Capacity, not headcount
Hiring or renting the full specialist bench is slow, expensive, and fragile. Every role a project needs is baked into a Zipdata surface — so the AI Team comes enabled from the platform.
For mid-market operations leaders
On-Demand AI Data Team
AI that runs your dashboards, alerts, automations, and customer comms — without hiring a single person. Zipdata gives your Business teams that capacity inside one configurable Workspace — each role mapped to a real product surface, with first output in hours.
Why Zipdata
The team is the headline. The choices behind it make it work.
Replacing a specialist team with a platform is only useful if the platform itself is shaped right. Capacity is just one piece — unifying the data, governing the action, and getting intelligence to the right audience all had to be true by design.
One unified data layer
Every initiative that starts from zero rebuilds the same data plumbing. We start from a typed workspace schema your analytics, feeds, automations, and agents all read from — no fresh stack per project.
Audience-aware delivery
A dashboard nobody opens is the most common failure mode. Feeds and Groups route briefings, alerts, and updates to the people who can act — on cadence, not on request.
Governance by design
Approval tiers, deny-by-default tool grants, and an append-only audit log are part of the runtime — not a policy document bolted on after launch.
A workspace that matures
Start with reporting. Add automation. Add governed agents. The same workspace deepens with the operation — no re-platforming between maturity levels.
Configured, not rebuilt
Each workspace is configured to your operation in days instead of being assembled from scratch. The infrastructure is never rebuilt for the next project — and the saving reaches you.
The Zipdata model
From design choices to working components.
Each design choice above is delivered by a real component in the platform — stitched together so the team, the data, the delivery, and the governance all run from the same workspace.
Capacity, not headcount
Team
The AI Data Team layer
Each consulting role is mapped to a real Zipdata surface — Project Lead, Architect, Engineer, Analyst, Automation Builder, Delivery, Governance.
One unified data layer
Data
Data Hub
A typed PostgreSQL workspace schema — entities, fields, relationships, and constraints — that every analytic, feed, automation, and agent reads from.
Audience-aware delivery
Delivery
Feed Studio + Groups
Twelve feed types — briefings, dashboards, alerts, scorecards, customer updates, statements — generated from live workspace data and routed to the right audience on cadence.
Governance by design
Agents
Approval Tiers + Audit
Side-effect-classified tools, deny-by-default grants, four approval tiers, and an append-only action log for every consequential step.
A workspace that matures
Runtime
The Workspace Runtime
One project container that starts as reporting, becomes automation, then governed agents — same data, same governance, same audit history.
Configured, not rebuilt
Setup
The Onboarding Process
Brief → entities → connectors → mock data → analytics → watches → feeds → publish. The first automated briefing lands within 48 hours.
Same workspace. Six building blocks. Configured to your operation in days, not assembled from scratch for every project — so the speed and the savings reach you. The expert work still matters; the infrastructure does not have to be redone.
In practice
How a real first project takes shape.
Not everyone starts in the same place. You may need a unified data story, repeatable automation, or be ready for agentic execution. Zipdata uses the same workspace spine to support each maturity level.
Unified Data & Intelligence
A scattered operation gets one live story
Orders, inventory, dispatch, payments, and customer commitments live across spreadsheets and source systems.
What goes live
- Workspace
Entities, KPIs, queries, and connected records shaped around the client project.
- Analytics
Trend monitoring, dashboards, reports, and saved questions built from the same schema.
- Feeds
Leadership and operating groups receive briefings, dashboards, and exception alerts.
What you get
You stop reconciling the business by hand and start from a shared, current view.
Process Automation
Repeatable work runs without custom plumbing every time
Invoices, customer updates, documents, recurring reports, and data refreshes each need triggers, logs, storage, and delivery.
What goes live
- Automations
Scheduled jobs, document processing, invoice generation, enrichment, and writebacks.
- Tasks
One task spine monitors schedules, runs, failures, and next execution windows.
- Feeds
Generated documents, statements, reports, and updates are sent to the right groups.
What you get
The automation becomes part of the client workspace instead of another one-off script to maintain.
Agentic Transformation
Agents help the workspace act from context
Once the data and workflow are stable, you want the system to notice conditions, draft actions, and support follow-through.
What goes live
- Agents
Role-scoped programs monitor workspace data and decide what needs attention.
- Tools
Granted actions let agents draft messages, update records, trigger workflows, or call external systems.
- Governance
Approvals keep customer-facing, financial, or material actions under human control.
What you get
The project evolves from visibility and automation into a governed operating layer.
Our edge
Consulting depth, platform speed, a workspace you keep.
We understand your operation, configure the workspace, connect the data, build the automations and outputs, then expand toward agents when the workflow is ready. Strategy does not stop at a deck — it becomes a running workspace you own.
Discover the real workflow
We map the sources, entities, metrics, exceptions, approval rules, and audiences before anything gets configured.
Deploy one governed workspace
The PRD becomes typed data, feeds, automations, groups, tools, and agent programs inside one operating layer.
Operate, measure, and expand
Agents watch live records, deliver intelligence, queue follow-through, and leave a history the next workflow can build on.
Strong discovery, but the output often becomes decks, recommendations, and a handoff your team must turn into systems.
Faster setup, but usually around one standard workflow, with your data, governance, and follow-through split elsewhere.
Flexible, but each project rebuilds its own data plumbing, app layer, automations, storage, delivery, and monitoring.
Discovery, a configured workspace, feeds, automations, and live agents — delivered as one running layer you own.
Where to start
Pick one workflow. We will shape the first workspace around it.
We will identify whether the first engagement is unified data, process automation, or agentic transformation, then map the workspace, feeds, automations, and next-step path around it.