Delivery reliability
Shipments, carrier events, dispatch cut-offs, customer promises, and OTIF drift.
OTIF RiskSupply ContinuityWarehouse OpsCustomer Promise
See related use cases →The Agent Layer
Agents that watch your operation
and act — under your rules.
Not a chatbot, not a workflow, not a dashboard. An agent is a role-scoped program that monitors your workspace data, drafts outputs, queues actions, and executes through governed tools. It is the advanced layer — switched on once your workspace has the data, feeds, and approvals to support it.
By Function
Agents matter when the workspace is ready to act.
Agent programs are configured inside a workspace for the use case that matters. The mechanics are consistent: workspace data, watches, feeds, tools, approvals, and action history define what the agent can do.
Collections follow-up
Ageing, payments, exposure, DSO, and promise-to-pay movement.
ArrearsPortfolio RiskDSO WatchFollow-up Draft
See related use cases →Customer and service coordination
Orders, tickets, visits, SLA windows, customer updates, and escalation paths.
Order ManagementCare CoordinationSLA WatchEscalation Draft
See related use cases →01
Perception
It watches your operation — continuously.
The agent is connected to your live operational systems from day one. Every record, every threshold, every condition — monitored without interruption. Not when someone runs a report. Always. Three modes determine when it acts on what it sees.
Scheduled cadence
Morning briefings, weekly scorecards, monthly statements. The agent runs on the rhythm your operation already uses.
Event-driven
Fires the moment a record is created, updated, or a watch condition is met — inside the same minute.
On demand
An operator triggers a run manually for exception handling, scenario checks, or urgent investigations.
02
Reasoning
It reasons — not just reacts.
When something changes, the agent does not simply log a flag. It maps the change against operational baselines, prior decisions, and KPI history scoped to its role. An LLM reasons over this structured context to determine what is actually happening and what the right response is — with the rationale produced before any action is taken.
01PerceiveReads current state across all connected systems
02ContextualiseMaps change against baseline and domain memory
03PlanDetermines what action is needed and why
04Select ToolChooses which tool contract to invoke
05ActExecutes through granted tools or escalates for approval
06LogRecords the full trace — trigger, reasoning, outcome
03
Action
It acts through your tool library.
Every action the agent takes is executed through a granted tool — a connection to a system your operation already runs on. The grant model is deny-by-default: an agent with no granted tools has zero action capability. You expand what it can do by granting tools explicitly.
Built-in actions
InternalRead and update your operational data, generate intelligence outputs, trigger monitoring conditions, route escalations.
Analytical scripts
ScriptRun complex calculations, scoring models, or data transforms in an isolated environment. Credentials are injected securely.
External systems
WebhookPush updates to your ERP, legacy systems, or any internet-accessible endpoint via outbound HTTP.
Your own infrastructure
MCPRun the connection inside your own environment. No data leaves your trust boundary.
250+ connected apps
250+ appsSalesforce, Jira, Slack, Gmail, ServiceNow, and 245+ more. Authentication managed. No integration engineering from your team.
Test mode
TestSimulate agent behaviour before going live. Full trace, no real actions taken.
04
Governance
You control how much it does on its own.
Every tool carries a side-effect class. The runtime derives the approval tier from that class automatically — no per-agent configuration needed. Low-risk actions execute and are logged. Consequential actions queue for your team with the agent's reasoning attached, so you know exactly what it is proposing and why before you approve.
AutomaticUpdate an internal status, log an anomaly, tag a record for follow-up.Happens immediately. Recorded in full.
Draft for reviewGenerate the Monday briefing, build a risk scorecard, draft a quotation.Ready when you are — not blocked.
Notify and approveEscalate to a team member, open a support ticket, send an internal alert.Queued for your confirmation before it goes.
Admin-gatedCustomer comms, ERP or financial system updates, any payment-impacting step.Nothing customer-facing or financially material leaves without explicit approval.
05
Memory
It carries everything forward.
Every run is appended to an audit trail — trigger source, reasoning, tool used, approval status, outcome. That history feeds the agent's context on the next run. Baselines sharpen. Exception patterns build. The agent running in month six is informed by everything that came before it.
Append-only action log
Every action, every approval, every dismissal. Trigger, reasoning, and outcome recorded in full — traceable forever.
Context snapshots
Synthesised memory documents the agent carries into each run: what changed, what was decided, what the current baseline is.
Knowledge items
Durable facts, risks, and anomalies identified and retained — available to every future run in the same workspace.
Agents vs Automations
Same runtime. Very different jobs.
Automations do the deterministic, repeatable work — and Zipdata runs them as first-class objects. Agents take on what automation can't: watching continuously, reasoning in context, carrying a decision through several steps, and staying inside the approval rules. You want both.
AutomationAgent
Trigger modelOne declared trigger — one webhook, one cron, one event — wired to one action.Fires from scheduled cadences, entity events, and watch conditions — evaluated continuously through one runtime.
Context awarenessReceives the inputs declared on the trigger payload. Stateless across runs by design.Carries operational baselines, prior decisions, KPI history, and role-scoped entity context across every run.
Decision behaviourDeterministic branch logic. Edge cases not anticipated by the rules fall through.Reasons over current state against the baseline — outputs a decision with the rationale attached.
Output shapeA single completion event — record updated, message sent, webhook posted.A multi-step outcome in one cycle: detect, prioritise, draft, route, and escalate.
GovernancePermissioning lives outside the runtime — in IAM, in the called system, or in the script's secrets.Every tool carries a side-effect class. The runtime enforces the approval tier automatically — no per-agent config.
Adding capabilityEngineering work — a new script, a new trigger, a new run history to maintain.Grant a tool to the role. The loop is unchanged; the action surface expands. Governance tier inherited automatically.
Ready to see it in your operation?
Configured for your team. Running in 48 hours.
We design the role, configure the trigger model, grant the tools, and set the approval tiers for your operation — not a generic demo.