——For retail buyers and merchants——
Palette tells you what to price, what to keep, what to cut, and when to act — with evidence behind every recommendation. It gets sharper every cycle and empowers your Open-to-Buy / Line Strategy decisions.
Every SKU gets a recommendation informed by demand elasticity, margin constraints, competitive position, and lifecycle stage. Every recommendation shows its reasoning.
Know which products earn their shelf space. When Palette recommends a removal, it models where demand migrates — so you cut SKUs without cutting sales.
Catch rising attributes before they peak. Spot fading trends before overbuying into them. Palette defines products optimized by attribute and frees budget to innovate.
At the core of Palette is Sherlock, a fully-custom AI engine. Every opinion Sherlock forms is explicitly evidence-based — evidence compounding on evidence, cycle after cycle. As it becomes more familiar with your business, it develops strong convictions about what works and what doesn't, and sets expectations for what will happen next.
When your actuals align with those expectations, conviction strengthens. When they defy expectations, Sherlock reasons through the source of the difference and revises its stance based on the new evidence.
It doesn't start over from scratch. It doesn't retrain on your entire history. It reasons — like its namesake — from models it's built, and revises only where challenged. Each time you flip a Product Card in Palette, it's akin to the great detective rounding everyone up and explaining what's what.
Your data is processed and returned.
The intelligence stays.
The data doesn't.
Most retail optimization vendors share the same architecture... and limitations.
This is the actual Palette portal. Every card is a product. Every metric traces to a specific analytical finding.



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Every tier gets the same intelligence. We don't charge for features. We charge based on the scale of the business we're serving.
| Retailer Type | Annual Revenue | Service Fees |
|---|---|---|
| Emerging | $10M – $100M | $120K |
| Growth | $100M – $500M | $300K |
| Enterprise | $500M – $2B | $600K |
| Premier | $2B – $5B | $1M |
| Flagship | $5B – $10B | $1.5M |
| Titan | $10B + | $2M |
Every tier includes the full platform
No feature gating, no module upsells. No nickels, no dimes.
Weekly Analysis of Your Entire Assortment
Every SKU, every store, every attribute — pricing, sell-through, and rationalization in one pass. A comparable single-category review from a consultancy runs $75K–$200K and delivers a static snapshot. Palette does it every week, across all categories, and it gets sharper each cycle.
Explainable Recommendations
Every price, every keep/cut/review, every chase/maintain/exit decision traces to a specific reason. No black box.
Cross-Category Trend Analysis
Rising and fading attributes surfaced across your business, not siloed within departments.
Promotional Event Planning
Seasonal demand detection, product-level tier assignments, offer and timing optimization together.
Accumulating Intelligence
Elasticity estimates, track records, and attribute signals sharpen with every cycle thanks to Sherlock, our custom AI engine.
48 Hours of Realtime Mode
Hourly analysis and opt-in execution during your most critical selling windows.
Zero Data Retention
Your data is processed and returned. We keep the intelligence and signals we need, not your information. No lock-in.
Higher tiers add dedicated onboarding support, quarterly business reviews, priority roadmap influence, and named support contacts. Not additional features. Palette doesn't charge more for more intelligence.
2-month pilots start at $15K for Emerging retailers and scale with tier — the same proportional commitment at every level.
Week 1
Palette prices your assortment. Full reasoning on every recommendation. You execute.
Weeks 2–3
Results come in. Palette refines its estimates based on observed outcomes.
Weeks 4–8
Palette is learning your business. Recommendations sharpen. Trends emerge.
By the end of Week 8, you're
not evaluating Palette.
You're using it.
Your pilot investment applies in full toward your first annual contract.
The pilot isn't a test. It's the beginning.
It depends on how quickly your team can provide data. There’s typically a short onboarding period — aligning on how data should be formatted, defining business logic like product hierarchies and subsets, and establishing your first weekly feed. For a pilot, that prep work usually takes a couple of weeks. For a full enterprise-wide implementation, expect 2–3 months. Once data is flowing, Palette produces actionable recommendations from the first submission.
We only need a weekly snapshot: SKU details, sales, inventory, costs, attributes. Your ERP already has this. We provide a template to expedite things. However, we’re able to surface additional pieces of data — competitive pricing, review information, etc. — within the Product Cards where that would be helpful. It’s really up to you what you want to see to help you materially make decisions.
No. Your data is processed and returned. Palette retains derived intelligence — elasticity priors, track records, trend signals, among others — not your raw data.
There’s nothing to migrate, unwind, or extract. Palette doesn’t embed itself in your systems. Every contract includes an early termination clause — if it’s not working, you can exit. Accumulated intelligence is deleted and you walk away clean.
Those platforms require years of historical data, 6–18 months of implementation, and $2–5M annually. Palette works from day one, explains every recommendation, doesn’t warehouse your data, and costs a fraction — not because we do less, but because our architecture doesn’t need what theirs does.
No. Palette ingests a weekly CSV — your team can upload it directly. No systems integration, no API setup, no IT project. If you want to automate the feed later, a scheduled export from your ERP is all it takes.
It doesn’t need to. Palette works from a flat file: SKU details, sales, inventory, costs, attributes. If your team can pull a report, Palette can run. Automated feeds are optional and straightforward.
Every recommendation comes with the evidence behind it — sell-through pace, elasticity, margin analysis, and constraint logic. You can accept, modify, or ignore any recommendation. Palette informs your decisions. It doesn’t make them for you.
Palette evaluates sell-through pace, margin floors, competitive position, lifecycle urgency, and remaining weeks — simultaneously, for every SKU. Most manual processes optimize one variable at a time. Palette holds the full picture so your team doesn’t have to.
Any retailer with 200 or more active SKUs and weekly sell-through data. The platform scales with assortment complexity, not company revenue. The pricing tiers reflect scope — number of SKUs, doors, and analytical depth — not artificial feature gates.
Yes. Palette evaluates products within whatever hierarchy you define — handbags, apparel, electronics, home goods. The methodology adapts to the assortment, not the other way around.
Data is transmitted over TLS, processed in isolated environments, and never commingled across clients. Palette retains analytical signals — elasticity priors, trend intelligence, track records — not your raw transaction data. When you stop, everything is deleted.
“Palette transforms a complex, often opaque process into something clear, actionable, and highly strategic. It delivers both simplicity and sophistication — an uncommon but valuable combination.”