How We Work # We don’t deliver from a distance. We embed. A forward-deployed team works inside your business, with your process owners, in your systems, under your governance, until working AI systems are running in production and your teams own them. It is the engagement path we use to [move AI from pilots to production](https://www.aixccelerate.com/enterprise-ai-execution). This page is about the operating model. For what the first engagement contains, see Discover and Prove. [Talk to Us ](https://www.aixccelerate.com/talk-to-us)[Explore Discover and Prove ](https://www.aixccelerate.com/discover-and-prove) The operating model Your team plus our forward-deployed team, in your environment, one team, one backlog, working AI systems your teams own. Where the work happensYour environment Your team - Sponsor - Process owner - Users and SMEs - IT, data, and security Our forward-deployed team - AI practice lead - Forward-deployed engineers - Architecture and governance One team, one backlog Working AI systems with ownership and operations defined for your teams Our principles ## Five principles we don’t trade away. They decide how every engagement is scoped, staffed, and delivered, and they are why the advice stays honest. 01 ### Strategy and execution together The roadmap and the first working system get built at the same time. No six-month assessment before anything ships. 02 ### Agnostic by design Platform, model, framework, and infrastructure agnostic. We recommend what fits your organization, not what we resell. 03 ### Proof before the big commitment Evidence gates control every investment step. Stopping a weak use case early is a success, not a failure. 04 ### Your environment, your ownership Systems are built inside your cloud, identity, and governance, and handed to your teams to own and operate. 05 ### One accountable owner The same team advises, builds, deploys, and stays. No handoffs between a strategy firm, a dev shop, and an integrator. How we engage ## Working sessions, not steering committees. Forward deployment means the people building the system sit inside the process it changes. Progress is something you use, not something you get reported. Not how we work - An offsite delivery team you never meet - Monthly status decks and steering committees - A big-bang reveal at the end of the engagement - A platform decision forced before the work starts How we work - A forward-deployed team embedded with yours - Working sessions inside the real process and systems - Working demonstrations against an agreed delivery cadence - Technology choices made from evidence, as we build Forward deployment is the delivery model behind this.[See Forward Deployment ](https://www.aixccelerate.com/forward-deployment) Who’s in the room ## You bring the operating truth. We bring the execution. Enterprise AI cannot be delivered outside the organization’s real context. These are the people the work needs, on both sides. ### Your team - 01Executive sponsorOwns the priority and the investment decision - 02Process ownerOwns the workflow the system will change - 03Users and subject-matter expertsBring the operating truth and test the system - 04Technology, data, and securitySet the boundaries the system must respect - 05Operational ownerTakes over running the system after deployment ### Our team - 01AI practice leadershipConnects executive intent to what gets built - 02Forward-deployed engineersBuild and iterate inside your environment - 03Architecture and governanceDesign for production, evaluation, and control from day one One accountable human owner on each side. Governance and evaluation at every step. The path ## One path from priority to production. Evidence earns each step. Every engagement moves along the same five phases. At each gate the honest options are proceed, refine, pause, or stop, schedule alone never advances the work. Discover → Prioritize → Prove → Deploy → Scale First engagementEmbedded execution - 01DiscoverWhere AI can create meaningful value - 02PrioritizeWhich opportunities deserve investment - 03ProveBuild something real, fast enough to matter - 04DeployInto your environment, under your governance - 05ScaleForward-deployed team executes the roadmap At every gate ProceedRefinePauseStop The first engagement ### Discover and Prove Phases 01–03 in one engagement: an AI roadmap and a working Proof of Impact, built at the same time. Scope, deliverables, and participation are detailed there. [Explore Discover and Prove ](https://www.aixccelerate.com/discover-and-prove) Then, if the evidence supports it ### Embedded execution Phases 04–05: the forward-deployed team deploys into your environment, hands ownership to your teams, and scales what production evidence justifies. [Forward Deployment ](https://www.aixccelerate.com/forward-deployment)[Governance and evaluation ](https://www.aixccelerate.com/integration-governance-evaluation) Common questions ## How the model flexes in practice. ### Does every engagement include all five phases? Not necessarily. The starting point and scope depend on what already exists, what evidence is available, and which decision the organization needs to make. The path provides continuity even when the engagement begins partway through. ### Are the phases strictly sequential? They create a clear decision path, but the work is iterative. Findings during build may change the design, and production behavior may refine the operating model. The purpose is disciplined learning, not a rigid waterfall. ### When do security and governance enter the process? At the beginning. Security, privacy, governance, evaluation, and human oversight shape the design and continue through build, deployment, and operation. They are not a review added after the system is complete. ### How does a Proof of Impact move into production? The proof creates evidence, not an automatic production approval. The next decision considers performance, architecture, integration, controls, adoption, support, ownership, and the investment required to operate reliably. ### Who owns and operates the system after deployment? Ownership, access, intellectual property, monitoring, support, incident response, documentation, and change responsibilities are defined for the specific engagement and deployment environment. We do not apply one universal model to every customer. Start with the current constraint ## Where is your AI initiative getting stuck? Bring us the priority, the stalled proof, or the production question. We’ll help identify the next decision and the evidence required to make it. [Talk to Us ](https://www.aixccelerate.com/talk-to-us) --- **Canonical URL:** https://www.aixccelerate.com/how-we-work