Every A2go agent runs on ADIP — the Decision Intelligence Platform that unifies your data, governs agent decisions, and encodes your team’s expertise into the Judgment Layer. No rip-and-replace. Deploy your first agent in 90 days.
Forecasting errors, siloed planning, excess inventory, and late deliveries are interconnected issues stemming from outdated supply chain management tools.
A2go’s Supply Chain Data Intelligence doesn’t replace your existing ERP systems; it augments them with real-time insights and decision recommendations.
Our Agentic AI streamlines data and transforms knowledge workers into proactive profit managers, driving business outcomes and growth.
A2go features a comprehensive library of AI agents, each developed by supply chain and AI experts. Each is designed as a purpose-built supply chain solution. These AI agents detect and resolve issues instantly.
Every agent in the A2go library is purpose-built for a specific supply chain problem — and every agent runs on the same ADIP infrastructure. That means each new agent you deploy benefits immediately from the data, memory, and governance already in place. Expansion becomes a natural next step, not a new implementation.
Demand variability is the single biggest driver of supply chain costs and complexity. Most companies struggle with forecast accuracy because their data is fragmented, their planning processes are manual, and their systems were not built to learn from what actually happened. As a result, median forecast errors range from 24-37%, leading to a devastating cascade of consequences throughout the network, including misaligned production, excess inventory, and unacceptable on-time performance.
ADIP continuously ingests, harmonizes, and enriches demand signals from across the enterprise and external sources — eliminating the fragmented data problem on day one. On top of ADIP, A2go’s Forecasting & Planning agents transform forecasting from a manual, periodic exercise into a dynamic, continuously learning system.
Specific agents in this area include:
Customers using A2go’s Forecasting & Planning agents reduce forecast error rates by 50–80%, with 100% SKU coverage and continuous monitoring. Lower error rates cut rework, reduce inventory, and improve on-time performance across the network. The Judgment Layer continuously encodes what your planners know about your business — so accuracy compounds over time rather than degrading between planning cycles.
ERP and legacy planning systems create fragmented, siloed processes that lead to suboptimal decision-making. Companies often resort to manual spreadsheet workarounds, creating invisible “shadow planning” processes that introduce more errors. Each functional area optimizes for its own narrow targets, creating conflicting schedules and bottlenecks that cascade into crises and force a reactive culture of “firefighting.”
ADIP overlays existing systems with an intelligent orchestration layer that unifies planning data across procurement, production, and logistics in real time. A2go’s Operational Planning agents identify conflicts and constraints before they cascade into disruptions — and run “what-if” scenarios automatically so planners can test options instead of chase problems.
Specific agents in this area include:
By embedding predictive analytics and automated what-if capabilities directly into existing workflows, ADIP-powered agents synchronize procurement, production, and logistics around a single, continuously updated plan. Planning cycles shorten from days to hours. Expedites drop. Throughput rises — without re-engineering your ERP or changing how your teams operate.
Proof point: ($500M industrial manufacturer) reduced master scheduling from 18 hours across 24 spreadsheets to 15 minutes after ADIP deployment.
Achieving perfect orders is a critical goal for customer satisfaction, but it remains elusive. Fragmented visibility throughout the fulfillment process means potential failures are discovered too late for effective intervention. This leads to frustrating delays, incomplete shipments, and costly recovery efforts, all of which erode customer trust.
ADIP monitors every order, shipment, and milestone in real time — flagging jeopardy situations while there is still time to act. A2go’s OTIF agents quantify the cost of each exception, recommend corrective actions, and update commitments across the organization automatically.
Specific agents in this area include:
Customers using A2go’s OTIF agents achieve consistently higher OTIF scores and 25% shorter order-to-cash cycles — while reducing the premium freight and expedite costs that erode margin. As the Judgment Layer encodes your specific customer commitments and exception patterns, the system increasingly anticipates jeopardy before it appears in the data stream.
Proof point: ($5B+ beef processor) achieved +$200M annual profit impact across 60,000+ SKUs — driven in part by ADIP’s ability to manage order complexity at a scale no human planning team could match.
It is imperative to continuously monitor and manage your supply chain’s event stream, which can consist of millions of events per week. Knowledge workers often lack the time and means to manage these anomalies effectively, leading to excess inventory as a protection mechanism against stockouts and missed schedules. For a $200M–$500M midmarket manufacturer, this event stream can exceed 5 million supply chain signals per week.
ADIP’s continuous event stream monitors every supply chain signal in real time. A2go’s Supply & Inventory Optimization agents surface the anomalies that matter, quantify their impact, and recommend corrective actions — so your team resolves exceptions before they become write-offs or expedites. Research confirms that nearly all adverse supply chain events can be resolved at low cost when caught early enough to act.
Specific agents in this area include:
Customers using A2go’s Supply & Inventory Optimization agents typically reduce working capital needs by 15–30% while maintaining or improving service levels. Inventory reductions of 30–50% have been achieved without increasing stockouts. As the Judgment Layer accumulates knowledge of your specific supplier behavior and demand patterns, optimization performance compounds — reducing the need for safety stock over time.
Proof point: ($500M industrial manufacturer) achieved 30% inventory cost reduction and 25% shorter cash cycles within 12 months of ADIP deployment.