Agree what the truth is.
Map the client roster, account ownership, and financial metrics to establish rigid, enterprise-wide definitions.
All case studiesMulti-client services portfolio company · In production
Enterprise-Wide Telemetry: Centralized Data Architecture & Autonomous Interrogation
Client delivery lived in one tool, financial performance in another, and ownership data in isolated spreadsheets. We engineered a unified, foundational data layer beneath them all, empowering every dashboard and future AI agent to read from a single, uncompromised source of truth.
Company profileMulti-client services portfolio company.
Systems in playDisparate spreadsheets, specialized operational tools, legacy accounting platforms, bank feeds.
EngagementCore data layer deployment, followed by autonomous agent integration; currently in production.
How the build ran.
The same stepped process we run on every engagement, applied to this company.
Build the layer underneath.
Deploy a unified system that ingests every source on a strict schedule, eliminating manual re-entry and stagnant data.
Put the views on top.
Surface the unified client book, delivery metrics, and cash flow into a single, cohesive leadership view.
Add agents that inherit it.
Introduce AI agents that securely query the unified layer, inherently understanding who the clients are and strictly following role-based access.
The architecture, in one picture.
Five sources of truth flow into one shared layer. Everything the company looks at, and every agent it adds, reads from that layer.
The sources
Client rosterAccountsOwnership
Marketing performanceCampaign data
Finance sourcesBank feedsAccounting platform
Operating applicationLive status
SpreadsheetsRetired as truth
The shared company layer
One live system, refreshed on schedule, holding the definitions everything else agrees on.
One scheduleOne set of definitionsRole-based accessWhat reads from it
Leadership viewClient bookDeliveryCash
Client workspacesSame definitions
Finance viewsSame numbers
Every new agentInherits it all
What changed operationally.
Whole book to one account.
A senior operator moves from macro portfolio views to granular account data in one seamless motion, with zero manual reconciliation.
Every view agrees.
Client workspaces, financial reporting, and management views finally operate on identical, universally agreed-upon metrics.
Results.
The point of the layer.
Which client is being discussed, who owns it, where each figure came from, who may see it, and which system to update next. Every agent added later starts knowing all of this.
Want to also become AI-native?
You have just seen what one shared layer changes. A 30-minute call tells you what it would look like in your company, and whether it’s worth paying us to build it. If it isn’t, I’ll say so.
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