutions.

Every engagement phase is included within your fixed monthly hours — from the first workshop to production monitoring.

THE AI-MANAGED SERVICES AGREEMENT

One Contract. Every Stage of AI.

Start with the right use cases
We look at your business, talk to your team, and identify AI use cases that directly address your business challenges outright. We then take on other use cases which collectively improve operational efficiencies. When an organization reaches this stage: every AI effort connects to a clear business goal.
We build it in your environment
We design the AI agent, set it up in your Azure AI Foundry or Databricks, and connect it to the data sources it needs. Every use case gets its own design document before we implement it. You sign off before we build. Each AI use case goes through a discovery, prototyping and implementation cycle: what we are building, the data involved, the acceptance criteria, and governance around it
Deploying an Agent isn’t completiont
We put the agent into production and scale it to desired success. Your monthly hours cover ongoing support, critical issue response, and weekly check-ins. If something breaks, we fix it. Monday to Friday, during your business hours for anything critical. Critical issues are covered the same day. Non-critical issues are handled during India business hours.
Build, Use & Improvise
We track adoption of the Agent and share in weekly updates. If they are not up to the mark, we investigate and help your team adopt it with confidence. We keep a live improvement backlog and tune the agent every month based on real usage data. 10% of monthly hours go to project management, backlog grooming, and governance every month
Improve Over Time / Adoption and Iteration
We track adoption of the Agent and share in weekly updates. If they are not up to the mark, we investigate and help your team adopt it with confidence. We keep a live improvement backlog and tune the agent every month based on real usage data. 10% of monthly hours go to project management, backlog grooming, and governance every month
Testing & Evaluation Pack
Sample prompts, UAT scripts, acceptance scenarios, defect log, and remediation notes.
User Guide & Admin Runbook
End-user guide for the agent plus admin/support runbook for triage.
Knowledge Transfer Sessions
Training for business users, administrators, and customer project owners.
Optimization Backlog
Managed backlog for tuning, enhancements, adoption feedback, and iterative improvements.

WHAT YOU GET

Every Approved Use Case Includes

Discovery & Prioritization Pack

Business challenge definition, process mapping, and risk classification, documented in a signed-off Functional Requirements Document (FRD).

Agent Design Document

Intended use, inputs/outputs, systems, human review checkpoints, assumptions, exclusions.

Configured AI Agent

Hosted in Azure AI Foundry or Databricks, ready for output generation.

Connectors & Integrations

Approved knowledge sources, orchestration configuration for the agreed use case

Testing & Evaluation Pack

Sample prompts, UAT scripts, acceptance scenarios, defect log, and remediation notes.

User Guide & Admin Runbook

End-user guide for the agent plus admin/support runbook for triage

Knowledge Transfer Sessions

Training for business users, administrators, and customer project owners.

Optimization Backlog

Managed backlog for tuning, enhancements, adoption feedback, and iterative improvements.

Prompt & Guardrail Config

Prompting, grounding, workflow, and guardrails. Prompt training via UAT with user guides and tutorials.

CLOUDFRONTS APPROACH

A Structured, Outcome-Driven Delivery

CloudFronts follows the same delivery approach for every engagement: structured discovery, documented use cases, and platform-native deployment in your own environment.

Structured Requirements

We run structured discovery sessions with your team. Every use case is defined with a signed Functional Requirements Document before anything gets built.

Stakeholder and Process Alignment

We get business and technical stakeholders aligned on what the Agent does, what it reads, and where a human needs to review the output.

Deep Discovery Using CloudFronts Blueprints

We use proven delivery blueprints to cut build time and reduce risk. Every agent is documented, tested, and handed over with full runbooks.

Acceptance Criteria

Based on agreed deliverables, successful deployment, test completion, and documentation delivery. Not withheld due to variable AI outputs.

Outputs Are Preliminary

AI-generated content is draft material only, not final or authoritative results.

Benefits Are Intended

Productivity and efficiency gains depend on data quality, user adoption, process adherence, permissions, and third-party platforms.

Human Review Required

Customer and end users must review, validate, and approve all outputs before operational, legal, financial, or compliance use.

WHY CLOUDFRONTS

A Trusted Partner for Your AI Program

We don't just explain where AI can take your business- we help you get there

Proven execution across mid-sized enterprises

We have delivered AI programs for businesses like yours. We understand the common challenges and how to avoid them.

Deep experience with Azure, Power BI, and data integration

Certified Microsoft Solutions Partner with hands-on Databricks experience. Your agents run on platforms your teams already know.

Know Where You Stand. Know What Comes Next.

Whether you are building your first AI agent or scaling across the business, CloudFronts helps you move forward with clarity.

Talk to an Expert

FREQUENTLY ASKED QUESTIONS

Everything You Need to Know

What is an AI-MSA and why does it matter?

It is a 12-month managed services contract where CloudFronts handles your AI program end to end. Instead of one-off projects, you get a continuous engagement that builds, launches, and improves AI use cases over time. That matters because most one-off AI builds are lost after the prototyping phase.

What platforms and technologies does CloudFronts use?

We build on Azure AI Foundry and Databricks. All agents are deployed in your own environment. You own everything we build reliable data before scaling predictive or prescriptive AI use cases. We also help enable your AI implementation on AI agents on ChatGPT. and Claude .

How do you ensure data quality and trust throughout the lifecycle?

We start every engagement with a data and process assessment. If data quality issues exist, we flag them in the discovery pack and agree on what is in scope to fix before we build anything.

How do you manage security and governance across the data platform?

We work within your existing security that your applications have in place. You maintain data classification, retention policies, and access controls. If a use case involves regulated or sensitive data, we flag it and agree on additional controls before building.

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