One AI-augmented plan that brings demand, capacity and financial scenarios together, so sales, operations and finance commit to the same numbers and see the impact of every trade-off on margin and cash.
Sales brings a volume plan, operations a capacity plan and finance a budget; the review spends its time reconciling them.
A what-if on price, capacity or raw material cost needs a spreadsheet rebuild, so few are ever run.
Plans are agreed in units and cases; the margin and cash consequence arrives after the month has closed.
Why a forecast was overridden, and by whom, is rarely recorded and never learned from.
Each engine hands its output to the next, and the executive review sees the whole chain.
Statistical baseline by SKU and channel with the drivers explained, plus a log of every sales override and its reason.
Tests the demand plan against lines, shifts, materials and lead times, and flags constraints with options to resolve them.
Turns the volume plan into revenue, margin, working capital and cash, reconciled to budget, and runs what-ifs on demand.
A walkthrough of the agents at work: what they see, what they decide, and where people stay in control.
AITHENTIC demo · YouTube
Every agent follows the same five steps, so behaviour is predictable and every step leaves evidence.
Orders, shipments, forecasts, capacity, bills of material, standard costs and the approved budget.
Builds a baseline forecast, tests it against capacity and converts it into financial outcomes.
Surfaces the gaps between demand, supply and budget and ranks the options to close them.
Prepares the consensus pack, runs scenarios on demand and records the agreed plan as the single version.
Tracks forecast accuracy and override value, and feeds both back into the next cycle.
No single agent both proposes and approves. Each one has a narrow job, its own tools and its own permissions.
Produces a statistical baseline by SKU and channel and explains the drivers behind each change.
Tests the demand plan against lines, shifts, materials and lead times, and flags constraints.
Converts the volume plan into revenue, margin, working capital and cash, reconciled to the budget.
Runs what-ifs on request and presents the trade-offs side by side for the executive review.
Speed comes from autonomy. Trust comes from the three things around it. This is how each is designed into Integrated Business Planning.
Forecasting, constraint checks and scenario runs happen without waiting for anyone; committing the plan stays with the executive review.
The planning calendar, sign-off roles and plan versions are defined once and enforced by the workflow, not by email.
Every override is logged with owner, reason code and value, and the plan of record can be replayed version by version.
Tolerance bands decide when a gap is escalated; finance holds the bridge to budget and can lock it for the cycle.
Bands are agreed with the business before go-live and widened only on evidence from the pilot.
| Action | Autonomy | Accountable owner |
|---|---|---|
| Generate the baseline demand forecast | Acts autonomously | Demand planner |
| Flag capacity and material constraints | Acts autonomously | Supply planner |
| Run a scenario requested by a planner | Acts autonomously | Planner |
| Propose consensus adjustments to the plan | Recommends | S&OP lead |
| Commit the plan of record | Human approves | Executive S&OP committee |
Success metrics are agreed before build and signed off with the client after the pilot.
| Metric | Target | How we measure |
|---|---|---|
| Forecast accuracy | Up vs baseline | Weighted MAPE by SKU and channel |
| Time to consensus plan | Down vs baseline | Working days from data cut to sign-off |
| Scenarios reviewed per cycle | Up vs baseline | Count presented at executive review |
| Plan-to-actual margin variance | Down vs baseline | Monthly variance to plan of record |
Pilot results are company-reported and engagement-specific. Figures and names in decision records are illustrative.
Agentic process reengineering, one workflow at a time.
Map how the workflow really runs today, with owners, data lineage and the tacit rules.
Agree the business outcome, the baseline and the success metrics before build.
Redesign for agent-first execution: agents, tools, rules and autonomy bands.
Pilot inside your controls, train owners and move bands only on evidence.
Measure against the baseline and report the result the business signed off.
One live decision layer across sales, supply chain, operations and finance, run by agents.
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View use caseBook a working session with our team in Dubai, Riyadh or the UK. We will map the workflow, agree the metric and show the agent running on data like yours.