Featured capability · Notebooks · RV·2026·NB

The notebook that ships
its own strategy.

Live queries, models, charts and prose on governed commercial data, then forecasting, prescriptive optimization, guardrails, governed execution and measured value, in the same living document. The document is the strategy, and the strategy ships.

SPECIMEN RUN · NORTHEAST DISTRIBUTION · GOAL +200 BPS · VOLUME TOLERANCE −1.0%
Revomo Notebooks: FY26 Margin Strategy · Northeast Distribution
Notebooks / Commercial strategy / FY26 Margin Strategy: Northeast Distribution
FY26 Margin Strategy: Northeast Distribution

This document is the strategy, not a slide about it. The data, the model, the optimization, the guardrails and the results live here, and they stay live after the meeting ends.

Goal. Recover 200+ bps of pocket margin in Northeast Distribution by Q2, without giving up more than 1.0% of volume. Constraints and floors below are the same governed records the business runs on.
Copilot
I bound the commercial context for Northeast Distribution, six sources, one spine. Everything below computes on these records, not on an extract.
ERP invoices · 24 moCOST vendor price filesREB rebate agreementsFRT freight lanesCRM quotes & winsCTR contract terms
184 customers · 1,842 SKUs · 96,412 transactions · ontology v2026.4
Analyze

Where the margin leaks

The part every good notebook can do, list to pocket, computed live:

Standard list$11.42M
Discounts off list−$0.86M
Freight absorbed−$0.41M
Rebates & programs−$0.33M
Pocket margin$9.82M · 20.4%
Two concentrations. Freight running below cost on 41 lanes (−$76K/yr) and 184 accounts priced under the corridor (−$92K/yr) account for 84% of the recoverable gap. Each line item traces to its record.
A finding and a chart aren’t a strategy. Ask for one.
Copilot
Model

Scenario model, what happens if we act

cell 04 · predictive · trained
volume_response = train(transactions_24mo, method='gradient_boosting')backtest: MAPE 4.1% · holdout Q1 · elasticity by segment × SKU family
20%21.5%23%goal · 22.4% (+200 bps)todayAPROCT 1 · effectiveMAR

Toggle levers, the forecast, the band and everything downstream recompute from the model, not from a slide.

Optimize

Prescriptive optimization, the exact moves

cell 07 · discrete optimization · solved 2.4s
maximize Σ pocket_marginsubject to Δvolume ≥ −1.0% · Δprice ≤ 4% per account · corridor floors · 37 contract lockssolver: MILP · 1,842 SKUs × 184 accounts · 339,128 decision variables
Recovery / yr
+$0K
Pocket margin
+0 bps
Volume impact
0%
SKUs held to term
0
430512486302112HOLD+0–1%+1–2%+2–3%+3–4%1,842 SKUs · per-account moves within corridor · contract-locked SKUs held
The optimizer respects the same guardrails the business does, because they are the same records. No blanket percentage; 1,412 SKUs move, each inside its corridor, 37 held to contract.
Govern

Guardrails, written into the operating system

Copilot
RULE·NE·FLOORPocket GM ≥ 18% on all Northeast Distribution quotesDEPLOYED ✓
RULE·NE·ESCMoves > 4% per account route to RVP with model context attachedDEPLOYED ✓
Execute

Governed execution, not an email thread

PA‑2026‑118 · price action · staged
Draft ✓→Validate ✓→Approve ✓→Publish · Oct 1
184 customers · 1,412 SKUs · effective Oct 1. Every quote, order and price list downstream inherits it, the strategy and the transaction system are the same system.
Measure

Did it work? The notebook keeps score.

modeled · +218 bpsrealized · +205 bpsWK 1WK 12
Week 12: +205 bps realized against +218 modeled, 94% capture. The variance decomposes to two national-account exceptions, both cited. The next notebook starts smarter than this one.
RV·2026·NB·001 · SPECIMEN, illustrative data, real mechanicsevery cell · every figure · on the record

Analysis is the floor, not the ceiling.

A strategy lives in stages, find it, decide it, ship it, prove it. Revomo Notebooks run every stage in one governed document, because the document runs on the spine.

01
Analyze

SQL, Python, charts and prose on live, governed commercial data. No extracts, no stale copies: every figure cites the record it came from, so the analysis survives the meeting.

02
Decide

Forecast demand response, train predictive models, and run discrete optimization against real business constraints (corridor floors, contract locks, volume tolerance) because the constraints are records on the same spine.

03
Execute

Write guardrails to the Rule Engine, stage governed price actions, and measure realized value against the model, in the same document, which stays live and keeps score.

Bring a business goal.
Leave with a running strategy.

In the first weeks of an engagement, we build this notebook on your data, your leak, your constraints, your optimizer run, your governed action.

Plate NB · Series 2026 · Notebooks · RV·2026·NB
Plate B2 · Series 2026