AgentWorksAgentWorks

Centralize AI · RBAC · Distribute · Govern · Audit

The AI workforce platform forEuropean teams that need control

Centralize every AI agent, workflow, and chat in one workspace. Distribute them to teams with role-based access. Manage budgets at the org, team, or per-user level. Share skills, rules, and knowledge across the organization. EU AI Act ready by design.

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What is an AI workforce platform?

An AI workforce platform is software that lets an organization run multiple AI agents under shared governance, budgets, and access controls — instead of each team running disconnected AI tools. It centralizes the workers (agents), the wallet (budgets), the access policy (RBAC), and the audit log into one workspace.

The problem

Disconnected AI tools break at scale

The most common AI failure mode in 2026 is sprawl. Six tools, six bills, six governance gaps — and no single view of cost, risk, or output quality.

  • Each team buys its own AI tool — 6+ subscriptions, 6+ bills, 6+ governance gaps.
  • No shared identity: every tool has its own login, its own permissions, its own audit log (or none).
  • No centralized budget: finance discovers the AI spend at quarter end, after the fact.
  • No way to enforce EU AI Act controls — risk classification, HITL, audit — across the stack.
  • Skills, rules, and knowledge built in one tool cannot be shared with another.
  • When someone leaves, off-boarding requires hunting through every AI subscription.

With an AI workforce platform

One platform, one audit log, one bill

  • One platform, one bill, one audit log — finance, IT, and legal each see the full picture.
  • Single sign-on with SSO/SAML; revoking a user revokes every AI access in one step.
  • Per-team budgets with live wallet visibility prevent runaway AI spend.
  • EU AI Act risk classification, HITL, and audit logging applied uniformly across every agent.
  • Skills, rules, and knowledge bases are built once and shared across the workspace.
  • Off-boarding is one role-removal click — every agent and tool access goes with it.

Capabilities

What AgentWorks delivers as your AI workforce platform

Eight capabilities that turn scattered AI tools into one governed AI workforce.

One workspace for every AI workload

Chat, AI agents, multi-agent pipelines, knowledge bases, and tasks all live in a single thread. Replace six disconnected AI tools with one governed control plane.

Role-based AI access (RBAC)

Org admins assign roles; roles define which agents, knowledge bases, tools, and budgets each team can use. SSO/SAML group mapping on Enterprise. Every access decision logged.

Agent and workflow distribution

Managers distribute custom or standard AI agents — and entire multi-agent workflows — to specific teams or roles. New hires inherit the right agents on day one.

Centralized budgets — org, team, per-user

One euro wallet for the organization, broken down by team, role, or individual. Set hard limits, soft warnings, and auto top-ups. See live spend per agent run.

Share skills, rules, and knowledge

Build a skill once, share across the workspace. Author a rule for tone or compliance, propagate to every agent. Index a knowledge base, ground every relevant agent on it.

Multi-LLM, no vendor lock-in

OpenAI, Anthropic, Google, Mistral — switch model per turn or per agent inside the same workspace. One wallet. No model markup. No vendor lock-in.

Unified audit log

Every chat turn, agent run, tool call, approval, and access decision in one log. Exportable as JSON or CSV. Designed for the EU AI Act Article 12 record-keeping obligation.

Collaborate with AI agents like teammates

Mention agents with @ inside any chat. Hand work between humans and agents. Run scheduled multi-agent pipelines as a digital team — research → draft → review → publish.

Use cases

Who runs an AI workforce on AgentWorks

  • Marketing teams

    Run content, SEO, and analytics agents under a shared brand-voice rule and a shared knowledge base. Scheduled multi-agent pipeline turns weekly research into published posts. Per-team budget keeps spend predictable.

  • Sales teams

    Lead-research, outreach-drafting, and CRM-update agents with HITL approval before sending. RBAC keeps prospect data scoped to the sales role. Per-rep budgets show ROI per seat.

  • Customer support

    Triage agent classifies inbound tickets; answer-drafting agent prepares responses; human reviewer approves before sending. Audit log captures every ticket touchpoint for QA.

  • Operations & finance

    Invoice-processing, expense-classification, and contract-review agents run on a schedule with EU AI Act-classified risk. Higher-risk decisions wait for controller approval.

  • HR & people teams

    Resume-screening, interview-scheduling, and onboarding agents — with strict RBAC and HITL on candidate-impacting decisions. Audit log preserves evidence for fair-hiring reviews.

  • Agencies & consultancies

    Distribute the same agent stack to every consultant; manage per-client budgets; ship governed AI to clients without giving each one a separate license to manage.

FAQ

AI workforce platform — common questions

What is an AI workforce platform?
An AI workforce platform is software that lets an organization run multiple AI agents under shared governance, budgets, and access controls — instead of each team running disconnected AI tools. It centralizes the workers (agents), the wallet (budgets), the access policy (RBAC), and the audit log into one workspace.
How does AgentWorks centralize AI in my organization?
AgentWorks consolidates 200+ pre-built AI agents, multi-LLM chat (OpenAI, Anthropic, Google, Mistral), multi-agent pipelines, knowledge bases, RBAC, per-team budgets, and a unified audit log into one workspace. Org admins distribute agents and workflows; team managers control budgets; every action lands in one log.
Does AgentWorks support role-based access control (RBAC) for AI agents?
Yes — on Team and Enterprise tiers. Org admins assign roles; each role defines which agents, knowledge bases, tools, and budgets are accessible. SSO/SAML group mappings are supported on Enterprise. Every access decision is logged for the EU AI Act audit log.
Can managers distribute AI agents and workflows to specific teams?
Yes. On Team and Enterprise, managers can distribute custom or standard AI agents and entire multi-agent workflows to specific roles or teams. New hires inherit the right agent stack the moment they get the role.
How do centralized AI budgets work on AgentWorks?
One euro wallet for the organization, broken down by team, role, or individual. You set hard limits and soft warnings; agents automatically pause when a limit is hit. The live wallet shows spend per chat turn or agent run, in EUR — no model markup.
Can I share skills, rules, and knowledge bases across my team?
Yes. Build a skill once and share it across the workspace; author a rule for tone or compliance and propagate it to every agent that needs it; index a knowledge base and ground every relevant agent on the same source of truth. Skills, rules, and knowledge are all first-class shared resources.
Does centralizing AI on one platform reduce vendor lock-in?
AgentWorks reduces lock-in by being multi-LLM (OpenAI, Anthropic, Google, Mistral — switchable per turn) and self-hosted-capable on Azure, AWS, GCP, or IBM Cloud (Enterprise). You centralize on AgentWorks but keep model-vendor and infrastructure choice open.
How does an AI workforce platform support EU AI Act compliance?
EU AI Act compliance requires per-agent risk classification, audit logging, human oversight on high-risk decisions, and PII protection. AgentWorks ships these as core platform features — applied uniformly across every agent, workflow, and chat. Disconnected AI tools cannot enforce EU AI Act controls consistently across the stack.
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