Taksh Solutions helps manufacturers put AI to work across planning and execution in SAP: sharper demand signals, faster supply decisions and production that responds to change. AI proposes, explains and automates the routine work, and your planners stay in control of the decisions.
We focus on use cases where AI saves planners time or improves a decision you make every day, and we build them on the SAP data and processes you already run.
Forecasts that learn from more than history, and a clear story behind every change.
Exceptions ranked by business impact, with options already worked out.
Schedules and orders that adjust when demand, materials or capacity change.
The real value of AI comes when a change in one area is carried through to the next automatically, instead of waiting for the next planning meeting.
AI senses a demand shift and updates the short-term forecast.
AI checks component and capacity impact and ranks the resulting exceptions.
AI proposes a revised, feasible schedule and highlights bottlenecks.
AI checks order readiness and flags shop floor issues as they happen.
AI in planning only works if people trust it. These principles shape every engagement.
AI proposes and automates routine steps. Planners and supervisors approve the decisions that matter.
Recommendations show what changed and why, so planners can check them quickly.
Forecasts and agents are only as good as the master data and history behind them.
Begin with one use case, measure it against today’s process, then scale what works.
Use cases run on the SAP processes and data you already have, not in a separate silo.
Access, data use and approvals follow your security and compliance policies.
A step-by-step path that delivers value early and builds toward an orchestrated demand-to-execution process.
Identify the highest-value use cases across demand, supply and manufacturing, and check whether your data and processes are ready.
Fix the master data, planning parameters and KPIs that AI depends on, so results are reliable from day one.
Deliver a focused pilot, such as ML forecasting or order release checks, and measure it against the current process.
Link use cases across demand, supply and manufacturing so changes flow from one plan to the next.
Planner training, approval rules and performance monitoring so AI keeps earning trust after go-live.
SAP Business AI and Joule, SAP IBP, SAP S/4HANA with embedded PP/DS and PEO, SAP Digital Manufacturing, and custom models where they add value.
AI enablement works best on top of solid processes. Combine it with our supply chain planning and manufacturing practices.
Demand planning and S&OP, supply and materials planning, and planning integration.
Explore supply chain planning →Production planning, embedded PP/DS, PEO, quality in production and shop floor integration.
Explore manufacturing →AI use cases and orchestration across demand, supply and manufacturing. You are here.
Capabilities on this page ↑Start with one decision your team makes every day and where data already exists, such as short-term forecasting, shortage prioritization or order release checks. A focused pilot shows value quickly and tells you what to fix before scaling.
No. AI takes on the repetitive work, such as cleaning data, sorting exceptions and preparing options. Planners spend more time on judgment calls, supplier and customer conversations, and approving the decisions that matter.
You need data that is good enough for the use case you choose. Part of our assessment is checking the master data and history a use case depends on, and fixing the gaps that would make results unreliable.
It depends on the use case. Many start with capabilities in SAP S/4HANA and SAP IBP, including machine learning forecasting and SAP’s Joule assistant and agents. Availability depends on your SAP products, release and licensing, so we confirm what you already have before recommending anything new.
Every use case has clear approval rules, explanations for its recommendations and measures that compare results with the current process. If a recommendation can’t be explained, it doesn’t go into production.
Tell us where planning and production slow you down today. We will suggest a first use case and a practical way to prove its value.
