Skip to content

The roadmap

The rail keeps growing.

The version ladder

Where each edition sits.

V1

Available now

The Montex AlphaRail System — available now

The Excel edition, shipping today. Eleven governed workbooks, the full authority chain, three proprietary indicators, the operator manual library. $497, one time.

V2

Next

Advanced Strategies, optimized modules & open configuration

Still Excel — the same workbook family, rebuilt. Over 200 Advanced risk strategies, optimized modules carrying more powerful metrics and advanced telemetry, and the open-ended configuration engine. Every readout benchmark-driven. Roughly a year out, and free for every V1 owner when it lands.

V3

On the horizon

The MARS Command Center — the web edition

The rail rebuilt as a live web application, streaming the same advanced telemetry V2 introduces. Roughly two years out. A separate subscription product, not an upgrade path from the workbooks. Waitlist members walk in first.

The promise

Every owner gets the next edition free.

The Advanced Strategies library, the optimized telemetry modules, and the configuration engine land at no additional cost for anyone who already owns the V1 workbooks. Same Excel system, expanded. A one-time price should mean the thing you bought keeps getting better — not that you bought a frozen snapshot of it.

The cloud edition is a separate subscription product, not part of this upgrade.

MARS V2 — the architecture

More accounts, a longer horizon, and branches you construct.

V1 governs one account across one year, through branches the system defines. V2 changes all three of those at once — and that, rather than any single new metric, is what makes it a version rather than an update. Everything below is in build. Nothing here is on sale today, and V1 owners receive it at no cost when it lands.

3

Account lanes

5 yr

Managed horizon

8

Primitive branches per lane

6

Composite branches

Account structure

Three account lanes, each on its own clock

Run up to three accounts side by side in separate lanes. The lanes are independent in TIME, not just in balance — one can sit at week 42 of year one while another is at week 12, and every metric reads against that lane's own position on its own timeline. No forcing two accounts into a shared calendar to make the maths work.

  • Up to three concurrent account lanes
  • Independent week/year position per lane
  • Lane-scoped metrics, benchmarks and cadence
  • Lanes need not run in the same period, or at all

Horizon

A five-year rail, not a one-year one

V1 governs a single year. V2 extends the managed horizon to five, which changes what the system can even ask: compounding across cycles, multi-year gate behaviour, and whether an edge survives conditions a twelve-month window never contains.

  • Five-year managed horizon per lane
  • Cross-year cycle and gate history
  • Long-horizon benchmark continuity

Branch architecture

Eight primitive branches, six composite

Each lane holds up to eight primitive branches. From those, the operator composes up to six composite branches — any combination they choose, or none at all. One composite or six; the structure is the operator's decision rather than a shipped preset.

  • Up to 8 primitive branches per lane
  • Up to 6 composite branches, operator-composed
  • Composites built from any primitive combination
  • Operator-defined branch construction, as an optional layer

Branch Construction Matrix

The branch becomes a configurable object

Entry, exit, model, and attached strategy all become fields the operator sets rather than behaviour inherited from a preset. A branch stops being a fixed lane on the rail and becomes something constructed — and therefore something that can be compared against a differently constructed one.

Risk governance

Dynamic risk throttle at the branch level

V1 governs risk through one chain: gate, tier, pool, smart capacity, per-trade risk. V2 adds a second layer underneath it, operating per branch — so a branch that has just taken a loss can step its own risk down without the whole book stepping down with it.

  • Max_Risk_%
  • ReduceRisk_After1Loss_%
  • Reset_On_Win_Y/N
  • Max_Consec_Reductions
  • Chain: gate cap → throttle pool → branch eligibility → branch multiplier

Exit engineering

Trailing families as modules

V1 centres on ATR trailing for trend branches. V2 treats the trail as an interchangeable module, so a different trailing logic is a configuration change rather than a rebuilt strategy.

  • ATR trailing
  • Parabolic SAR trailing
  • Fractal trailing

Position engineering

Scale-in, scale-out, and time at full scale

Deployment stops being a single decision at entry. Size can be built and reduced through the life of a position, and the time spent fully deployed becomes a measured quantity rather than an impression.

  • Scale-in and scale-out ladders
  • Time at full scale
  • Initial and maximum exposure %
  • Adverse excursion after scale
  • Marginal EV of added size

Research management

Scenario Registry and A/B comparison

V1 has scenario profiles. V2 turns them into a persistent experiment system: named, stored configurations you can hold constant and vary one rule against — same sample, same trades, different management. That is the only structure in which a management-rule question has a real answer.

  • Named, persistent scenarios with run groups
  • Lane, risk %, branch weights, trade frequency per scenario
  • Scenario Compare A/B on a fixed sample
  • Scenario-stamped exports

Simulation

Monte Carlo snapshots

A snapshot store sits alongside the existing 50,000-path Dynamic 7-Tier benchmark rather than replacing it. Frozen distributions mean the rest of the system reads a stable, auditable result instead of re-simulating — and a result you can point at months later is a different kind of evidence from one that moves each time you open the file.

  • Run ID, scenario, lane
  • EV mean and standard deviation
  • P10 / P50 / P90
  • Robustness score
  • Fat-tail frequency

Deployment visibility

The Branch Deployment Matrix

Every branch activation state across all three lanes, shown as one grid. Each lane carries up to eight primitive and up to six composite branches, so the matrix holds up to forty-two branch cells at full extension. The question it answers is the one that is hardest to hold in your head from a spreadsheet: what is actually live right now, and what is sitting idle.

  • 3 lanes × up to 14 branches per lane
  • 8 primitive + 6 composite per lane
  • Up to 42 branch cells at full extension
  • Active / inactive state per cell

Analysis scope

An open-ended grain dimension

Instead of building dedicated columns per pair, per timeframe, per session, analysis takes a grain and a scope value — pair, strategy, timeframe, or tag. One structure that answers the question you have rather than a fixed set of the questions someone anticipated.

  • Grain: all · pair · strategy · timeframe · tag
  • Scope value set per read

Risk telemetry

Regime expected shortfall by branch style

Not only the expected value of a trend, no-trend, or overflow branch, but its average outcome inside its worst tail of results. Governance needs the shape of the bad side, not the average of everything.

MARS V2 — the Branch Construction Matrix

Every branch, specified rather than inherited.

In V1 a branch behaves the way the system defines it. In V2 the operator constructs it — entry, exit, model, attached strategy, and the management ladder underneath. The full field set is below. Branch variants remain optional: build them if you want that control, ignore them entirely if you don't.

Branch ID

Slot

Active status

Branch type

Branch style

Structure mode

Strategy attached

BE trigger

TP target

ATR trail

Risk throttle

Branch weight

Branch hit rate

Partial %

Scale-in

Scale-out

Time at full scale

Partial TP ladder

Defense ladder

ATR trailing

SAR trailing

Fractal trailing

MARS V2 — two ways to read the same system

Basic view. Advanced view.

The same workbook, read at two depths. At the trigger you want the reading that resolves a decision. At the review desk you want the distribution behind it. V2 makes that a system-wide setting rather than a matter of which file you happen to have open. Both depths ship inside V2 — this is a reading mode, not a paid tier.

Basic view

Operator reading

What you need at the click. The reading that tells you whether to deploy, hold, or stand down — and nothing that would slow that decision down.

  • Expected value
  • Probabilities
  • Simple guardrails
  • Quota status
  • Pacing
  • Basic risk state
  • Straightforward badges

Advanced view

Quant reading

The same workbook, opened up. For the review desk rather than the trigger — where you are interrogating the structure of the edge rather than acting on it.

  • Monte Carlo distributions
  • Attribution
  • Uncertainty
  • Skew and kurtosis
  • Regime analysis
  • Factor tilts
  • Tail behaviour
  • Advanced risk statistics
  • Cross-path comparison

MARS V2 — the headline feature

Over two hundred advanced strategies. You pick which ones run.

These are not signals and they do not replace the rail. They are additional risk-management rules that layer on top of how the system already governs your account — the operator chooses which strategies to activate, and each one adds its own conditions to how risk gets deployed, laddered, trailed, and cut. The governance stays; the strategies sharpen it.

200+

Strategies

5

Categories, 40 each

Opt-in

Every one, operator-selected

Volatility & Derivative Proxies

40

Variance Guild

Read the volatility surface and let it decide the ladder. Break-even triggers, trail widths, and runner permissions all scale with sigma instead of sitting at a fixed number.

  • Vol-Regime Switcher — switch ladders when the vol badge flips
  • Vol-Conditioned BE — break-even triggers that scale with sigma
  • Overflow-Only in High-σ — runners permitted only above a volatility threshold
  • Shock-Absorber Trail — the trail widens as volatility spikes
  • Sigma Expansion Runner — ride the expansion, accept the flat stretches
  • Implied–Realized Carry — harvest the structural gap, stand down in shocks
  • Vol-Term Structure Proxy — favour short-horizon dislocations
  • Vol-Synced Pyramids — add only into a volatility uptick

Cross-Asset & Relative Value

40

Correlation Guild

Stop trading a pair in isolation. Confirm the trade against the wider market — the dollar index, yields, equities, commodities — before the rail authorizes risk.

  • DXY Confirmation Overlay — trade EURUSD only when the dollar index agrees
  • AUDUSD–Copper Confluence — trend trades only on the commodity confirm
  • Cross-Asset Shock Gate — disable entries when the stress index fires
  • Basket Mean-Revert — fade tri-pair deviation on a z-score
  • Vol Spillover Arb — read the cross-asset volatility lead

Macro & Factor Tilt

40

Mini-Ecosystem Cluster

Tilt the whole book toward the macro regime. Real-rate differentials, carry, and risk-on/risk-off state bias which branches get deployed and how hard.

  • Real-Rate Differential — lean toward the higher real yield
  • Dollar Smile Proxy — favor USD length in risk-off regimes
  • Yield Curve Overlay — bias the majors by 2s10s shifts
  • Carry/Value tilt — structural bias from the spot–forward basis

Execution & Microstructure

40

Execution Guild

The rules that live between the signal and the fill. Session timing, spread conditions, and order tempo — the layer where most edge quietly leaks away.

  • Session-gated deployment — risk only inside the liquid windows
  • Anti-Chop Gate — disable runners when the chop index is high
  • Stall-Then-Burst — wait for the micro volatility stall, then break out
  • Trail-efficiency feedback — trail widths tuned by realized giveback
  • Gamma-Trail Hybrid — wider trails where shakeouts cluster
  • Skew-Adjusted BE — break-even safety scaled to downside skew

Advanced Portfolio Overlays

40

Governance Guild

Account-level rules that sit above every individual trade. Tail sleeves, vol-parity sizing, and drawdown-coupled brakes that govern the book as one position.

  • Tail-Insurance Split — route 10–15% of risk to no-partial tails only
  • Vol-Parity Rebalance — size by volatility targets across pairs
  • Drawdown-Vol Coupler — tighten when drawdown × volatility runs hot
  • Risk-Parity-Across-Pairs — weight the book to equal risk contribution
  • Overflow Sigma Sleeve — reserve risk for the high-σ tail, pay the patience tax
  • Shock-Sigma Gate — a crisis brake that protects expectancy
  • Kurtosis Regime Bias — tilt toward the fat-tail weeks

MARS V2 — the instrument upgrade

Optimized modules. More powerful metrics. Advanced telemetry.

The workbooks are not merely gaining features in V2 — they are being rebuilt as instruments. Every module is optimized around the metrics that actually move a decision, and every one of them reports against benchmark performance rather than reporting in isolation. A number that cannot be compared to what should have happened is not a metric. It is a rumour.

Optimized

Every module, rebuilt

The eleven workbooks re-engineered around what governs a decision — sharper engines, cleaner surfaces, faster recalculation across the authority chain.

More powerful

Metrics that decide

Deeper readouts on the dimensions that carry weight — the ones that change what you deploy, not the ones that merely describe what you did.

Telemetry

Benchmark-driven throughout

Every readout reports against the benchmark. You do not see a figure; you see a figure and the band it should have landed in. That is the difference between a dashboard and an instrument.

The V3 Command Center streams this same telemetry two years out. What V2 builds into the workbooks is what the cloud edition will render live — the instrument comes first, the screen comes after.

MARS V2 — the configuration engine

The presets become yours.

Today the workbooks ship with the assumptions the system was built on. In V2, the performance trackers — CP3, the Weekly EV Scorecard, and the rest — open up. You set the benchmarks, the branch mix, the risk ranges, and the tail thresholds your own account should be measured against.

Open-ended branch configuration

Branches stop being fixed. Define how many run, which mix deploys across a day or a week, and how many trades each one is allowed — instead of inheriting a preset.

Configurable benchmark hit rates

Set the hit-rate levels the system benchmarks against, per branch, instead of trading someone else's assumptions about your edge.

Adaptive risk ranges

Define the deployment range the throttle works inside, so the tier ladder is calibrated to the account you actually run.

Rolling averages & standard deviation

Every metric gains a transition view: rolling windows and standard-deviation bands that show whether a number is drifting, stabilizing, or breaking down.

Deeper gate-transition metrics

Not just which gate you're in, but how you move between them — dwell, transition frequency, and the pressure building underneath a gate change.

Fat-tail & accelerator benchmarks

Configurable benchmark levels for fat-tail capture, hybrid accelerators, and overflow deployment — the convex end of the system, made measurable.

M.A.R.S. V2 — AI Deployment Architecture

One Analytical Management Architecture.Multiple Ways to Deploy It.

M.A.R.S. AI Intelligence is being designed as a portable analytical management architecture, not a platform-dependent collection of bots. Specialist roles, reporting relationships, authority boundaries, integrity controls, benchmark layers, executive synthesis, and handoff standards remain consistent as V2 expands the environments through which the architecture can operate.

The runtime may change. The M.A.R.S. analytical doctrine does not.

01 · System depth

CorePro

How much of the M.A.R.S. workbook system is covered.

02 · AI intelligence level

AI Analyst TeamAI Command Team

Question-led specialist analysis or coordinated executive synthesis.

03 · Deployment environment

GrokbotHermesOpenClaw

Where the same analytical management architecture operates.

Three independent selection axes—not twelve separate products.

Available nowManaged AI Deployment

Grokbot Edition

Deploy the team. Skip the infrastructure.

The current production environment for M.A.R.S. AI Intelligence, designed for customers who want the complete analytical organization operating quickly without maintaining private agent infrastructure.

Best for

  • Individual and professional traders
  • Consultants and small teams
  • Customers prioritizing simplicity
  • Customers wanting minimal infrastructure administration

Key strengths

  • Managed runtime
  • Rapid deployment
  • Persistent agents
  • Scheduled workflows
  • Google Drive integration
  • Structured reporting
  • Configuration-ready agent templates
  • Minimal server administration
Coming soonProfessional Agent Infrastructure

Hermes Edition

Configure every specialist. Control every workflow.

A planned professional custom deployment for organizations that want deeper control over each specialist's model requirements, memory, skills, tools, schedules, credentials, state, and workflow responsibilities.

Best for

  • Quantitative and advanced traders
  • Financial researchers and analysts
  • Developers and automation consultants
  • Data-intensive professional organizations

Key strengths

  • Independent specialist environments
  • Role-specific model selection
  • Advanced automation
  • Structured delegation
  • Portable configuration
  • Custom integrations
  • Local, cloud, VPS, or managed hosting potential
Coming soonSovereign AI Command Infrastructure

OpenClaw Edition

Own the infrastructure behind your AI organization.

A planned private and sovereign deployment class for organizations seeking dedicated infrastructure, configurable agent routing, deeper integrations, private deployment options, and maximum extensibility.

Best for

  • Proprietary trading and research teams
  • Fintech companies and automation agencies
  • Larger professional teams
  • Organizations with private data systems or APIs

Key strengths

  • Dedicated infrastructure
  • Controlled agent routing
  • Private and VPS deployment
  • Custom internal integrations
  • Model flexibility
  • Multi-channel operations
  • Maximum infrastructure control

The M.A.R.S. reporting chain

M.A.R.S. source workbooks

“The governed evidence base”

Specialist analysts

“What happened?”

Monte Carlo Benchmark Directorate

“How normal or abnormal was it?”

Executive analytical offices

“What does it mean for capital, deployment, edge, and execution?”

Alpha Conversion

“How effectively was expectancy converted into alpha?”

Chief of Staff

“What matters most?”

Same management architecture. Different runtimes.

Fixed Architecture. Flexible Intelligence.

Defined governance. Dynamic inquiry.

Official M.A.R.S. AI configurations use defined roles, reporting relationships, authority boundaries, workbook assignments, handoff formats, and escalation procedures. Customers may ask dynamic questions and generate custom analyses without changing the certified reference architecture.

M.A.R.S. Certified ArchitectureM.A.R.S.-Compatible CustomModified / Non-Certified

Custom AI Organizational Architecture

Planned for M.A.R.S. V2

We Don't Just Configure Agents.We Engineer How the Organization Works.

Every company operates differently. A useful AI workforce should be designed around its actual responsibilities, information flows, reporting relationships, analytical requirements, approval structure, and operational cadence.

M.A.R.S. V2 is planned to expand beyond fixed agent templates with bespoke organizations defining roles, models, data access, memory, tools, communication, delegation, escalation, reporting, integrity controls, executive synthesis, and operating rhythm.

We engineer how the organization thinks, reports, escalates, and works.

Organizational hierarchy design

Define specialists, managers, executive agents, oversight roles, reporting relationships, supervisory layers, and escalation paths.

Integrity or compliance roles may operate independently across approved departments.

Specialist role engineering

Design every agent around a professional responsibility—from research, finance, and operations to compliance, engineering, risk, and executive synthesis.

Each role receives its own operating doctrine and information scope.

Model-to-role architecture

Match different intelligence profiles to different jobs: deep reasoning for synthesis, specialist capability for technical work, fast models for routing, or private models for sensitive data.

The right model for the right role.

Memory architecture

Define independent specialist memory, shared departmental memory, executive-only context, temporary task context, and archived reporting memory.

Memory follows organizational responsibility instead of being shared everywhere.

Tools and data-source ownership

Assign spreadsheets, APIs, databases, CRM, Google Drive, documentation, code repositories, reporting systems, and messaging tools by role.

Agents access what their jobs require—not necessarily everything.

Agent communication design

Engineer which specialists, managers, executives, and oversight roles may communicate, including authorized cross-organization access.

Structured communication beats unrestricted agent chatter.

Handoff and report routing

Specify how structured reports, validation results, benchmark comparisons, exceptions, escalation notices, and executive briefs move upward.

The goal is to prevent summary drift and uncontrolled information propagation.

Escalation and authority design

Define what stays with a specialist, what escalates on conflicting evidence, what requires integrity review, and when a human operator must decide.

Authority boundaries are part of the architecture.

Automation and cadence design

Coordinate real-time, event-driven, daily, weekly, monthly, quarterly, and on-demand work across specialists operating at different cadences.

The organization works on a designed rhythm.

Executive synthesis

Convert distributed work into department reports, cross-functional summaries, risk briefings, management packets, and strategic recommendations.

The customer receives a reporting organization, not disconnected outputs.

A business-neutral operating pattern

Data / systems
↓
Specialist agents
↓
Department leads
↓
Executive synthesis

Integrity / QA agent

Authorized cross-layer verification and escalation

↓ Human decision maker

Reference Architecture or Custom Architecture

M.A.R.S. Certified Reference Architecture

A pre-engineered, version-controlled analytical hierarchy with defined roles, reporting paths, authority boundaries, workbook assignments, operating standards, and escalation procedures.

Core and Pro AI Analyst Teams and AI Command Teams use the official M.A.R.S. reference hierarchy.

Custom AI Organizational Architecture

A separate bespoke implementation engineered around a customer's company, workflow, departments, data systems, reporting requirements, and operating model.

A modified company architecture is not automatically a M.A.R.S.-certified configuration.

Grokbot

Managed custom organization

Customize roles, reporting hierarchy, handoffs, schedules, and company-specific data organization inside a managed platform.

Best when organizational customization matters more than server administration.

Hermes

Professional specialist architecture

Engineer independent specialist profiles, memory, skills, schedules, models, tools, and portable worker configurations role by role.

Best when each specialist's operating environment must be deeply tailored.

OpenClaw

Organization + infrastructure architecture

Engineer both the digital organization and the dedicated environment connecting its routing, integrations, channels, and private systems.

Best when the customer wants control over the organization and the infrastructure operating it.

Who is this for?

Organizations that have outgrown a single general-purpose assistant and need coordinated specialists operating under a defined structure.

  • Trading and investment teams
  • Financial research firms
  • AI consulting companies
  • Professional service firms
  • Operations-heavy businesses
  • Analytics and research teams
  • Software companies
  • Sales and support organizations
  • Companies with complex approval chains
  • Businesses with specialized reporting requirements

When one AI assistant isn't enough, build the organization.

Four operating examples

Financial research team

Data Analyst → Risk Analyst → Research Director → Executive Brief

Operations organization

Inventory + Service + Scheduling Agents → Operations Manager → Executive Summary

AI consulting agency

Research + Solutions + Implementation + QA → Project Director → Client Report

Trading / M.A.R.S.

Specialists → Monte Carlo → Executive Offices → Alpha Conversion → Chief of Staff

Custom Architecture Services · Planned for V2

A higher-touch professional implementation.

Architecture scope, implementation requirements, availability, and professional-services pricing will be announced separately.

Discuss a Future Custom Deployment
Architecture discoveryWorkflow mappingAgent-role designHierarchy engineeringModel-selection strategyTool and data-source mappingMemory architectureReporting protocol designHandoff schema designAutomation schedulingIntegration planningQA and validationDeployment supportDocumentationOptional ongoing maintenance

Deployment comparison

Compare Planned M.A.R.S. AI Deployment Environments

Future capabilities remain planned and may depend on the selected platform, hosting model, integrations, and final V2 implementation.

CapabilityGrokbotHermesOpenClaw
M.A.R.S. reporting hierarchy✓✓✓
Specialist analytical roles✓✓✓
Monte Carlo benchmark layer✓✓✓
Data Integrity Controller✓✓✓
Executive analytical offices✓✓✓
Alpha Conversion✓✓✓
Chief-of-Staff synthesis✓✓✓
Structured handoffs✓✓✓
Conflict preservation✓✓✓
Certified architecture concept✓✓✓
Managed deploymentPrimaryOptional / deployment dependentOptional / deployment dependent
Setup simplicityHighestModerateModerate / advanced
Per-agent customizationHighVery highVery high
Independent specialist statePlatform managedAdvancedAdvanced
Per-agent model flexibilityPlatform basedHighHigh
Multiple model providersPlatform dependentPlannedPlanned
Local/private model potentialPlatform dependentPlannedPlanned
Custom toolsPlatform dependentAdvancedMaximum
Custom APIsPlatform dependentAdvancedMaximum
Advanced automationStrongAdvancedAdvanced
Private VPS deploymentPlatform managedPlannedPlanned
Dedicated private environmentPlatform managedPlannedPlanned
Infrastructure controlManagedHighMaximum
Agent routing controlWorkflow / platform basedConfigurableStrong / explicit
Multi-channel integrationsPlatform dependentConfigurableStrong
Custom organizational architectureYesAdvancedAdvanced / infrastructure-level
Custom workflow engineeringYesAdvancedMaximum control
Custom reporting hierarchyYesYesYes
Role-specific operating environmentsPlatform basedAdvancedAdvanced
Model-to-role customizationPlatform basedHighHigh
Custom memory architecturePlatform basedAdvancedAdvanced
Custom communication topologyWorkflow definedConfigurableStrong / infrastructure-level
Custom escalation pathsYesYesYes
Custom internal-system integrationPlatform dependentAdvancedMaximum
Private infrastructureManaged platformAvailable by deploymentStrongest
Best fitMost customersAdvanced professionalsFirms / infrastructure users
StatusAvailable nowComing soonComing soon

Which deployment fits your operating model?

Choose by the control you need.

Grokbot

Available now

“I want the M.A.R.S. AI organization without managing infrastructure.”

Trader · Professional · Consultant · Small team · Simplicity-first buyer

Hermes

Coming soon

“I want deeper control over how each AI specialist performs its job.”

Advanced trader · Quant · Researcher · Analyst · Developer

OpenClaw

Coming soon

“I want control over the environment running the entire AI organization.”

Firm · Desk · Agency · Professional team · Private-infrastructure organization

V2 workbook upgrade

The M.A.R.S. V2 workbook upgrade remains part of the existing V1-to-V2 upgrade path for eligible owners.

Separate infrastructure offerings

Future Hermes and OpenClaw deployment environments are not being announced as part of the free workbook upgrade. Pricing and availability will be announced separately.

V2 expands the analytical and deployment architecture.

V3 rebuilds the rail as a native web application.

MARS V3 — the Command Center

The rail, in the cloud.

The most advanced edition of the system — the whole rail rebuilt as a live web application, streaming the same advanced telemetry V2 introduces to the workbooks. Roughly two years out. It is a separate subscription product with its own pricing, not an upgrade path from the Excel editions.

$39.95/mo

Alpha Core

Feature split to be announced

$69.95/mo

Alpha Pro

Feature split to be announced

$119.95/mo

Alpha Ultra

Feature split to be announced

$139.95/mo

Alpha Quant

Feature split to be announced

Contact us

Institutional

Custom-designed per desk — priced on enquiry

Five subscription levels. What sits inside each one will be announced closer to launch — waitlist members hear first, and get in first.

Questions about what's coming?

Ask about the V2 timeline, the strategy library, the upgrade path, or the cloud edition.