In any growing business, finance isn’t just about ticking compliance boxes anymore. It’s about staying in control, spotting trends early, and making confident decisions fast. That’s exactly where financial dimensions in Dynamics 365 Finance come into play. Over the last few months, we’ve seen multiple requirements from businesses asking for smarter use of dimensions. And it makes sense, dimensions are no longer just an optional “nice-to-have.” They’re becoming the backbone of modern financial management, enabling organizations to track performance in ways that directly support decision-making. Think of them as a smarter way to organize your numbers. They give finance teams the flexibility they need to adapt on the fly, and they give leadership the kind of clear, real-time visibility that helps drive better business calls  What Are Financial Dimensions? At the core, financial dimensions are labels you attach to transactions. These labels tell you: So instead of tracking expenses only by account (e.g., Travel Expenses), you can track: All this without creating hundreds of extra GL accounts. Why Should Management Care? Here’s how financial dimensions support strategic and operational goals: 1. Multi-Dimensional Reporting Want to review profitability by region, department, or project? Dimensions let you filter and analyze financial data from multiple angles—without waiting on custom reports. This supports faster decision-making, better forecasts, and more agile operations.  “How much did we spend on marketing in South India last quarter?” You’ll have the answer in seconds. 2. Budgetary Control and Cost Monitoring Dimensions allow finance teams to set up budget controls per department or project. This ensures: Spot overruns before they become problems not after. 3. Cleaner Chart of Accounts Without dimensions, you’d need separate accounts like: This becomes unmanageable. With dimensions, you keep one account (611000 – Travel) and layer in detail using dimensions, keeping your chart lean and reporting rich. 4. Easier Scaling and Restructuring Adding a new business unit, product line, or region? No need to overhaul your chart of accounts. Just add new dimension values. Dimensions give you the structure you need today and the flexibility you’ll need tomorrow. A Practical Example Let’s say you want to understand the true cost of a customer support center in Pune. You can filter all expense accounts with: Immediately, you’ll see: All grouped by those two dimensions without modifying your account structure. Final Word Financial dimensions are not just about slicing data they’re about driving alignment between finance and operations. They: If you’re already using Dynamics 365 or considering it, investing time in defining the right dimensions upfront will pay dividends for years. Planning a D365 Finance rollout or re-implementation? Let’s talk about how to design a dimension strategy that fits your business model. You can reach out to us at transform@cloudfronts.com. 

Why SmartPitch? – The Idea and Pain Point  The idea for SmartPitch came directly from observing the day-to-day struggles of sales and pre-sales teams. Every Marketing Qualified Lead (MQL) to Sales Qualified Lead (SQL) conversion required hours of manual work: searching through documents stored in SharePoint, combing through case studies, aligning them with solution areas, and finally packaging them into a client-ready pitch deck.  The reality was that documents across systems—SharePoint, Dynamics 365, PDFs, PPTs—remained underutilized because there was no intelligent way to bring them together.   Sales teams often relied on tribal knowledge or reused existing decks with limited personalization.  We asked: What if a sales assistant could automatically pull the right case studies, map them to solution areas, and draft an elevator pitch on demand, in minutes?  That became the SmartPitch vision: an AI-powered agent that:  As a result of this product, it has helped us reduce pitch creation time by 70%.   2. The First Prototype – Custom Copilot Studio  Our first step was to build SmartPitch using Custom Copilot Studio. It gave us a low-code way to experiment with conversational flows, integrate with Azure AI Search, and provide sales teams with a chat interface.  1. Knowledge Sources Integration  2. Data Flow  3. Conversational Flow Design  4. Integration and Security  5. Technical Stack  6. Business Process Enablement  7. Early Prototypes  With Custom Copilot, we were able to:  We successfully demoed these early prototypes in Zurich and New York. They showed that the idea worked but they also revealed serious limitations.  3. Challenges in Custom Copilot  Despite proving the concept, Custom Copilot Studio had critical shortcomings:  Lacked support for model fine-tuning or advanced RAG customization.  However, incorporating complex external APIs or custom workflows was difficult.  This limitation meant SmartPitch, in its Copilot form, couldn’t scale to meet enterprise standards.  4. Rebuilding in Azure AI Foundry – Smarter, Extensible, Connected  The next phase was Azure AI Foundry, Microsoft’s enterprise AI development platform. Unlike Copilot Studio, AI Foundry gave us:  Extending SmartPitch with Logic Apps  One of the biggest upgrades was the ability to integrate Azure Logic Apps as external tools for the agent. This allowed SmartPitch to:  This modular approach meant we could add new functionality simply by publishing a new Logic App. No redeployment of SmartPitch was required.  Automating Document Vectorization  We also solved one of the biggest bottlenecks—document ingestion and retrieval—by building a pipeline for automatic document vectorization from SharePoint:  This allowed SmartPitch to search across text, images, tables, and PDFs, providing relevant answers instead of keyword matches.  But There Were Limitations  Even with these improvements, we hit roadblocks:  At this point, we realized the true bottleneck wasn’t the agent itself, it was the quality of the data powering it.  5. Bad Data, Governance, and the Medallion Architecture  SmartPitch’s performance was only as good as the data it retrieved from. And much of the enterprise data was dirty: duplicate case studies, outdated documents, inconsistent file formats.  This led to irrelevant or misleading responses in pitches.  To address this, we turned to Databricks’ Unity Catalog and Medallion Architecture:  You can read our post on building a clean data foundation with Medallion Architecture [Link]   Now, every result SmartPitch surfaced could be trusted, audited, and tied to a governed source.  6. SmartPitch in Mosaic AI – The Final Evolution  The last stage was migrating SmartPitch into Databricks Mosaic AI, part of the Lakehouse AI platform. This was where SmartPitch matured into an enterprise-grade solution.  What We Gained in Mosaic AI:  In Mosaic AI, SmartPitch wasn’t just a chatbot it became a data-native enterprise sales assistant:  From these, we came to know the following differences between agent development in AI Foundry & DataBricks Mosaic AI –    Attribute / Aspect  Azure AI Foundry  Mosaic AI  Focus  Developer and Data Scientist  Data Engineers, Analysts, and Data Scientists  Core Use Case  Create and manage your own AI agent  Build, experiment, and deploy data-driven AI models with analytics + AI workflows  Interface  Code-first (SDKs, REST APIs, Notebooks)  No-code/low-code UI + Notebooks + APIs  Data Access  Azure Blob, Data Lake, vector DBs  Native integration with Databricks Lakehouse, Delta Lake, Unity Catalog, vector DBs  MCP Server  Only custom MCP servers supported; built-in option complex  Native MCP support with Databricks ecosystem; simpler setup  Models  90 models available  Access to open-source + foundation models (MPT, Llama, Mixtral, etc.) + partner models  Model Customization  Full model fine-tuning, prompt engineering, RAG  Fine-tuning, instruction tuning, RAG, model orchestration  Publish to Channels  Complex (Azure Bot SDK + Bot Framework + App Service)  Direct integration with Databricks workflows, APIs, dashboards, and third-party apps  Agent Update  Real-time updates in Microsoft Teams  Updates deployed via Databricks workflows; versioning and rollback supported  Key Capabilities  Prompt flow orchestration, RAG, model choice, vector search, CICD pipelines, Azure ML & responsible AI integration  Data + AI unification (native to Lakehouse), RAG with Lakehouse data, multi-model orchestration, fine-tuning, end-to-end ML pipelines, secure governance via Unity Catalog, real-time deployment  Key Components  Workspace & agent orchestration, 90+ models, OpenAI pay-as-you-go or self-hosted, security via Azure identity  Mosaic AI Agent Framework, Model Serving, Fine-Tuning, Vector Search, RAG Studio, Evaluation & Monitoring, Unity Catalog Integration  Cost / License  Vector DB: external, Model Serving: token-based pricing (GPT-3.5, GPT-4), Fine-tuning: case-by-case, Total agent cost variable (~$5k–$7k+/month)  Vector Search: $605–$760/month for 5M vectors, Model Serving: $90–$120 per million tokens, Fine-Tuning Llama 3.3: $146–$7,150, Managed Compute built into DBU usage, End-to-end AI Agent ~$5k–$7k+/month  Use Cases / Capabilities  Agents intelligent, can interact/modify responses; single AI search per agent; infrastructure setup required; custom MCP server registration  Agents intelligent, interact/modify responses; AI search via APIs (Google/Bing); in-built MCP server; complex infrastructure; slower responses as results batch sent together  Development Approach  Low-code, faster agent creation, SDK-based, easier experimentation  Manual coding using MLflow library, more customization, API integration, higher chance of errors, slower build  Models Comparison  90 models, Azure OpenAI (GPT-3.5, GPT-4), multi-modal  ~10 base models, OSS & partner models (Llama, Claude, Gemma), many models don’t support tool usage  Knowledge Source  One knowledge source of each type (adding new replaces previous)  No limitation; supports data cleaning via Medallion Architecture; SQL-only access inside agent; Spark/PySQL not supported in agent  Memory / Context Window  8K–128K tokens (up to 1M for GPT-4.1)  Moderate, not specified  Modalities  Text, code, vision, audio (some models)  Likely text-only  Special Enhancements  Turbo efficiency, reasoning, tool calling, multimodal  Varies per model (Llama, Claude, Gemma architectures)  Availability  Deployed via Azure AI Foundry  Through Databricks platform  Limitations  Only one knowledge source of each type, infrastructure complexity for MCP server  No multi-modal Spark/PySQL access, slower batch responses, limited model count, high manual development  7. Lessons Learned:  … Continue reading Inside SmartPitch: How CloudFronts Built an Enterprise-Grade AI Sales Agent Using Microsoft and Databricks Technologies  →

In any enterprise application like Dynamics 365 Project Operations, setting up a secure and structured environment is the foundation of a successful implementation. Before diving into projects, resource planning, or billing, it’s critical to configure the environment, establish legal entities, assign the right user roles, and implement appropriate security controls. This article explains how to configure these foundational elements in D365 PO. 1. Legal Entity Configuration A Legal Entity in D365 represents an organization that can enter into legal contracts and is used to segregate financial, operational, and statutory data. Steps to Configure: Why It Matters: Each project in D365 PO must be linked to a legal entity for:  2. User Setup D365 users are authenticated via Azure Active Directory (Azure AD). Once synced, users must be provisioned in the application. How to Set Up: 3. Security Roles & Duties Security in D365 PO is role-based, meaning users get access based on the role(s) assigned to them. Each security role contains duties, which contain privileges. Common Roles in D365 PO: Role Name Purpose Project Manager Manage project planning, time entry approvals Project Accountant Responsible for costing, billing, revenue Resource Manager Manage bookings and capacity Salesperson Handle opportunities and quotes Time/Expense User Submit time and expenses System Administrator Full access, environment config  Assigning Roles:  4. Security Settings & Access Controls Security ensures users can access only what they are authorized to. Key Configurations: Advanced Features: I Hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

In today’s data-driven business landscape, fast, reliable, and automated data integration isn’t just a luxury it’s a necessity. Organizations often deal with data scattered across various platforms like CRMs, ERPs, or third-party APIs. Manually managing this data is inefficient, error-prone, and unsustainable at scale. That’s where Azure Logic Apps comes into play. Why Azure Logic Apps? Azure Logic Apps is a powerful workflow automation platform that enables you to design scalable, no-code solutions to fetch, transform, and store data with minimal overhead. With over 200 connectors (including Dynamics 365, Salesforce, SAP, and custom APIs), Logic Apps simplifies your integration headaches. Use Case: Fetch Business Data and Dump to Azure Data Lake Imagine this:You want to fetch real-time or scheduled data from Dynamics 365 Finance & Operations or a similar ERP system.You want to store that data securely in Azure Data Lake for analytics or downstream processing in Power BI, Databricks, or Machine Learning models. What About Other Tools Like ADF or Synapse Link? Yes, there are other tools available in the Microsoft ecosystem such as: Why Logic Apps Is Better What You Get with Logic Apps Integration Business Value To conclude, automating your data integration using Logic Apps and Azure Data Lake means spending less time managing data and more time using it to drive business decisions. Whether you’re building a customer insights dashboard, forecasting sales, or optimizing supply chains—this setup gives you the foundation to scale confidently. 📧 Ready to modernize your data pipeline? Drop us a note at transform@cloudfronts.com — our experts are ready to help you implement the best-fit solution for your business needs. 👉 In our next blog, we’ll walk you through the actual implementation of this Logic Apps integration, step-by-step — from connecting to Dynamics 365 to storing structured outputs in Azure Data Lake. Stay tuned!

AI-powered agents are quickly becoming the round the clock assistants of modern enterprises. They automate workflows, respond to queries, and integrate with data sources to deliver intelligent outcomes. But what happens when your agent needs to extend its abilities beyond what’s built-in? That’s where Logic Apps come in. In this blog, we’ll explore how you can add functionality to an AI Foundry Agent by connecting it with Azure Logic Apps-turning your agent into a truly extensible automation powerhouse. Why Extend an AI Foundry Agent? AI Foundry provides a framework to build, manage, and deploy AI agents in enterprise environments. By default, these agents can handle natural language queries and interact with pre-integrated data sources. However, business use cases often demand more: To achieve this, you need a bridge between your agent and external systems. Azure Logic Apps is that bridge. Enter Logic Apps Azure Logic Apps is a cloud-based integration service that enables you to: When integrated with AI Foundry Agents, Logic Apps can serve as external tools the agent can call dynamically. Steps to achieve external integrations / extending functionality in AI Foundry Agents with Logic Apps :- 1] Assuming your Agent Instructions and Knowledge Sources are ready, go to your Actions under Knowledge – 2] In the pop-up window, select Azure Logic Apps, you can also use other actions based on your requirement – 3] Here you would see a list of Microsoft Authored as well as our custom-built Logic App based Tools. To be displayed here, for suitable use by the AI Foundry Agent, it should meet a certain criterion as follows – a] Should be preferably on Consumption Plan, b] Should have an HTTP Request Trigger, atleast one Action, and a Response, c] In the Methods, select “Default (Allow all Methods)”, d] And a suitable description in the trigger, e] A Request Body (Auto Generated if created directly from AI Foundry). The developer can either create a Trigger from AI Foundry or, manually create a Logic App in the same Azure Subscription as the AI Foundry Project, observing the criteria. 4] As you can see below, For the scope of the blog I am covering a simple requirement of getting the list of clients for the SmartPitch Project, to fetch the case studies based on it; As you can see, the Logic App Tool meets the requirements for compatibility with Azure AI Foundry, with the required logic between the request and response. 5] As you can see below, For the scope of the blog I am covering a simple requirement of getting the list of clients for the SmartPitch Project, to fetch the case studies based on those;Once the Logic App is successfully created it would be visible in the Logic App Actions; select that Logic App to enable it as Tool. 6] Verify the details of the Logic App Tool and proceed. 7] Next you need to provide / verify the following information –a) Tool Name – The Name by which the Logic App would be accessible as a tool in the Agent, b) Connection to the Agent (Automatically assigned), c) Description to invoke the Tool (Logic App) – This is a crucial part for providing intent to the agent to when and how to use this logic app, and also what to expect from it. “Provide as much details as possible about the circumstances in which the tool should be called by the agent” 8] Once the Tool is created, it would be visible in the Actions list, and be ready for use. Here to check if the Intent is being understood and the tool being called, I have specifically instructed it to mention the name of the tool as well, along with it’s result. As you can see in the screenshot, the tool is triggered successfully, and the expected output is displayed. Example Use Case: Smart Pitch Agent Imagine your sales team uses an AI Foundry Agent (like “Smart Pitch Agent”) to create tailored pitches. By connecting Logic Apps, you can enable the agent to: Which we already have achieved in the in the above AI Agent using the other Logic App Tools The aim is to expose each capability as a Logic App, and the agent calls them as tools in conversation flow. Benefits of This Approach To conclude, by combining AI Foundry Agents with Azure Logic Apps, you unlock a powerful pattern: Together, they create a flexible, extensible solution that evolves with your enterprise needs. I Hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

Accurate and transparent costing and pricing is fundamental to the profitability of any project-based business. Dynamics 365 Project Operations (D365 PO) provides a flexible framework to manage internal cost rates, define sales pricing, and configure billing rules that align with different engagement models such as Time & Material or Fixed Price. In this article, I walk through the key configuration steps and concepts behind setting up costing and pricing models in D365 PO. 1. Understanding Cost & Sales Rates 🔹a. Cost Rate: The cost rate represents the internal cost to the company for using a resource. This can include: Cost rate setup helps track project profitability and perform margin analysis. 🔹b. Sales Price: The sales price is what the customer will be billed for the resource’s effort or service. It can be: This helps manage client expectations and enables accurate invoicing. 2. Setting Up Cost and Sales Price Lists In D365 PO, cost and sales prices are configured through Price Lists.  Steps:  Note: 3. Sales Pricing Models D365 PO supports different pricing models to suit diverse customer contracts: Pricing Model Description Time & Material (T&M) Billing based on actual time and expenses incurred Fixed Price Customer is billed agreed-upon amount regardless of actual effort Milestone-based Invoice generated upon reaching predefined milestones Progress-based Invoicing occurs based on percentage completion Sales pricing rules are linked to contract line details to control how billing is triggered and calculated.  4. Billing Rules Configuration Billing rules define how and when the system should generate invoices. Configuration: Billing rules link directly to project tasks or milestones and automate invoice generation. Example Scenario A customer agrees to a Fixed Price project of $50,000, to be billed across 3 milestones: In D365 PO: When the task is marked complete, an invoice proposal is automatically generated.  Reporting & Impact Proper costing and pricing setup enables: Cost and sales rates feed into Project Actuals, enabling real-time financial tracking. To conclude, costing and pricing configuration in Dynamics 365 Project Operations is a cornerstone of financial control and project success. Whether your business operates on T&M, Fixed Price, or milestone-based models, D365 PO offers the flexibility and automation to manage it efficiently. Through hands-on learning, I now understand how to set up cost rates, sales pricing, and billing rules to support a wide range of project billing scenarios in D365 PO. I Hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

We are pleased to announce that the largest heavy-duty truck manufacturer in North America has partnered with CloudFronts for Phase 1 of a Dynamics 365 ERP implementation. The company is the largest heavy-duty truck manufacturer in North America and a leading producer of heavy- and medium-duty trucks as well as specialized commercial vehicles. Its Gastonia Components and Logistics facility plays a pivotal role in the supply chain, providing stamping, metal fabrication, and sub-assembly of cab and chassis components used across manufacturing operations and aftermarket support. Additionally, the facility oversees line sequencing of parts for manufacturing plants and aftermarket packaging, ensuring efficiency and consistency throughout the production process. The customer is facing several operational challenges due to disconnected systems and limited data visibility. The lack of real-time inventory insights is causing production delays, slowing down planning, scheduling, and work order releases. Teams are burdened with redundant work and manual effort, as legacy systems force them to navigate multiple platforms, leading to inefficiencies and errors. Procurement processes are also impacted, with limited visibility into raw material availability and purchase history resulting in material waste, overstocking, shortages, and purchasing delays.  Phase 1 focuses on implementing Dynamics 365 Supply Chain Management (SCM) to establish the client’s defined end-state capabilities. This phase includes configuring and setting up core business processes such as User & Security Management, Product Information Management, Warehouse Management, Procurement, and other operational setups, which will be further expanded in Phase 2.  On this occasion, Priyesh Wagh, Practice Manager at CloudFronts, stated:   “This engagement marks the beginning of an ERP implementation journey, laying the groundwork for long-term business transformation. At CloudFronts, we are committed to helping our client overcome their complex challenges through technology. By implementing Dynamics 365 Supply Chain Management, we aim to streamline processes, reduce inefficiencies, empower their team with data-driven insights, and build scalable capabilities for future growth.”  About CloudFronts  CloudFronts is a global AI First Microsoft & databricks Solutions Partner for Business Applications, Data & AI, helping teams and organizations worldwide solve their complex business challenges with Microsoft Cloud, AI, and Azure Integration Services. We have a global presence with offices in U.S, Singapore & India. Since 2012, CloudFronts has empowered 200+ global clients small and medium-sized clients all over the world, such as North America, Europe, Australia, MENA, Maldives & India, with diverse experiences in sectors ranging from Professional Services, Financial Services, Manufacturing, Retail, Logistics/SCM, and Non-profits.   Please feel free to connect with us at transform@cloudfronts.com 

As a Business Central functional consultant, I often come across clients who want to stretch the system just a little further than what the standard product offers. And honestly? That’s the fun part of my job, taking a real business problem and making Business Central work for it. Recently, one of our clients came to us with an interesting ask. They were using Projects in Business Central (note: not full-blown Project Operations, since BC’s project functionality is more limited) just to track their internal projects. For them, it wasn’t about billing customers or external reporting, it was about managing their own internal tasks in a structured way. But soon, they hit a snag: “We want task dependencies. Unless Task A is done, Task B should not be editable. And while we’re at it, can we also forecast task timelines automatically?” The Customization: Task Dependency + Forecasted Dates We built a customization with two powerful features: This combination turned their static task list into a dynamic project plan inside Business Central. Why This Feature Made a Big Difference Here are a few ways it improved their day-to-day working: A Small Customization, A Big Win Sometimes, it’s not about adding a huge new module, it’s about adding the right control and visibility at the right place. This customization gave our client confidence that their internal projects would stay on track, with dependencies and timelines automatically adjusting in Business Central. And that’s the beauty of Business Central: it gives you a strong foundation, and with a little tailoring, it can adapt perfectly to your unique business needs. I Hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

Service Management in Dynamics 365 Business Central supports companies that provide after-sales services such as repairs, maintenance, installation, and support. It allows users to manage service agreements, quotes, orders, invoicing, and even loaner equipment, ensuring full control of service delivery and customer satisfaction. This article outlines the entire flow of managing service operations in D365 Business Central—from quote to invoicing and everything in between.  Create Service Quotes A Service Quote is the initial estimate given to a customer before approving or scheduling the actual service. Steps: Once accepted, convert it directly into a Service Order. Create Service Orders A Service Order is used to record and execute the actual service work. Types of Services: Key Components: Once created, the order acts as the central document for planning, execution, and billing. Create Service Invoices or Credit Memos After the service is completed, a Service Invoice or Credit Memo is generated. Invoice: Credit Memo:  Allocate Resources Assign technicians or engineers to perform the work: This ensures the right person is assigned to the right task with visibility for planning teams.  Work on Service Tasks Each Service Order can include multiple Service Tasks: Technicians can: These tasks provide visibility for both field and back-office teams. Service Posting Service Posting involves updating financial and inventory records after service execution. Items/Resources Posted: System ensures all services are financially accounted for and supports audit trails. Post Service Orders and Credit Memos Once the work is completed and verified: Posted documents are archived and accessible under: Lend and Receive Loaners D365 BC allows you to lend temporary replacement items (Loaners) while the customer’s equipment is being serviced. Loaner Process: This boosts customer satisfaction during long repairs and keeps service transparent.  Service Management Features Here are some of the advanced features D365 BC provides in the Service Management Module: Feature Purpose Service Contracts Recurring maintenance or warranty-based agreements Service Items Registers customer equipment and service history Fault/Repair Codes Standardize service documentation Service Pricing Price groups, discounts, and warranty handling Response Time Setup SLAs based on service priority or zone Service Dispatching Schedule and manage field technicians  To Conclude, service Management in Dynamics 365 Business Central enables complete control over the entire lifecycle of customer service, from the initial quote to the final invoice. With integrated features for resource allocation, task execution, inventory tracking, and loaner control, the system enhances service efficiency and customer satisfaction. We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

Budget Control in D365 Finance allows organizations to enforce spending discipline by validating transactions against defined budgets. Here are the steps to set it up. 1. Navigate to Setup Go to: Budgeting > Setup > Budget control configuration. 2. General Settings 3. Define Dimensions Select the financial dimensions to apply budget control against, such as: If Department + Cost Center are selected, every transaction is validated against that combined budget. 4. Approval Rules Determine the actions when a budget is exceeded: 5. Documents & Journals Specify which transactions should be included in budget checks, such as: It is best practice to include unposted documents (e.g., open POs) to ensure commitments are accurately reflected. 6. Activate Once the configuration is complete, activate Budget Control. From this point, all relevant transactions will be validated against the assigned budgets. Example To conclude, budget Control in Dynamics 365 Finance is straightforward to configure but highly effective in preventing overspending. With the right setup, organizations can gain real-time visibility and strengthen financial governance. For Finance consultants, system admins requiring guidance with setup or optimization, CloudFronts can help you design the right Budget Control configuration for your business. Get in touch with CloudFronts Technologies at transform@cloudfronts.com for assistance.