Supply-Chain Decision Intelligence
The A2go Decision Intelligence Platform (ADIP) turns the data your systems already produce into operating decisions your team can review, approve, and execute the same day.
Results from production, not a demo
Forecasting time, before and after ADIP.
Pricing simulated in minutes rather than days.
Master scheduling at a roughly $500M industrial manufacturer.
The first two figures come from the published Databricks customer story about A2go. ADIP is built on Databricks. The full picture, including the before-state, is on the Results page.
The obvious objection
Traditional analytics
Dashboards tell you what happened. A person still pulls the data into a spreadsheet and builds the recommendation by hand.
Generative AI
Copilots draft, summarize, and answer questions. They do not carry a decision through approval and into the systems that run your operation.
Agentic decision intelligence
Agents assemble the decision with the evidence attached, a person approves it, and the approved action writes back to the system of record.
The full comparison: Traditional vs. generative vs. agentic.
What it does
Forecasting & Planning
Demand forecasts refreshed continuously and reconciled across sites, channels, and customers.
Forecast accuracyOperational Planning
Master schedules and clear-to-build calls prepared in minutes instead of overnight.
Schedule adherenceSupply & Inventory
Purchase, rebalance, and expedite decisions grounded in the live supply position, not last week’s extract.
Inventory turnsOTIF Optimization
ATP and short-ship decisions made before the promise breaks, not after.
OTIFThe platform in full, pillar by pillar: ADIP.
Why nothing breaks
ADIP does not replace your ERP, your planning tools, or your warehouse. They stay where they are and keep doing their jobs. Data flows from those systems into a governed decision layer, the agents do their work there, and the only thing that comes back is a decision a person has approved, written to the system that owns it. No rip-and-replace, no parallel master data, no second place for the truth to live.
The differentiator
Automation projects usually stall on one question: who decided, and on what authority? The Judgment Layer is where your operating policy lives. You set which decisions agents may execute on their own, which require a named approver, and what evidence must be attached before anything moves. Every recommendation shows its reasoning, and every action keeps its approval trail. That is the difference between software that suggests and software you can put in the middle of your operation.
Who this is for
ADIP is built for manufacturers and distributors between $400M and $2B in revenue: multiple sites, more than one ERP left over from acquisitions, and OTIF sitting stubbornly under 90 percent. A $20B enterprise can survive a slow planning cycle or a bad month of service, because there is buffer everywhere. A $500M manufacturer cannot. The same miss shows up in the quarter, and there is no forty-person analytics team to throw at it.
Reading for your seat: for the CFO · for the COO and supply-chain leader.
Who is behind it
More on the team: About A2go.
Pick the decision that hurts the most today. The survey takes five minutes and maps it to the pillar and the metric it moves.
Map your highest-pain decision