Guac

1. Procurement requires publicly documented SOC 2 / ISO 27001 attestations prior to engagement.

• Public materials reviewed do not include these certifications. If procurement policies require published attestations, consider vendors with documented third-party audits.

2. A buyer requires an all-in-one enterprise planning suite backed by long-term references.

• Incumbent vendors that explicitly offer integrated planning across pricing, promotions, assortment, and forecasting may be a better fit for these requirements.

3. The retailer’s data foundation is weak (poor inventory accuracy, inconsistent item master, or undisciplined promotion calendars).

• Forecasting models cannot compensate for persistent data quality issues; foundational data cleanup or a different service engagement is recommended first.

4. The buyer is uncertain about domain or brand continuity.

• The domain contains legacy consumer-facing content alongside current B2B material. Buyers should validate legal entity, contracting party, and alignment of privacy and terms documentation.

• A mobile app store listing for an inventory/ordering app associated with the vendor exists, but it indicates insufficient ratings to display an overview.
• Partner-published content (for example, a partner social post) includes operational commentary attributed to vendor staff, but it is partner-produced material rather than independent customer feedback.
• No significant forum or news-aggregation threads were identified that review the B2B forecasting product; many search results for “guac” relate to food topics rather than the vendor.

• Missing details necessary to validate ROI include baseline definitions (department or SKU subset), measurement periods and seasonality controls, how stockouts and lost sales were handled, and whether measured improvements derived primarily from forecast accuracy improvements or from process standardization and UI changes.

Recommendation: Require a paid pilot with predefined success metrics (for example: shrink percentage, in-stock percentage, labor minutes per order, and proxies for lost sales) and an agreed measurement methodology.

Guac markets a demand forecasting and replenishment platform for fresh grocery that uses machine learning models to forecast demand and supports adjacent operational workflows (store ordering, DC allocation, production planning). The vendor positions forecasting as the central capability and advertises supporting operational modules for ordering and inventory estimation at store and distribution center levels. References to the vendor website and product pages appear on official vendor product and overview pages.

Key modules described publicly include:

• Forecasting: item-level, store-level, day-level demand forecasts trained with external variables.
• Store Ordering & Inventory: ordering recommendations and store/backroom stock estimation.
• DC Allocation / DC Buyer Ordering / Production Planning: listed as components of the suite with less public detail than forecasting and store ordering.