Only 29% of organizations see significant ROI from generative AI, despite widespread deployment and investment, according to Writer’s 2026 Enterprise AI Adoption Survey. This underscores that while interest in AI is high, many companies are overwhelmed by too many ideas and lack a clear process to identify which projects will actually move the business forward. A new five-product AI suite from Mission Cloud, a CDW company and U.S.-based Amazon Web Services (AWS) Premier Tier Services Partner, is designed to fill this gap and give leadership teams a structured, business-focused approach to AI with the right information, the right people in the room, and a clear path to ROI.
Designed “to take organizations from strategy to working software,” Mission Cloud’s five complementary AI offerings include AI on Mission (AIM), Quick 5x5x5, AI Landing Zone, the Fixed-Fee Chatbot MVP, and Agent-Enabled Chatbot Limited Pilot. “Together, these solutions give organizations a clear, sequenced path from identifying where AI belongs in their business to having a production-ready AI solution up and running,” said the company.
AIM serves as an entry point to the suite. Powered by the AWS AI Roadmap Prioritization (AIR) workshop, AIM is a 90-minute session that helps leadership teams identify and prioritize AI use cases tied to specific business objectives. Sessions are built for cross-functional leadership teams and require no prior AI or technical experience. A dedicated Mission Cloud Solutions Architect facilitates each engagement, with the goal of having participants leave with a prioritized AI roadmap aligned to their business goals.
“AWS built a rigorous framework for helping organizations think clearly about AI investment with AIR,” said Ted Stuart, President and COO at Mission Cloud. “What we’ve built around that framework is a session where any leader, regardless of their technical background, can walk in, think freely about the possibilities, and leave with a concrete plan.”
For organizations whose AIM roadmap points toward AI-powered analytics and automated decision workflows, Mission Cloud’s Quick 5x5x5 offers an on-ramp. The engagement is a fixed-scope, partner-funded five-day sprint that stands up Amazon Quick for five business users, using five data connectors, and delivers a working AI-searchable knowledge base, custom chat agent, and one automated workflow per user.
For organizations ready to move beyond strategy and into production, Mission Cloud’s Fixed-Fee Chatbot MVP delivers a working, AWS-native conversational AI solution in three weeks at a firm fixed price. Built inside the customer’s own AWS environment and grounded in their data via RAG-powered knowledge search, it is a production-ready system. The customer owns the data, the infrastructure, and the controls from day one, with no per-seat licensing fees and no lock-in on the underlying model. The architecture is designed to support flexibility across available models, so organizations can evolve their AI strategy as the technology matures. When their AI needs grow, they build on infrastructure they already own.
For organizations ready to move from AI that answers questions to AI that completes work, Mission Cloud’s Agent-Enabled Chatbot Limited Pilot builds on the Fixed-Fee Chatbot MVP foundation to add agentic capabilities. Up to two agents connect to backend systems via API and complete defined workflows, designed to require human approval on write actions. The engagement includes a consultative scoping phase before build begins and delivers a validated proof of concept in six weeks, with a clear path to full production deployment.
For organizations that are serious about moving AI agents into production, Mission Cloud’s AI Landing Zone is the infrastructure those agents run on: a deployable, purpose-built environment aligned to AWS best practices for security, observability, cost governance, and application delivery. Every agent Mission deploys for a customer runs on this foundation, which means customers get consistent, auditable, production-grade AI operations rather than one-off deployments that fragment and break at scale.
