Every angle on the wealth-tech ecosystem.
Five neighborhoods, 22 maps. Players, work, money & markets, the live pulse, and the talent side — jump in anywhere.
The Players
Who's in the game — vendors, firms, and how packed each capability is.
Most-crowded capabilities
Which sub-capabilities have the most vendors fighting for the same buyer.
- Count of vendors mapped to each sub-capability.
- Higher = more competition, harder differentiation.
- Full map has Sand → Clay heat + Overview split.
Under-served corners of the wealth-tech stack
Sub-capabilities where the vendor-to-need ratio is thinnest — the shape of the whitespace, not a headline count.
- Ratio = 1 / (vendor_count + 1) so low-count long-tail rises without exaggerating single-vendor pockets.
- Absolute counts (usually 1–5) intentionally omitted on the front — they read as low-credibility on a card.
- Full map has the raw counts + Sand → Clay heat lens.
Wealth-tech vendors covering the most sub-caps
Vendors that have expanded from a beachhead into multiple adjacent capabilities.
- Count of distinct sub-capabilities the vendor sits under.
- Signals platform posture vs. point solution.
- Full atlas filters by capability + tags.
Where AI-native builders are concentrated
Sub-capabilities where AI-native, agentic, or LLM-first vendors are actually piling up — the concentration story, not a top-line percentage.
- Vendors self-tagged as AI, agentic, or LLM in the atlas.
- Grouped by sub-capability, ranked by count.
- Full atlas filters by the same AI-native cohort.
Firms by channel
The distribution of firms in the industry map across channels.
- Channel tag per firm (wirehouse, RIA, bank PWM, IBD, etc.).
- Full map has channel × AUM × segment lenses.
- Firm-detail cards on click.
The AUM ladder
Where firms cluster by scale — the $1T+ giants vs. the long tail.
- Tiers: <$50B / $50-200B / $200B-1T / >$1T.
- Uses each firm's reported AUM.
- Filter by AUM in the industry map.
Where the big firms sit
Firm headquarters by country in the industry map.
- ISO-3166 alpha-2 country tag per firm.
- Reflects the tracked set, not the whole industry.
- Geography map covers vendor + talent heat separately.
Advice-led vs. discretionary
Whether firms lead with advice, discretionary portfolios, or something else.
- Service model tag per firm.
- Advice-led = planning + relationship. Discretionary = manager decides.
- Full map: service × channel lens.
The top-rated vendors
How many vendors score ≥ 4.5 across the review sources we monitor.
- Aggregated from G2 / Capterra / T3 where available.
- topRated flag applies at ≥ 4.5.
- Filter the atlas by top-rated.
The Work
What actually happens inside a firm — capabilities, functions, data, and the people doing the job.
What a wealth firm actually does
Categories ranked by how many sub-capabilities live inside them.
- Bigger bar = broader capability surface.
- Full map has 5 lenses: density, AI, M&A, hotness, whitespace.
- Cells cross-link to skills + roles.
Prospect → bill in 8 stages
The 8 stages of the client value chain and how many phases sit inside each.
- Phase count = distinct steps inside the stage.
- Full map layers vendors + roles + skills per stage.
- 4 lenses on the functions map.
9 data objects thread every wealth workflow
9 core data objects laid out end-to-end with clickable systems + functions.
- Bar length = how many systems the object touches.
- Full map shows hand-offs + owners.
- Click a node to isolate its systems.
Where AI is landing across the wealth-tech stack
The sub-capabilities where AI is having the biggest impact right now — ranked, not tier-bucketed.
- Impact tiers: transformative / high / moderate / emerging.
- This card surfaces the top of the transformative + high buckets.
- Overview shows extremes; Explore has 3 lenses.
How AI is landing across the wealth-tech stack
The distribution of AI impact across every capability tracked.
- Tier per sub-capability.
- Counts, not weighted revenue.
- Full map explores the disruption lens.
Front / middle / back split
Catalogued roles split across office by family.
- Office tag per role in the matrix.
- Counts only — not FTE.
- Full map has 4 lenses + cross-links to skills.
Which capabilities are widest
Both extremes of the capability model — the sprawling categories and the tight ones.
- Count of sub-capabilities per category.
- Highlights where the work is complex.
- Full map lets you drill any cell.
Bet the payoff
A short game: pick whether each sub-capability's payoff is mostly cost-out, revenue-up, or hybrid. The market pays these three buckets very differently.
- 8 sub-caps per round (product mode) or 6 inside a career lens.
- Answers scored against the Impact-ROI classifier + funding + hiring heat.
- Opens the full Impact-ROI map on reveal.
Money & Markets
How capital moves — fees, funding, deals, maturity, and the rulebook the firm operates under.
Where 165 bps actually goes
Every layer that skims something between the client and the portfolio. The 165 bps total is not what the advisor charges — it's the wallet-to-portfolio drag.
- Advisor fee: 100 bps (line on the invoice).
- Platform/TAMP + custody + funds + cash drag + tax friction: 65 bps hidden below the line.
- Illustrative $2M household at a boutique RIA.
Cost-out vs revenue-up: what's actually funded
Not every AI/workflow bet pays the same. Ops-side work compresses cost; advisor-side work expands the top line — and the market pays very differently for each.
- Category defaults: ops → cost-out, planning/engagement/growth → revenue-up, investing/AI-tools/platforms → hybrid.
- Per-sub-cap overrides applied where the workflow breaks its category default.
- Full Impact-ROI map (coming soon) plots payoff × hiring temp × deal volume.
Who keeps the fee
How the client fee is split between advisor, platform, manager, and custodian.
- % of total client bps per player.
- Snapshot — shifting as bundling changes.
- Full map explores margin lens.
Where fees are moving
Where fees are actually rising, falling, or holding.
- Direction × magnitude per line.
- Sourced from public disclosures + trend reports.
- Fees map shows the trend lens in Explore.
Priciest → cheapest channel
How much clients pay in each distribution channel.
- Average all-in bps.
- Skew high in relationship channels, low in direct.
- Channel × fee-type in the full map.
Which regulators pull the most weight
Regulator × obligation count, across every regime we track.
- A single obligation can name multiple regulators.
- Full map has 4 lenses + jurisdiction filter.
- Vendor pills show who solves each obligation.
How fast the rules are changing
Where the regulatory load is accelerating vs. easing off.
- Per-obligation velocity tag.
- Full map exposes the velocity lens.
- Filter by jurisdiction to see local pressure.
Where compliance work sits
Obligation load across the client lifecycle.
- An obligation can touch multiple stages.
- Highlights where compliance eats time.
- Full map ties obligations to vendors.
The regime landscape
How the tracked regimes stack up in raw obligation count.
- Regime tag per obligation.
- Global + US-heavy today, EU/APAC growing.
- Filter by regime in the full map.
Where capital is flowing
Funding activity across wealth-tech stages.
- Aggregated deal counts + $ volume.
- Full map: stage × sub-sector heat.
- Data refreshed monthly.
Widest fee spreads
Both extremes at once: full-service vs. self-serve pricing.
- Avg all-in bps per channel.
- Extremes shown for quick contrast.
- Full map has channel × fee-type.
Live Pulse
What's shifting right now — AI, geography, hiring, and the raw signals feed.
The scope of the atlas
The vendor + capability surface behind every card in this deck — and the share of it that already carries an AI or disruption verdict.
- Vendors = every logged company in the atlas.
- Sub-capabilities = leaves of the capability model.
- AI-led + contested counts come from the recompute pipeline.
Wealth-tech stack: heating up vs. cooling
Heating = disruption verdict is 'disrupted' or 'contested'. Cooling = 'mature' with dried-up funding.
- Verdicts come from the recompute pipeline (funding, new entrants, leader share).
- Delta % is a directional heat indicator, not a market share change.
- Full pulse page has the underlying scores.
How AI is landing across the stack
The AI-impact split across every tracked sub-capability.
- Bucketed from AI-native vendor share + legacy impact tag.
- AI-led = workflows being rebuilt; augmented = copilots bolted on.
- Full AI-impact map has the per-cap drill-down.
Where AI is already leading
The sub-caps flagged AI-led by the recompute pipeline.
- AI-led = workflows fundamentally rebuilt around models.
- Ranked by AI-native vendor share within the sub-cap.
- Click through for the full AI impact matrix.
Where the market is settled vs. up for grabs
The disruption verdict split — where incumbents still hold vs. where AI-native vendors are winning.
- Verdict = funding/vendor × new-entrant share − leader share.
- 'Contested' = mixed picture, incumbents pressured.
- Recomputed daily from the vendor landscape.
The most contested capabilities
The sub-caps where the disruption verdict is 'disrupted' or 'contested' — this is where the market is actually up for grabs.
- From the recompute pipeline (funding + new entrants + leader share).
- Ranked by disruption score.
- Click through for the full AI + disruption map.
Where hiring is running hot
Baseline-normalised hiring temperature per sub-capability.
- Temp = role-taxonomy × vendor footprint vs. baseline.
- 'Hot' = above-baseline intensity.
- Skills-heat map ranks the underlying skills.
Where wealth-tech teams are hiring right now
The full jobs map — every wealth-tech role we track, live.
- Scraped from firm careers + LinkedIn + ATS feeds.
- Filtered to wealth-tech scope.
- Full map has capability × seniority × firm cuts.
Latest signals off the wire
The full signals ticker page — every item links back to its source and is deduped before publish.
- Four lanes: Vendor, AI, Money, Talent.
- Deduped + fact-checked before publish.
- Also pushed to Telegram.
Settled vs. up for grabs
The live disruption verdict summarised on one dial — contested + disrupted vs. mature. Emerging sub-caps are excluded because they haven't landed a verdict yet.
- Verdict = funding + new-entrant share − leader share, recomputed daily.
- 'Contested' bundles disrupted + contested (the two that are moving).
- 'Settled' = verdict = mature (incumbents defended it).
Talent & Skills
The people side — real maps of the roles being hired and the skills that power them.
Top 5 climbing roles
Ranks catalogued roles by a hiring-pressure score with agentic / AI roles flagged so future work stands out.
- Hiring score blends job-feed velocity and pay-band pressure (0 → 1).
- Flame = AI exposure ≥ 0.9 (agentic).
- Powers /skills/roles too.
Where the gap pays
For every skill wealth-tech pays for, we score demand (postings + salary) and estimate how thin the trained talent supply is. The widest gaps are where firms pay premiums today.
- Demand = live postings + salary signal (0→1).
- Supply gap = share of postings where firms report struggling to fill.
- Ranked by demand × gap.
The hottest hiring lane
Aggregates the hiring signal across role families so you can see which lane is heating up at a glance.
- Each bar = mean hiring pressure across roles in that family.
- Mirrors the live Jobs Map.
- Full map drills into firm-level postings + skills.
Which families go agentic first
Share of roles in each family that already look agentic-eligible — a directional read on which lane reshapes first, not a raw headcount.
- Agentic-eligible = AI exposure ≥ 0.85 in the roles taxonomy.
- Share = agentic-eligible roles ÷ total roles in that family (percentages, not counts).
- Filter the role ladders map by Future to see them.
Workflow articulation
Workflow articulation tops the demand × gap rankings this cycle.
- Score = demand × supply-gap, both 0→1.
- Refreshed with each taxonomy sync.
- Click through to see it in the full mosaic.
Where the money is
Average US comp band across every role we catalogue in that family.
- Comp bands: 1=$70-110k, 2=$110-170k, 3=$170-260k, 4=$260k+.
- Family average across all offices.
- Individual role bands live in the ladders map.
Where wealth-tech talent moves
Directional talent movement across the wealth-tech stack over the last 12 months.
- Weight = share of role transitions in the LinkedIn / hiring feed sample.
- Sample is directional, not exhaustive.
- Full map explores by firm + role.
Front vs. back office hiring
Count of catalogued roles by office across every role family.
- Each role tagged to an office in the roles matrix.
- Counts, not weighted headcount.
- Full map cross-links to skills + games.
Where demand is running ahead of supply
The pay / supply mismatch across the top wealth-tech skills — where hiring managers report the hardest fills and salary premia outrun the available talent.
- Top 10 skills by demand (posting velocity + salary signal).
- Supply gap > 0.6 means hiring managers report a hard-fill signal.
- Signals where operator experience — not credentials — is the moat.
Where the jobs actually are
Ranked concentration of catalogued wealth-tech roles across the six career families — where the ladders are actually deep.
- Bar length + count = number of catalogued roles in that family.
- Tint is fixed per family so colors read consistently across the deck.
- Open the roles map to see comp bands + agentic exposure inside each ladder.