Guac
AI forecasting and replenishment built specifically for fresh grocery departments.
Guac is one of the few forecasting platforms aimed squarely at fresh grocery rather than general retail, and that focus shows in the module list: store ordering, production planning, DC allocation, commissary planning and recipe management all speak the language of perishables. The variable-aware forecast — you can toggle schools, promotions, sports, weather and holidays to see the effect on predicted sales — is the feature most buyers will test first, and the reported 38% waste reduction and 3% sales lift are the numbers to validate in a pilot. Weigh it against general retail forecasting suites that treat fresh as one workload among many; Guac's depth in fresh is its edge, its narrowness
Verified 11h ago · liveness 57/100 · cite: rightaichoice.com/tools/guac
- Mid-to-large grocery chains with fresh departments
- Store ordering and production teams needing daily store-level guidance
- DC buyers and allocation planners managing perishable inventory
- Commissary and prepared food operations tied to HQ recipes
- Non-grocery retail verticals like fashion or electronics
- Small independent stores without digital infrastructure or budget for a custom solution
- Teams that need a full ERP or accounting suite
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Skip Guac if you run a non-grocery format, you're a small independent without the infrastructure for a custom deployment, or you need one platform that also covers general merchandise and accounting.
Because every solution is custom-built per retailer, expect implementation and integration effort beyond the software itself — Guac describes a consultative engagement with customized forecasting and cloud-native
Guac sells through a consultative, custom-engagement model rather than published self-serve tiers, so budget for an implementation-style purchase. That typically suits mid-to-large grocery chains where a 38% waste reduction across fresh departments can justify the spend; smaller independents will likely find lighter-weight forecasting add-ons from their existing inventory or POS vendor easier to afford.
In short
Guac — AI forecasting and replenishment built specifically for fresh grocery departments. Best for Mid-to-large grocery chains with fresh departments, Store ordering and production teams needing daily store-level guidance, DC buyers and allocation planners managing perishable inventory. Contact Sales pricing.
What people actually say about Guac — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
89 mentions across 6 sources (Hacker News, YouTube, Product Hunt, App Store, GitHub, Lemmy) · researched Aug 16, 2026.
Average across the 6 sources that answered — each source counts once, not each post.
- +Targets a clear niche: fresh grocery forecasting, not generic retail
- +Uses 240+ local data variables for accuracy
- +Reports 38% food waste reduction and 3% sales lift
- +Provides store-level daily forecasts for every SKU
- +Modules for store, DC, and commissary planning
- −Almost no direct user feedback exists to validate claims
- −Speculative benefits not independently verified
- −Pricing opaque, requiring sales contact
- −Brand confusion with a poorly reviewed budgeting app
- −Potential integration complexity with existing ERP systems
- • Custom onboarding may incur professional services fees
- • Potential costs for data integration and API access
Viability Score
How well maintained and how widely used is Guac? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- AI demand forecasting per SKU, per store, per day
- 240+ external variables including weather, sports, school terms and social media trends
- Custom forecasting algorithm trained per retailer on internal and external data
- Interactive forecast chart with variable toggles (schools, promotions, sports, weather, holidays)
- Store Ordering with recommended quantities based on current stock and case sizes
- Store Production Planning for prepared food and fresh production
- DC Buyer Ordering with intelligent ordering suggestions
- DC Allocation optimization across stores
- Commissary Production Planning
- Recipe Management for HQ teams
- Analytics dashboards for performance insights
- Support for meat & seafood, bakery, produce, deli and center store departments
- Web-based platform
- 24/7 support with a dedicated engineer and in-person rollout support
- Custom cloud-native integrations with existing retailer systems
About Guac
Guac is an AI forecasting and replenishment platform built exclusively for fresh grocery retail. It trains a custom demand model for each retailer by ingesting your internal data together with 240+ external local variables — weather, sports, school terms, promotions, demographics, and social media trends — to forecast demand for each SKU, each day, at each store. Forecasts are turned into ordering and production recommendations that account for current stock, case sizes, and the operational quirks of fresh. Six product modules cover the workflow: Store Ordering and Store Production Planning for store teams, DC Buyer Ordering and DC Allocation for distribution, Commissary Production Planning, and Recipe Management with Analytics for HQ. Departments supported include meat & seafood, bakery, produce, deli, and center store. Guac reports a 38% reduction in food waste and a 3% increase in sales for retailers using its forecasts. The company runs a consultative engagement — solutions are customized per retailer, with 24/7 support, a dedicated engineer, and in-person rollout support, plus fully custom cloud-native integrations into existing systems.
Behind the Verdict
Fresh grocery is the hardest forecasting problem in retail: short shelf life, daily store-level variation, and demand that swings on local events no central planner can see coming. Guac's answer is a per-retailer custom model fed by 240+ external variables — weather, sports schedules, school terms, proms, promotions, demographics and social media trends — layered on top of the retailer's own sales and inventory data. The three-step process is easy to follow: forecast sales, convert forecasts into recommendations using current stock and case sizes, then push those recommendations into the product modules where store, DC, commissary and HQ teams actually work. That last step matters more than the model. A great forecast that lands in a spreadsheet nobody opens does nothing, and Guac's product surface — Store Ordering, Store Production Planning, DC Buyer Ordering, DC Allocation, Commissary Production Planning, Recipe Management and Analytics — is designed so the forecast becomes an action. The interactive chart with variable toggles is a smart trust-builder: a store manager who can see that a school holiday is why the forecast dropped is far more likely to follow the recommendation than one staring at a black-box number. Reported results are 38% less food waste and 3% more sales; treat both as vendor-reported and insist on a measured pilot in your own stores before signing anything long. On engagement: Guac explicitly builds a custom solution per retailer, offers 24/7 support, a dedicated engineer, and in-person rollout, and describes fully custom cloud-native integrations with existing systems — read that as a real implementation project, not a plug-in-and-go SaaS. The platform is web-based. Where it fits: mid-to-large fresh-focused grocery chains with the data plumbing and the appetite for a custom deployment, and teams whose pain is concentrated in meat & seafood, bakery, produce, deli or center store. Where it doesn't: non-grocery verticals, very small independents without the infrastructure or budget for a custom build, and buyers who need a full ERP or accounting suite rather than a forecasting and replenishment layer.
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Real-world workflow fit
Concrete scenarios for the personas Guac actually fits — and what changes day-one when you adopt it.
Every morning the manager opens Guac's Store Ordering module, reviews the day's per-SKU forecast, checks the interactive chart to see whether a local school holiday or a promotion is driving the change, and accepts or adjusts the recommended order quantities before the cut-off.
Outcome: Orders match expected demand more closely, which reduces over-ordering on perishables and lowers the chance of running out on high-turn items.
The buyer uses DC Buyer Ordering and DC Allocation to turn store-level forecasts into a consolidated buying and allocation plan, adjusting for case sizes and current stock before releasing to stores.
Outcome: Fewer emergency top-up orders and less spoilage in the DC, because allocation follows per-store demand rather than a flat push.
The lead updates a recipe in Recipe Management, and the change flows into commissary production plans and store production planning so prepared food teams produce the right quantities of the updated item.
Outcome: Recipe and production changes reach stores and commissaries consistently instead of through manual handoffs.
Use Cases
- Forecast daily store demand for blueberries using weather, school term and local event data
- Cut food waste by following AI-recommended order quantities at store level
- Plan fresh bakery production around predicted sales and upcoming promotions
- Allocate DC inventory to stores using granular per-store demand forecasts
- Push recipe changes from HQ into updated commissary production plans
Limitations
- Guac is purpose-built for fresh grocery, so it is not a general retail planning suite and does not cover non-fresh verticals like fashion or electronics.
- The forecasting algorithm is proprietary and the underlying model is not named publicly.
- Deployment is consultative: the site describes solutions as unique to each retailer, with fully custom cloud-native integrations, 24/7 support, a dedicated engineer and in-person rollout — plan for an implementation project rather than self-serve setup.
- Reported outcomes (38% waste reduction, 3% sales increase) are vendor-reported and should be validated in a pilot.
as of 2026-09-23
Verification history
We have re-verified Guac 10 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
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Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Guac's pricing actually pencils out — and where peers do it cheaper.
Guac sells through a consultative, custom-engagement model rather than published self-serve tiers, so budget for an implementation-style purchase. That typically suits mid-to-large grocery chains where a 38% waste reduction across fresh departments can justify the spend; smaller independents will likely find lighter-weight forecasting add-ons from their existing inventory or POS vendor easier to afford.
Setup time & first value
How long it actually takes to get something useful out of Guac — broken out by persona, not the marketing-page minute.
Store teams: fastest path to value once forecasts are live, since ordering and production screens mirror existing daily routines. DC buyers and allocation planners: a few weeks to align case sizes, current stock logic and allocation rules with Guac's recommendations. HQ teams: longest ramp, because recipe management and analytics depend on clean item and recipe data across departments. Expect a
Switching to or from Guac
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From spreadsheet-based ordering: Guac's Store Ordering replaces manual reorder sheets with per-SKU recommended quantities, and the interactive chart shows what's driving each forecast.
- →From a generic retail forecasting suite: Guac layers fresh-specific logic (shelf life, case sizes, production planning, recipes) on top of your existing data.
- →From an ERP's basic replenishment module: Guac adds store-level, variable-aware forecasting and dedicated DC and commissary workflows.
- ↗To a general retail planning suite: if you need one platform spanning fresh and non-fresh categories, expect to rebuild fresh workflows in a broader system.
- ↗To an ERP-native replenishment module: simpler in theory, but you would lose the 240+ external variables and the fresh-specific modules.
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Guac”, and we withheld 6: 6 could not be judged, because “Guac” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Guac.
Official links
Tools that pair well with Guac
Common stack mates teams adopt alongside Guac, with the specific reason each pairing earns its keep.
Metreecs
Metreecs is an AI inventory and demand-planning suite for mid-to-large retailers that automates forecasting, replenishment and rebalancing across multi-echelon
Transfix
AI freight TMS for brokers and 3PLs with custom cost models built on your own data
StockTrim
AI inventory forecasting and automated purchasing that tells SMBs exactly what to reorder — priced by revenue, not seats.
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