Marketing has more data than ever. Campaigns still run on handoffs.
Ideas wait
Testing backlogs move slower than the market. Hypotheses are inconsistent and measurement is often an afterthought.
Plans fragment
Budget, audience, inventory, channel and creative decisions are made across separate teams and tools.
Optimisation lags
Teams find pacing, fatigue or underperformance after the budget is already spent.
Learning evaporates
Post-campaign reports explain what happened. The insight rarely becomes the next test, plan or action.
Four sectors. One shared lag.
Telecom
Churn, usage and contract data sit in separate systems. Retention offers trigger after the customer has left, and revenue leakage surfaces after billing closes.
Media & Entertainment
Audience, viewership, and ad-sales data land after the flight. Pacing adjusts once the budget is spent and sell-through is lost.
Gaming
Player behavior, LTV, and monetization signals arrive late. Win-back and in-game offers reach players who have already uninstalled.
Ad Tech & Publishers
Audience, yield, and attribution data trail the auction. Bids, floors, and targeting update after the impression is gone.
The window to act closes in that gap. Your first-party data already sits in Databricks. It rarely reaches the campaign in time.
A team of specialist agents that works every campaign with you
Grow qualified pipeline
Business outcome, target audience, budget, timing, constraints.
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Command layer
Routes work to the right specialist and preserves shared context
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Specialist agents
Plan, test, QA, activate, monitor, report and recommend.
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Human gates
Human gates · Your team approves before anything launches, spends or publishes.
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Closed loop
Results feed the next hypothesis, allocation and campaign decision.
One journey.
Eleven experience modules.
Experiment & Launch
Base Camp — structure the test
Media Plan Center — build the plan & I/O
Campaign Launchpad — traffic, QA & activate
Operate & Improve
Campaign Navigator — pacing & reporting
Flight Optimizer — analyse and optimise
Campaign Cockpit — Post-campaign reporting, insight & learning
Spend Vector — supplier and wallet contro
Assist
Campaign Assist — self-serve help and operational guidance
Create & Protect
Pre-Flight Inspector — creative & brand compliance
Creative Hangar — ideation & generation
GEO Radar — search, GEO and market relevance
One closed loop, with memory.
Human approval before any budget is spent or any content is published.
Autonomy where it helps. Control where it matters.
Shared campaign object
Agents operate from a common campaign context rather than isolated conversations.
Grounded decisions
Planning, measurement and optimisation reason against enterprise performance data, not model intuition.
Human approval
Launch, publish, report and other side effects stop at explicit approval checkpoints.
Trace & evaluate
Execution stages, alerts, outputs and agent quality are monitored and benchmarked before autonomy expands.
Governed execution at machine speed. Autonomy expands only as the agents prove themselves.
The agents move. Your data doesn't.
No copy, no new silo
Agents read governed tables in place under Unity Catalog.
Zero Data Egress
No customer telemetry ever reaches external third-party servers
Nothing is replaced
Your ad platforms, DSPs and measurement partners stay.
Live in 4–6 weeks
An embedded iOPEX pod configures pipelines and gates.
What it runs on
Agent Bricks
Agents
Lakebase
Campaign memory
Lakeflow Connect
Telemetry
Unity Catalog
Governance
Databricks Apps
Modules
MLflow 3
Tracing
Bring one campaign. One governed data source.
