AI that actually read your collection. Thematic analysis you can't get on a spreadsheet.
Monthly stories that read your portfolio honestly — winners and losers both. Retirement signals that lead with LEGO and Brickset, not a third-party guess. Deep dives on every theme. Demand-spike flags, pattern matching, and a seasonal calendar that finally tells you when to buy.
Plus a quantitative roadmap — Monte Carlo, backtesting, correlation, causal attribution — on the runway for post-launch. We're honest about what's shipped and what's coming.
Why we built it
Charts you scroll past don't change behavior.
Most market dashboards bury the signal in dozens of charts you stop reading after the second week. The questions you actually want answered — "is anything in my collection retiring soon?", "what's actually working in this theme?", "is this set behaving like a past winner?" — never get answered, because nobody synthesizes the chart.
Insights is the synthesis layer. The AI story reads your Brickfolio every month and writes the paragraph. The retirement feed surfaces the EOL window before it disappears. The theme deep dives roll up cohort behavior into a curve you can actually use. The pattern matcher points at sets behaving like past winners. The seasonal calendar tells you when to buy.
Insights doesn't replace the underlying market data — it lives on top of it. The same price guide that prices your Brickfolio also feeds the AI. The same retailer history that drives the deals feed also drives the seasonal cadence. One source of truth. Different lenses.
See the synthesis
Four views into your collection's story
The synthesis layer — retirement signals, theme analytics, demand spikes, and the personalized read on what you actually hold.
Retirement signals, multi-source
LEGO + Brickset catalog flags first. Retailer disappearance patterns next. Algorithmic scoring as backup. 500 sets, ranked.
Demand spikes, signal-confirmed
Multi-signal detection across sales rank, retail supply, and price. Sets only appear when independent signals agree.
Theme deep dives, every theme
Long-run appreciation, drawdowns, top performers, retirement-spike curves — for every theme LEGO has shipped.
Your collection, synthesized
Top gainers and worst performers, OOS-everywhere flags, Health Score — the read on what you actually hold.
What's in Insights now
Six built-and-shipping pieces
Every feature in this section is live or in active production. The roadmap items are called out separately below — no vaporware on the "what's in" list.
Monthly AI collection stories
Once a month, your Brickfolio generates a short narrative — what's been moving, where the unrealized gains landed, which holdings flagged retirement signals, and the standout pieces in your book. Not a chart you have to read; a paragraph you actually do read. Honest about losers, not just winners.
- Per-Brickfolio monthly narrative
- Surfaces movers, retirement flags, rare holdings
- Honest about underperformers (not a hype tool)
- Pulled from current market data, not last quarter
Multi-source retirement signals
Three independent feeds, fused into a single signal: LEGO and Brickset catalog flags (the strongest source — when LEGO marks EOL, that's it), retailer disappearance patterns (set vanishes from LEGO.com and major retailers), and our own algorithm scoring availability and age. No single source is perfect; the combination, calibrated against years of past retirements, is the best you'll find.
- LEGO/Brickset catalog flags (primary source)
- Retailer disappearance pattern detection
- Algorithmic age + availability scoring
- Calibrated against past retirements
Theme deep dives, every theme
Every theme gets its own deep dive: long-run appreciation curve, drawdown windows, top-performing sets, retirement-spike behavior. Modular Buildings vs. Star Wars UCS vs. Architecture vs. Technic flagships — each behaves differently. The cohort view tells you which sub-asset class actually compounds and which one's overrated.
- Every LEGO theme individually tracked
- Long-run appreciation, drawdowns, top performers
- Retirement-spike curves per cohort
- Year-over-year and longer context
Demand spikes & velocity flags
Best-Seller Rank moves before price does. When a set's rank jumps from way down to near the top of its category in a week, demand has shifted — usually before listings firm or stock thins out. The spike feed surfaces those moves so you find them before the spread closes.
- Per-ASIN rank trend monitoring
- Daily, weekly, monthly velocity flags
- eBay sold-comp velocity overlay
- Tied to retirement signals where they overlap
Pattern matching — sets that look like past winners
Years of LEGO going through the cycle. Pattern matching surfaces sets currently behaving like sets that historically delivered — early rank rise, retailer firming, healthy sold-comp velocity at retail. Not a guarantee. A filter for which retail buys deserve a closer look.
- Surfaces sets matching historical winner patterns
- Multiple-signal match (price + rank + retailer)
- Honest disclaimer: not a return guarantee
- Cohort-aware (UCS patterns vs. Modular patterns differ)
Seasonal calendar — when sets historically appreciate
Most LEGO sets follow a seasonal cadence: summer dip, October–December peak, post-holiday slow-down, summer dip again. The seasonal calendar gives you that cadence per theme and per set, so you know whether to buy in May or wait until August — and whether the "30%-off" banner in November is the real low or the head-fake before the one in early December.
- Per-set, per-theme seasonal price cadence
- Sale-pattern overlay (Black Friday, post-holiday)
- Year-over-year seasonal compare
- Wishlist alerts respect the seasonal context
Quantitative features on the runway
Four post-launch features that the data layer is already wired for. Honest signal: these are not built yet. They're included on this page so you know what the platform is heading toward — not so we can call them shipped.
Monte Carlo price simulation
For any set, run thousands of simulated price paths against historical volatility, retirement timing distributions, and demand-velocity assumptions. Output a 5/50/95 percentile band on the year-ahead value. Useful for sizing a position with honest downside, not just an upside target. (On the quantitative-features roadmap; not built yet.)
Backtester — strategy testing on historical data
Test investing rules against the market memory. "Buy every UCS at retail, hold 3 years past retirement." "Buy every modular at 20%-off MSRP." Realized return, drawdown, time-to-realize, max-loss for that rule applied to history. Honest about survivorship bias and the limits of backtesting. (Roadmap.)
Correlation analysis — themes vs. broader markets
Are LEGO returns actually uncorrelated with equities? Are UCS returns correlated with new movie releases? With LEGO Group revenue cycles? With consumer-discretionary indexes? The correlation analysis surfaces the relationships that matter for portfolio construction. (Roadmap; some directional plotting available now.)
Causal attribution — what actually moved the price
Set X went up 28% over 18 months. Was it the retirement announcement? The new flagship release that compressed older UCS? The IP-driven spike from the show that came out in March? Causal attribution decomposes the move into estimable contributions. Honest disclaimer: causal inference on observational data is hard; treat outputs as hypotheses, not proof. (Roadmap.)
Plan documents for these features live in our internal roadmap. We don't pre-sell features that aren't built — these are listed so you can see the direction the platform is heading, not because the "launch" price gets you them.
Pairs with
Insights wires into everywhere else
Brickfolio
AI stories run against your Brickfolio every month.
BrickPulse Predictions
Community consensus complements algorithmic retirement signals.
Market Data
The market memory that anchors every insight.
Deals & Arbitrage
Retirement signals upgrade some deals from flip to hold.
For Investors
Theme analytics + retirement timing are the investor's core stack.
For Collectors
Monthly stories + theme deep dives + retirement timing in one place.
How honest is the AI story?
Why not just use BrickEconomy's retirement predictions?
How accurate are the demand-spike flags?
What's on the roadmap and when?
Do these signals work on retired sets too?
What's gated and what's free?
Stop scrolling past charts. Start reading the call.
Free sees the basics. Collector unlocks AI monthly stories, full theme deep dives, and a bigger retirement feed. Reseller adds the demand-spike feed and pattern-matching. The depth scales with the tier.