AI that acts, not just answers. With every action anchored. With the EU AI Act documentation generated automatically.
The conversational AI deployment was the warm-up. The agentic deployment is the production scale-up.
The agent doesn't just answer the question — it routes the claim, opens the contract, triggers the workflow, updates the record, schedules the follow-up. Every action is an action your company is responsible for. The auditor's question becomes: what was the agent allowed to do, what did it actually do, and how do you prove the difference 6 months later?
TeamSync's agentic surface answers the question by architecture. The agent's tool surface is defined declaratively by your business rules. The agent can't take actions outside the surface — not because it's instructed not to, but because the actions aren't reachable. Every action — successful or refused — is anchored to the audit chain. The EU AI Act Article 11/13/14 documentation is generated from the chain.
Talk to the AI solutions team · Read the agentic workflow pillar · See the Chief AI Officer page
What's in the agentic surface.
| Sub-capability | What it does |
|---|---|
| Agent designer | Define the agent's purpose, the tool surface, the human-in-the-loop checkpoints |
| Tool surface enforcement | Business rules declare which actions the agent can take; platform enforces |
| Bounded retrieval | Every retrieval bounded by the user-on-whose-behalf the agent is acting |
| Action logging | Every action — attempted, successful, refused — anchored to the audit chain |
| Human-in-the-loop checkpoints | Configurable review gates at risk thresholds you set |
| Multi-agent orchestration | Agents that hand off to other agents under explicit policy |
| EU AI Act documentation generation | Articles 11/13/14 documentation generated from the audit chain |
| Performance monitoring | Agent effectiveness, refusal rate, escalation rate |
What "bounded autonomy" actually requires.
Most agentic frameworks rely on prompt engineering to keep the agent inside the lines. That works for the demo. It doesn't survive the regulator's review.
| Stage | Standard agentic frameworks | TeamSync |
|---|---|---|
| Tool surface | Prompted, hopefully respected | Declared in business rules; platform-enforced |
| Permissions | Often the agent's own; not the on-behalf-of user's | The on-behalf-of user's, at every action |
| Audit per action | Optional; varies by framework | Native; every action anchored |
| Human-in-the-loop gates | Application-layer | platform-layer; can't be bypassed |
| EU AI Act documentation | Manually constructed | Generated from the audit chain |
| Multi-agent handoff | Application-managed | platform-managed under policy |
The CISO's review for production agentic deployment depends on every one of these being structural, not procedural.
What an agent looks like in practice.
Consider a claims-triage agent. The shape:
| Element | Configuration |
|---|---|
| Purpose | Triage incoming claims into routing categories |
| Tool surface | Read claim documents in the user's queue; classify against the taxonomy; route to the correct claims handler; escalate to a human reviewer above $X claim value |
| Bounded retrieval | The agent reads only documents the on-behalf-of user can see |
| Human-in-the-loop | All claims above $X value require human approval before routing |
| Audit anchor | Every retrieval, every classification, every routing, every escalation, anchored |
| Refusal logging | If the agent attempts an action outside the tool surface, the refusal is anchored with the reason |
6 months later the auditor asks: "What did the agent do, and was every action authorised?" The chain answers in a query.
Where customers deploy agentic AI.
The patterns we see most often:
| Workflow | What the agent does | Where the human stays |
|---|---|---|
| Claims triage | Read, classify, route, summarise | Approval above defined value; complex claims |
| Contract first-pass review | Flag risk clauses, summarise against playbook | Risk clauses; final negotiation |
| Trade surveillance | Flag potentially anomalous communications | Final review and disposition |
| Quality event triage | Classify non-conformance, route to CAPA owner | Investigation, root-cause, corrective action |
| FOIA response | Identify responsive documents, draft redactions | Final redaction approval; response sign-off |
| TMF completeness check | Identify missing documents, draft notifications | Document upload, final TMF approval |
In each case, the agent removes the slowest parts of the workflow. The human focuses on judgment.
How customers compare TeamSync for agentic workflow.
The agentic-AI evaluation usually compares against:
- Microsoft Copilot Studio + Power Automate — strong on M365-resident workflows; cross-source platform, per-action permission check, and EU AI Act documentation are weaker
- Salesforce Agentforce — strong inside Salesforce; the regulated-content platform is weaker
- In-house frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) — most flexible; bounded-autonomy enforcement, audit anchoring, and regulator-acceptance argument need to be built
- n8n / Zapier with AI nodes — strong on workflow visual designers; the regulated-content audit is weaker
For specific comparisons: - TeamSync vs M365 Copilot
Read further.
- Why TeamSync — agentic AI workflow — the architectural pillar
- Chief AI Officer page — the AI program view
- Business Rules capability — the rules engine that defines tool surfaces
- Business Process Automation — the workflow engine the agent orchestrates
- EU AI Act overlay — the regulator-specific documentation pack