Platform and Architecture # Years of practice, hardened into building blocks. Knowledge, memory, data, files, skills, identity, integrations, and orchestration are composed as reusable building blocks. That structure helps teams avoid rebuilding the same foundation for every agent or worker. Environment, ownership, controls, and operating responsibilities are scoped with your team. [Discuss the architecture ](https://www.aixccelerate.com/talk-to-us)[Explore the AI Workforce ](https://www.aixccelerate.com/ai-workforce) The stack Interaction (text · voice · vision · meetings) → AI workers and agents → the AIX building blocks, our IP → swappable models → your cloud. Governed, observed, and evaluated end to end. The stackGoverned · observed · evaluated Interaction: in and out Text · Voice · Vision · Meetings What gets built AI workers and task agents: with humans in the loop The AIX building blocks: our practice, our IP IdentityKnowledgeMemoryAgent DBSkillsScribeIntegrationsOrchestration Models: your choice, swappable Providers selected and verified per use case AIX Core + Enterprise SSO: Clerk · WorkOS The backbone every block plugs into Target environment Selected with your architecture and security teams Observability · evals · guardrails · human in the loop, across every layer The building blocks ## Eight blocks, one backbone. Our IP. These are not features on a pricing page. They are the foundational structure we assembled over years of building AI workers for real organizations. Centralized knowledge, centralized memory, a centralized skill library: every worker inherits them instead of starting over. 01 ### Identity and access Worker identity, scoped permissions, and attribution, with enterprise SSO as a module (Clerk, WorkOS) 02 ### Knowledge: Parchment Governed company knowledge and wiki. Write it down once; every worker reads it 03 ### Memory: Agent Mem Memory that persists: what a worker learned, decided, and was told 04 ### Agent DB The database and file system for agents: structured records, workflow state, and governed files and documents 05 ### Skills library Centralized, reusable capabilities, built once, governed, shared across workers 06 ### Meeting Intelligence: Scribe Joins and captures meetings: the tribal knowledge conversations create 07 ### Tools and integrations MCP, APIs, webhooks, and connectors selected and verified for the engagement 08 ### Runtime orchestration Agentic frameworks in production: LangChain, LangGraph, Deep Agents, Claude Agent SDK, OpenAI Agents SDK, plus triggers, state, handoffs, and sandboxes for agents that run code AIX Core: the backbone every block plugs into Identity · permissions · platform Deployment options assessed per engagementMicrosoft AzureAWSGoogle CloudCloudflareVercelRailway Enterprise SSO moduleClerkWorkOS Overarching observability and evals. Every block, every worker, every action is measured, so you know it is going correctly, and can prove it. Human in the loop, by design. Strong guardrails and review, approval, and escalation paths are part of the structure, not an add-on. What the blocks buy you ## Two kinds of systems build on the same foundation. A reusable foundation can reduce duplicated work. Delivery timing still depends on scope, data, integrations, security review, validation, and operating readiness. ### AI agents for tasks Bounded, single-task agents assembled from the blocks, research, triage, drafting, data work, deployed where the org-scan says they belong. [The three levels ](https://www.aixccelerate.com/ai-workforce) ### AI workers Full roles by our definition: multi-agent, multimodal systems governed by a job description, reporting to a human manager. [The role methodology ](https://www.aixccelerate.com/ai-workforce/roles) ### Model changes become an evaluated architecture decision. The blocks are model-agnostic: OpenAI, Anthropic, Google, or open source, chosen per use case. A new model is a swap, not a rebuild, knowledge, memory, skills, integrations, and governance all stay put. Agents that need to execute code run in governed sandboxes under the same controls. How workers show up ## Text, voice, and vision, in and out. Workers meet your business where it already communicates: they read and write email and chat, take and make phone calls, understand documents and screens, and join the meetings your teams are already in. ### Text Email · chat · documents ### Voice Phone calls · voice interaction ### Vision Documents · screens · images ### Meetings Teams · Google Meet · Zoom The integration layer underneath: MCP, APIs, webhooks, and available connectors, verified against the systems, permissions, and controls in scope. MCPAPIsWebhooks1000s of connectors Deployment and ownership ## Scoped to your environment and operating model. Putting the blocks into your infrastructure accelerates your organization's ability to build agents and workers, without handing your AI capability to a vendor. 01 ### Environment scoped with you Infrastructure, network boundaries, identity, controls, and hosting responsibilities are selected for the engagement. 02 ### Run together Operating responsibilities are defined with your team so ownership and knowledge transfer are explicit. 03 ### Ownership made explicit Deployment assets, portability, support, and exit responsibilities are documented in the agreement. Deploys onMicrosoft AzureAWSGoogle CloudCloudflareVercelRailwaywith enterprise SSO viaClerkWorkOS The models are rented. The clouds are yours. The practice of putting it all together. That is what we bring. Common questions ## What architects and platform teams ask. ### Do we need to adopt the platform before working with AI Xccelerate? No platform-first decision is required. The blocks are applied where they make delivery faster, the engagement starts with the business priority, not a platform sale. ### Which models and providers are supported? The architecture is designed to allow model choice. Provider compatibility, migration effort, data handling, and evaluation requirements are verified for each use case. ### Does the platform replace our systems of record? No. It connects workers to the systems and context their roles require. Your systems of record stay the systems of record, workers read from and write to them under scoped permissions. ### Can workers connect to any enterprise system? No universal connector claim is made. MCP, APIs, webhooks, and available connectors are evaluated against the target system, permissions, security requirements, and operating constraints. ### Where does the platform run and who owns it? Infrastructure, identity, governance, asset ownership, portability, and operating responsibilities are defined per engagement. ### What about agents that need to execute code? Agents can run inside governed sandboxes, isolated runtimes for code execution and similar work, with the same observability, evaluation, and human-in-the-loop controls as everything else. Bring your architects ## Map the blocks to your target environment. Bring your infrastructure, identity model, and governance requirements. We’ll walk the architecture, verify the relevant dependencies, and define what responsible delivery requires. [Discuss the architecture ](https://www.aixccelerate.com/talk-to-us) --- **Canonical URL:** https://www.aixccelerate.com/platform