Crypto intelligence and execution infrastructure for exchanges, funds, banks and fintech platforms.
Verified human analysts, AI agents and algorithmic strategies publish risk-capped, fully logged trade signals on BottomUP. We package that infrastructure as data, analytics and technology rails your institution can license, while you keep the license and the customer.
Institutional research on demand.
Ask Foxy a question in plain language and receive a full research note in about a minute: market structure, derivatives, positioning, on-chain flows, scenarios and the levels that matter. No contract, no integration. Buy credits and pay per report.
- 1Create an account
Sign in with your work email. If a BottomUP partner introduced you, their code applies their discount automatically.
- 2Buy credits
Card payment through Stripe; packs from $50. Invoicing and bank transfer for larger allocations.
- 3Ask, read, export
Standard or deep reports in English or Turkish, kept in your history and exportable to PDF.
The signal layer institutions can't build
Institutions entering digital assets face no shortage of opinions, but an acute shortage of verifiable, risk-standardized, machine-readable trading intelligence. Banks, funds and brokers cannot consume Telegram calls or influencer threads. They need audited track records, uniform risk accounting, defensible data rights and clean APIs.
BottomUP built exactly that. Every trade idea, human, AI or algorithmic, is published under one risk methodology: at most 1.5% of the book at risk per trade, enforced through fixed-fractional position sizing.
On top of the verified signal layer sits Foxy AI, our market analyst built on frontier-model infrastructure. It listens to market data and the news flow continuously and fuses on-chain intelligence with a source no competitor holds: the live positioning and pending limit orders of our verified analyst pool.
BottomUP sells data, analytics and technology rails. Your institution keeps the license, the suitability obligations and the customer relationship.
Risk-capped, verified signal infrastructure
A stopped-out trade always costs exactly 1.5%. Every signal is one standardized risk unit (1R) and every outcome a clean R multiple, which makes track records portable across any book size and comparable across every provider.
The cap is the floor. Foxy AI operates on top.
Position sizing is the entry ticket. What defends capital and compounds returns is how a live trade is carried, and that is where our AI layer works on every open position.
- Adaptive stop management. Stops are re-evaluated in real time against volatility regime shifts, funding and on-chain liquidity: tightened to protect gains or trailed to let winners run, inside the same 1R budget.
- Dynamic position carrying. Partial take-profits and scale-outs at defined R multiples, with re-entry logic on structural pullbacks.
- Regime-aware exposure. Book-wide risk is monitored across correlated positions and throttled when regime models flag stress.
- Human + AI oversight. Every adjustment is logged, timestamped and auditable.
Why it matters to buyers
- Portable performance. R-denominated track records replicate one-to-one on any book size. A desk running 0.25% risk per trade inherits the same performance profile.
- Apples-to-apples comparison. Every provider, human, AI or algorithmic, runs under identical risk rules and accounting, so track records are directly comparable.
- Clean institutional accounting. Expectancy, drawdown and streak risk expressed in R convert to any risk budget in seconds.
- Machine-readable by design. Timestamped entries, exits, stops and targets. No parsing, no ambiguity, no survivorship editing.
What gets logged
- →Full trade lifecycle: entry, stop, targets, exit and timestamps
- →Win rate and standardized monthly PnL per provider
- →R multiple per trade for expectancy and drawdown-in-R analytics
- →Executed and pending limit orders across the verified pool
- →Every AI-driven adjustment, attached to the original signal
Sharpe, Sortino, max drawdown, profit factor, slippage-adjusted returns and per-signal capacity estimates are derived from the same logs.
Four layers, bought separately or stacked
A frontier-model market analyst that fuses on-chain flows, market and order book data with the live positioning of our verified analyst pool. Deploy it as an in-app AI analyst for exchanges and banks, a research engine for brokers and asset managers, an SDK for fintech and tokenization platforms, or as recurring institutional research.
A normalized, timestamped feed of verified, R-based trade signals, tiered by latency, volume and historical depth. Plus an anonymized, aggregated smart-money intent dataset: limit-order clustering and long/short concentration across the verified pool.
The full delegation engine inside your own app and brand: end users connect wallets and route portfolios through verified analysts, AI agents or algorithmic strategies, with conservative, balanced and aggressive profiles built from one signal pool. For custody providers, an overlay that lets stored assets join active strategies without leaving safekeeping.
Real-market simulated trading under the same enforced risk framework, with Foxy as an always-on mentor. Licensed per seat to trading academies and to institutions onboarding staff to digital assets.
Built on frontier AI, defensible by design
Foxy AI is not a chatbot wrapper. It is our own application with its own data fusion pipeline, market listening layer and a data source that exists nowhere else. The orchestration layer is model-agnostic, so the reasoning core can be upgraded as the frontier advances, without vendor lock-in.
Frontier reasoning core
Anthropic's Claude as the analysis engine, wrapped in BottomUP's own agent orchestration, prompt architecture and output controls. Accessed under commercial API terms: submitted data is not used to train foundation models.
Real-time market listening
Continuous price, volume and order book ingestion via exchange and aggregator integrations (OKX, CoinGecko). Analysis reflects the live tape, not a snapshot.
News flow monitoring
Market-moving news and events are tracked and fused into every analysis, so users see why a chart is moving, not just that it is.
On-chain intelligence
Arkham integration for wallet-level flows and smart-money movement, connecting on-chain behaviour to market structure.
Proprietary positioning layer
Live executed orders and pending limit orders from BottomUP's verified analyst pool. A source no other vendor holds.
Who buys what, and why
| Vertical | Layer | Why they buy |
|---|---|---|
| Crypto exchanges | L.03 + L.01 | Retention and engagement; copy-trade flow generates commission volume |
| Hedge funds & prop desks | L.02 | An alpha source in R, scalable to any book size |
| OTC desks & liquidity providers | L.02 | Early warning when retail and smart-money flow diverge |
| Quant funds & data buyers | L.02 | Net-new alternative data: verified-analyst limit-order clustering |
| Private banks | L.01 + L.03 | Crypto advisory for HNW clients without an in-house desk |
| Custody banks | L.03 | Put idle stored assets to work through the safekeeping overlay |
| EAMs & family offices | L.01 + L.02 | Outsourced crypto expertise backed by verified track records |
| Digital banks & fintechs | L.01 | An in-app AI crypto analyst as a retention feature |
| Brokers (CFD / FX) | L.01 + L.02 | Crypto research at scale; MT4/MT5 bridge on the roadmap |
| RWA & tokenization platforms | L.01 | An embedded asset-analysis assistant that supports in-platform liquidity |
| Financial media | L.01 + L.02 | AI coin analysis and positioning indices as content |
| Corporate treasury | L.01 | Risk analytics for crypto held on balance sheet |
| Trading academies | L.04 | Real-market simulated trading with an AI mentor |
Priced the way institutions budget
| Product | Layer | Commercial model | Budget line |
|---|---|---|---|
| Foxy AI | L.01 | Monthly SaaS + API usage (per-query tiers) | Technology |
| Institutional research | L.01 | Annual retainer + per-seat access | Research |
| Signal API | L.02 | Annual data license, tiered by latency, volume and depth | Market data |
| Positioning Data Feed | L.02 | Enterprise license, limited seats per market | Alternative data |
| Copy-trading infrastructure | L.03 | Setup fee + AUM bps + volume revenue share | P&L / distribution |
| Education environment | L.04 | Per-seat annual license | Training / L&D |
A flexible revenue matrix
Every layer supports fixed SaaS fees, AUM basis-point share or a success-fee / alpha share, so the structure fits your procurement process rather than the other way round.
Limited seats on positioning data
Alternative data that everyone owns stops being alpha. The Positioning Data Feed is sold in a limited number of seats per market, which keeps it useful for the desks that hold it.
Four regulation-ready markets
UAE
A dense concentration of exchanges, prop desks, family offices and a major regional OTC hub, with navigable licensing and fast decision cycles.
London
Europe's deepest pool of hedge funds, quant funds and alternative-data buyers, with firms selecting vendors ahead of the UK cryptoasset regime.
Switzerland
External asset managers and multi-family offices facing client demand for crypto without in-house research, and custody banks with idle stored assets.
Singapore
Thousands of single family offices that speak the R-capped Signal API's quantitative risk language, and the region's tokenization and RWA hub.
In every market our regulatory posture is the same: we supply data and infrastructure, and the licensing perimeter stays with the client.
Answering the hard questions first
BottomUP does not custody client funds, does not execute trades under its own brand in white-label deployments and is not the regulated customer-facing entity. The client remains responsible for licensing, suitability, onboarding, KYC/AML and user-facing obligations.
Positioning data is anonymized, aggregated and delayed where required, and licensed only under user and analyst agreements that explicitly grant those rights. Individual orders are never exposed.
Anti-front-running by design
Positioning data enters the feed only above a minimum aggregation threshold and with tiered time delays. Buyers can never trade against an identifiable provider’s order.
Audit trail
Every signal lifecycle and every Foxy reasoning step is preserved in timestamped, immutable logs.
AI governance
Enterprise frontier-model infrastructure with governance aligned to MAS FEAT principles and EU AI Act concepts: documented model use, output monitoring and human oversight.
Compliance & audit export
Signal and AI-decision exports formatted for VARA, FCA, FINMA and MAS reporting needs.
Enterprise sandbox
API keys to test R-normalized signal history and delayed positioning data in a self-serve simulator before contracting.
Security & SLAs
SOC 2 Type II attestation, with ISO 27001 to follow, and per-tier uptime, latency and support commitments.
Signal logging, risk enforcement, PnL accounting and Foxy AI run in production today. Institutional delivery (enterprise API, sandbox, audit export) is being rolled out with our first institutional partners.
The verification standard is unclaimed
Regulatory windows are open. The UK regime is finalised and VARA, FINMA and MAS already support the data-vendor model. Firms are choosing data and infrastructure partners now.
AI agents are entering markets. BottomUP is one of the few venues where humans, agents and algorithms are measured on identical terms.
Adoption is outpacing tooling. Institutional crypto adoption is accelerating while research and signal infrastructure remain retail-grade.
No one owns verification. Copy-trading platforms are unaudited and data vendors have no positioning intent. The standard is unclaimed.
See the data, the demos and the track records.
Tell us which layer you are evaluating and where you operate. We will walk you through the product, R-normalized signal history and a commercial structure that fits your budget line.
BottomUP, Inc. is not a registered investment adviser, broker-dealer or custodian. Information on this page describes data and technology products for institutional clients and is not investment advice. Past and simulated performance is not indicative of future results. Products marked roadmap are not yet generally available.