Owllys

PlanningNest

AI demand planning that doubts itself until it is right

The planning brain — Agentic RAG demand sensing that retrieves more context and iterates until the forecast clears a confidence threshold.

The problem

Forecasts miss by 30%+, so you carry excess to be safe and still stock out on the SKUs that matter.

92%
forecast accuracy
-30%
inventory
87%
confidence gate
How it works

From signal to outcome, the PlanningNest way

01

Sense

Agents fuse history, orders, promotions, weather and channel signals into a live demand picture.

02

Doubt

A confidence gate scores each forecast; low-confidence SKUs trigger another RAG retrieval round.

03

Plan

Replenishment, safety stock and S&OP scenarios are generated with explainable drivers.

04

Commit

Approved plans flow to OpsNest, Stocki and SourceNest automatically.

What it solves

The pain it takes off your plate

Chronic over- and under-stocking
Manual spreadsheet S&OP
No confidence on the forecast
Slow scenario planning
Run a live job

See the agent reason, end to end

Live job

Plan a demand spike before it stocks you out

  1. 1
    Signal

    Channel sell-through on SKU-4471 jumps 22% week-on-week; a promo is live in 9 days.

  2. 2
    Retrieve

    Agent pulls 3-yr seasonality, promo lift history, supplier lead times and on-hand cover.

  3. 3
    Doubt

    Forecast confidence 61% — below gate. Retrieves competitor stockout + weather signal.

  4. 4
    Decide

    Confidence now 89%. Recommends +1,800 units, split across two replenishment waves.

  5. 5
    Commit

    Pushes a draft PO to SourceNest and a build-ahead to OpsNest for one-click approval.

Outcome

Stockout avoided, no blanket overstock — the spike is covered with 1,800 units, not 5,000.

Put PlanningNest to work on a real outcome

AI recommends. Business governs. We commit to the KPI before we start — then you scale.