Agentic platform # The foundation for a reliable AI workforce. Give every AI worker trusted knowledge, memory, tools, and controls—connected once across your enterprise. [Talk to Us ](https://www.aixccelerate.com/talk-to-us)[Sign In ](https://app.aiworkforce.md) Work completed · Evidence retained · Outcomes measured ### AI workers Workforce Pre-built Ready roles for sales, support, marketing, and operations. Custom Purpose-built workers for proprietary business responsibilities. ### AIX tools Products Scribe Meeting intelligence Sightline Visual intelligence Canvas Visual thinking The foundation ### One shared platform 01Identity + users 02Integrations 03Parchment 04Agent Mem 05Data + Agent DB 06Tools + skills Permissions · Governance · Evaluation · Observability 01 ### Connect 02 ### Coordinate 03 ### Operate 04 ### Improve Platform capabilities ## One foundation. Every worker. A platform shared across the workforce eliminates duplicated context, fragmented controls, and disconnected point solutions. [ SYS_01 ### Parchment Ground every worker in approved company context, policies, products, and customer knowledge. Explore ](https://www.aixccelerate.com/platform/knowledge)[ SYS_02 ### Tools + systems Connect CRM, email, calendar, ticketing, data, and the operating stack you already use. Explore ](https://www.aixccelerate.com/integrations)[ SYS_03 ### Agent DB Keep operational data structured, permissioned, and ready for action across every workflow. Explore ](https://www.aixccelerate.com/platform/agentdb)[ SYS_04 ### Agent Mem Give authorized agents one durable, portable, permissioned memory through MCP or API. Explore ](https://www.aixccelerate.com/platform/agent-mem)[ SYS_05 ### Evaluation + observability Measure quality, inspect activity, and improve performance before and after deployment. Explore ](https://www.aixccelerate.com/enterprise/governance-evaluation)[ SYS_06 ### Governance Put people, policy, permissions, and approvals in the loop for every consequential action. Explore ](https://www.aixccelerate.com/ai-workforce/security-governance) AIX Core ## Operate the workforce from one place. Configure workers, manage access, connect company knowledge, and inspect performance through a shared enterprise control plane. Workforce dashboard Worker catalog Shared knowledge The definition ## What is an AI workforce? An AI workforce is a group of AI workers that hold defined roles, share one set of company knowledge and controls, and are managed like staff rather than like software. Each worker owns a job and is measured on the output of that job — meetings booked, tickets resolved, proposals out the door — not on how many messages it generated. The word doing the work in that definition is shared. A company running six disconnected AI tools does not have an AI workforce. It has six vendors, six sets of context to maintain, six permission models, and six places for something to go wrong unobserved. An AI workforce means the second worker inherits everything the first one learned about your business, and the tenth costs less to add than the second. This is the part most AI programs skip. They buy capability and skip infrastructure, then conclude the technology was not ready. The technology was ready. Nothing underneath it was. In practice Our own workforce runs seven roles across the revenue motion: - Nick — demand generation - Jules — outbound prospecting - Pepper — inbound response, including voice - Tony — technical selling - Joy — deal operations - George — customer success and retention - Mike — technical L1 support [Meet the workers ](https://www.aixccelerate.com/our-agents) Where the lines are ## AI workforce vs. agents, RPA, and chatbots These get used interchangeably and they are not the same thing. The distinction that matters commercially is not how smart the system is — it is what happens when the system is wrong, and what it costs to add the next one. ApproachScopeMemoryTakes actionWhere it breaks ChatbotAnswers questionsSession onlyNoAnything outside its script RPARepeats fixed stepsNoneYes, rigidlyWhen the screen or form changes AI agentPlans and uses toolsPer agent, isolatedYesAt scale — no shared context or controls AI workforceOwns a defined roleShared and permissionedYes, with approvalsCorrected by policy, not rewrites The economics ## What it costs We price against headcount because that is the budget this replaces. Comparing an AI worker to a software seat is the wrong comparison and produces the wrong decision. $3,000 One-time setup, per worker ~$1,000 Per month, per worker ~$15,000 Total year one, per worker The loaded cost of the human role each worker covers runs $45,000 to $120,000 per year. That gap is the entire argument, and it is why we say we capture headcount budget, not software budget. [Run the numbers for your team ](https://www.aixccelerate.com/calculate-roi) Straight answers ## Common questions What is an AI workforce?An AI workforce is a group of AI workers that hold defined roles, share one set of company knowledge and controls, and are managed like staff rather than like software. Each worker owns a job — outbound, inbound, deal operations, support — and is measured on the output of that job. The defining trait is shared infrastructure: the workers draw on the same knowledge, the same permissions, and the same audit trail, so adding the second worker is cheaper than the first. How is an AI workforce different from AI agents?An AI agent is a single unit of capability. An AI workforce is an operating model. An agent can plan and use tools; it still has no role, no manager, no shared memory with the agent beside it, and no accountability for a number. A workforce adds the parts that make agents usable at scale: defined roles, shared knowledge, permissions, evaluation, and a human in the loop for consequential actions. Most companies that say agentic AI failed for them deployed agents without any of that. Is an AI workforce the same as RPA?No. RPA follows a fixed script and breaks the moment the screen, form, or process changes. An AI worker reasons about the goal, handles inputs it has not seen before, and asks when it is unsure. The practical difference shows up in maintenance: RPA deployments accumulate brittle scripts that need constant repair, while AI workers are corrected by updating knowledge and policy rather than rewriting logic. What does an AI workforce cost?At AI Xccelerate, each AI worker is $3,000 one-time setup plus roughly $1,000 per month. Year one lands around $15,000 per worker. The comparable loaded cost of the human role each worker covers runs $45,000 to $120,000 per year. That is why we describe this as capturing headcount budget rather than software budget — the comparison that matters is against a hire, not against a SaaS seat. How long does it take to deploy an AI worker?Deployment is measured in weeks, not quarters, because the workers are prebuilt for defined roles. The work is not building the worker — it is connecting your systems, loading approved company knowledge, and agreeing what the worker may do without asking. Most of the elapsed time in a deployment is access provisioning and knowledge review on the customer side. What happens when an AI worker gets something wrong?The same thing that happens with a new hire: you find it, correct it, and the correction sticks. Every consequential action runs through permissions and approvals, activity is inspectable, and evaluation runs before and after deployment rather than only at launch. Corrections are made by updating knowledge, policy, or scope — not by editing code. Do AI workers replace employees?They cover work, not people. The pattern we see in practice is teams taking on coverage they could never justify hiring for — following up on every inbound lead, running technical discovery on every deal, keeping CRM records current — rather than removing existing roles. Technology should amplify human capability, not replace human purpose. --- **Canonical URL:** https://www.aixccelerate.com/platform