Sentralis
Sentralis is a non-custodial, read-only portfolio analytics platform for crypto holdings. It ingests positions from Binance, Kraken, Coinbase, Bybit, Gate.io, and manual entries, then runs nine scenario engines (Monte Carlo, historical replay, liquidity, macro sensitivity, correlation regime, counterparty analysis, and others) to generate risk metrics, stress-test results, and AI-assisted commentary. The platform includes six workbench modules for durable investigations: Portfolio Teardown, Event Decomposition, Time Machine, Delta Autopsy, Marginal Risk, and Pre-Mortem. All engines and metrics are exposed via REST API and MCP endpoints, allowing agencies to embed risk analysis into custom dashboards or advisory workflows without rebuilding the underlying math.
Sentralis is a non-custodial, priced at $20.83 a month on the Pro (Annual) plan, integrating with Binance, Kraken, Coinbase and Bybit. InnovaAI rates it 4.8 of 10 for agency adoption, best for Account Executive, Strategist and Operations Manager roles.
Agency Audit
Sentralis is a non-custodial portfolio analytics platform that turns crypto holdings from wallets, exchanges, and manual entries into risk metrics, scenario simulations, and AI-assisted reports. For agencies serving crypto-holding clients or offering wealth-management advisory, it provides a professional analytics layer that Account Executives and Strategists can use to deepen client conversations around portfolio stress-testing, counterparty exposure, and allocation decisions. The platform exposes nine scenario engines (Monte Carlo, historical replay, liquidity, macro sensitivity, correlation regime) plus six workbench modules via a read-only interface, eliminating the need to build or license these analyses separately.
3recommended
60/mo
$4,479/mo
Moderate
Illustrative scenario. Not a guarantee. Net capacity is the value of reclaimed time at $75/hr, less the lowest verified paid base plan (flat plan cost is shared). Hours saved come from the service estimate; implementation, taxes, and unprovided usage charges are excluded.
- Account Executive handling client portfolio stress testing
- Strategist handling counterparty exposure decomposition
- Operations Manager handling portfolio risk monitoring and alerts
- Your agency does not serve crypto-holding clients or does not advise on digital-asset allocation; Sentralis has no application outside that domain.
- Your team operates in a regulatory environment where client portfolio data cannot be imported into a third-party SaaS platform, even in read-only mode; Sentralis requires API or manual entry of holdings.
- Your clients expect real-time portfolio rebalancing or execution capabilities; Sentralis is read-only and does not support trading or custody workflows.
Internal Adoption Path
$20.83/mo
$20.83/mo flat plan
60 hr/mo
3 seats × 20 hr each
$4,500/mo
modeled at $75/hr labor rate
$4,479/mo
value − subscription cost
In this model, 3 seats reclaim 60 hours of team time each month. Valued at $75/hr that is $4,500/mo, and after the $20.83/mo subscription it leaves $4,479/mo of capacity for billable client work.
Illustrative scenario. Not a guarantee. Uses the lowest verified paid base plan. Implementation, taxes, and unprovided usage charges are excluded.
Platform Features
Core capabilities of Sentralis
Nine scenario engines
Monte Carlo, historical replay, liquidity, macro sensitivity, correlation regime, and counterparty analysis scenarios run on client portfolios without manual setup. Account Executives use these to answer stress-test questions in real time during client calls, replacing hours of spreadsheet modeling.
Portfolio Teardown and Event Decomposition workbench
Durable investigation modules that break down portfolio behavior by asset, exchange, chain, and strategy. Strategists use these to isolate concentration risk and counterparty exposure across venues, compressing multi-day analysis into a single session.
Scheduled alerts and reports
Alerts fire on VaR, drawdown, or concentration thresholds; reports generate on daily to monthly cadence in PDF or JSON. Operations teams use these to monitor client portfolios passively and flag risk escalations without manual daily review.
AI-assisted portfolio commentary
Claude-powered report generation that explains portfolio behavior, scenario results, and risk decomposition in natural language. Strategists use this to draft client-facing commentary and reduce the manual writing burden by 40-60% per report.
REST API and MCP endpoints
Expose all nine scenario engines and risk metrics programmatically for integration into custom dashboards or advisory workflows. Technical Operations or Founder-led teams use this to embed Sentralis' risk engines into proprietary client platforms without rebuilding the math.
Non-custodial, read-only imports
Connect to Binance, Kraken, Coinbase, Bybit, and Gate.io via API, or manually enter holdings; Sentralis never requests private keys or signing capability. Compliance and Operations teams use this to satisfy client data-security requirements while enabling full portfolio analysis.
What Makes Sentralis Different
Unique advantages vs similar tools in this niche
Forward-looking scenario engines rather than balance aggregation
vs Portfolio trackers and aggregators that only show consolidated balancesSentralis turns holdings into risk metrics, scenario results, liquidity views, and allocation comparisons that a tracker does not show.
Eight risk engines callable over REST and MCP
vs Closed analytics dashboards with no programmatic accessThe API exposes eight risk engines over plain HTTP with an OpenAPI 3.1 contract, and MCP connects Claude directly to run analyses.
Non-custodial, read-only safety model
vs Platforms that require signing or custody accessSentralis never holds assets, never asks for private keys, and never signs transactions or places orders.
Value Equation
Outcome-likelihood-time-effort assessment for Sentralis
Limited agency channel
Sentralis scored below the agency-resellability threshold (agency_fit_score < 50). The Value Equation projects agency-side outcomes, which don't apply to tools without a clear resell pathway.
Contact SentralisPricing
Sentralis platform cost to your agency
Starts at $20.83/mo (Pro (Annual)), scales to $49 one-time (Premium)
Free
- All nine scenario engines, including Monte Carlo, Correlation Regime and Macro Sensitivity
- 2 real portfolios (10 holdings each) + 2 hypothetical (5 positions each)
- Portfolio Teardown and Event Decomposition workbench modules
- 150 AI credits per month
Pro
- 5 real portfolios (15 holdings each) + 5 hypothetical (20 positions each)
- All six workbench modules: adds Time Machine, Delta Autopsy, Marginal Risk, Pre-Mortem
- Alerts evaluated every 2 days, 10 alerts and 5 scheduled reports
- 2,000 AI credits per month
Pro (Annual)
- 5 real portfolios (15 holdings each) + 5 hypothetical (20 positions each)
- All six workbench modules: adds Time Machine, Delta Autopsy, Marginal Risk, Pre-Mortem
- Alerts evaluated every 2 days, 10 alerts and 5 scheduled reports
- 2,000 AI credits per month
Premium
- Unlimited portfolios and holdings
- Daily alerts (20) and daily scheduled reports (10)
- All six workbench modules
- 10,000 AI credits per month
Premium (Annual)
- Unlimited portfolios and holdings
- Daily alerts (20) and daily scheduled reports (10)
- All six workbench modules
- 10,000 AI credits per month
Add-ons
Optional extras priced on top of any main plan
No verified white-label program for Sentralis: client-facing delivery runs under the platform's native branding.
Market Intelligence
Offer + scale economics for Sentralis
Limited agency channel
Sentralis scored below the agency-resellability threshold (agency_fit_score < 50). It's a useful tool but not designed for white-labeled or retainer-based reselling, so we don't publish productized offer economics for it.
Contact SentralisInvestment Decision Framework
Strategic vetting analysis for Sentralis
Situational Fit
Fit depends on your client mix
Buy If
4Your Account Executives spend 3+ hours per week manually building portfolio stress-test scenarios or risk summaries for crypto-holding clients, and Sentralis' nine pre-built scenario engines would replace that work.
Your Strategists need to decompose counterparty exposure and concentration across exchanges and chains for client advisory, and Sentralis' Event Decomposition and counterparty workbench modules compress that investigation from days to hours.
Your team manages multiple client portfolios and currently relies on spreadsheets or external tools to track VaR, drawdown, or concentration thresholds; Sentralis' scheduled alerts and daily reports would consolidate that monitoring into a single interface.
Your Founder or Operations lead wants to offer data-driven portfolio commentary to clients without hiring a dedicated crypto analyst; Sentralis' AI-assisted report generation (with 150 to 10,000 monthly credits depending on plan) reduces the manual writing burden.
Skip If
4Your agency does not serve crypto-holding clients or does not advise on digital-asset allocation; Sentralis has no application outside that domain.
Your team operates in a regulatory environment where client portfolio data cannot be imported into a third-party SaaS platform, even in read-only mode; Sentralis requires API or manual entry of holdings.
Your clients expect real-time portfolio rebalancing or execution capabilities; Sentralis is read-only and does not support trading or custody workflows.
Your team lacks familiarity with crypto risk metrics (VaR, Monte Carlo, correlation regime, liquidity scenarios) and cannot interpret Sentralis' outputs without significant training overhead.
Bottom Line
Sentralis is a non-custodial portfolio analytics platform that turns crypto holdings from wallets, exchanges, and manual entries into risk metrics, scenario simulations, and AI-assisted reports. For agencies serving crypto-holding clients or offering wealth-management advisory, it provides a professional analytics layer that Account Executives and Strategists can use to deepen client conversations around portfolio stress-testing, counterparty exposure, and allocation decisions. The platform exposes nine scenario engines (Monte Carlo, historical replay, liquidity, macro sensitivity, correlation regime) plus six workbench modules via a read-only interface, eliminating the need to build or license these analyses separately.
Reality Check
Sentralis is purpose-built for crypto portfolio analysis and offers no value to agencies that do not serve crypto-holding clients or advise on digital-asset allocation. Adoption requires team familiarity with crypto risk terminology and scenario interpretation; the tool does not simplify analysis for non-technical stakeholders.
Moderate effort: standard configuration with some customization needed
Academy for Sentralis
Work through it in order: the course for this service first, then the modules behind it.
Course for this service
Sentralis Agency Implementation, Crypto Risk Advisory at Scale
Learn to deliver crypto portfolio risk analysis as a retainer service by mastering Sentralis' nine scenario engines, workbench modules, and API integrations. This course shows agencies how to embed stress-testing, counterparty decomposition, and automated alerts into client advisory workflows, turning complex risk investigations into repeatable, billable engagements.
Open the courseNo Academy modules are published for this service yet. Browse the full Academy
Why this category matters
The commercial case before the tooling.
Core concepts
The mental model you need to price and scope the work.
- Reconciliation DebtConcept
Reconciliation debt is the accumulated gap between what a dashboard shows and what actually happened, and it accrues interest every reporting cycle. Every source an agency bolts into a client dashboard (ad platforms, GA4, CRM, billing) carries its own attribution logic, consent loss, and refresh lag, so each added integration widens the surface where two numbers can disagree in front of a client. The framework asks agencies to price that gap before scaling source coverage: a 20-source stack with three known discrepancies is more expensive than a 12-source stack with one documented caveat. Dana DiTomaso's argument that Universal Analytics masked attribution's structural limits while GA4 exposed them is the clearest recent illustration, because clients trained on the old numbers now read consent-driven underreporting as agency failure. Treat reconciliation as a line item in the retainer, not a cleanup task after the quarterly review goes sideways.
- Narrative Control LayerConcept
Narrative Control Layer is the part of a reporting stack that decides what a client concludes, not just what they see. Two agencies can pull identical numbers from the same ad account and land in opposite conversations: one defending spend, the other proposing expansion. The layer has three jobs. First, annotate: every dashboard needs a written reason attached to any movement over an agreed threshold, because unlabeled variance gets read as failure. Second, sequence: the order metrics appear in a report shapes which one the client remembers, so lead with the number the retainer is priced against. Third, bound the claim: label modeled or consent-affected figures as directional. Kick Point's Dana DiTomaso makes the case that Universal Analytics hid attribution's limits and GA4 exposed them, which means clients trained on the old dashboards now read normal data loss as agency underperformance. Tools like DashThis and Reportz ship annotation and template controls; the discipline of using them is the agency's job.
- Freshness Half-LifeConcept
Freshness Half-Life is the interval at which a dashboard's numbers stop matching what a client can see with their own eyes, and how fast trust erodes after that point. Every reporting stack has a half-life: a live ad spend figure might hold for an hour, a GA4 conversion count for a day, a reconciled CRM pipeline for a week. Agencies that publish without knowing each metric's half-life end up defending numbers instead of discussing performance. The framework asks three questions per data source: how often does it actually update, how often does the client check it independently, and who absorbs the gap when the two disagree. Dana DiTomaso's argument that GA4 simply made attribution's limits visible is the canonical case: clients trained on Universal Analytics read consent-driven gaps as underreporting, and the agency eats the credibility cost. Set refresh cadence to the client's checking rhythm, not the vendor's sync schedule.
Decision and risk
How to judge the fit, and the ways it goes wrong.
- Analytics & Reporting Tools Rule: Benchmark the Reporting Process Before Buying Dashboard CoverageEvaluation Rule
Time the current report build per client for one cycle, then buy only the platform that cuts that number and route the recovered hours into analysis and recommendations.
- When Dashboard Numbers Disagree With Client Reality, Reconcile Before You Add SourcesEvaluation Rule
Reconcile every dashboard metric against the client's own system of record before adding another integration, because source coverage without reconciliation just multiplies the numbers a client can challenge.
- Reporting Automation vs Analysis Capacity: Where the Agency Hours Actually GoDecision Framework
IF the agency's current reporting process burns more than a few hours per client per month on manual data pulls, screenshot assembly, and slide cleanup, THEN buy an aggregation platform and reinvest the recovered hours into analysis and proactive recommendations. IF reporting time is already under control and the real gap is interpretation, THEN skip new tooling and spend the budget on analyst time instead.
- The Dashboard Handoff Trap: Why Analytics & Reporting Tools Stall After the First Client ReviewFailure Pattern
- The Reconciliation Gap: Why Analytics & Reporting Tools Fail When Sources DisagreeFailure Pattern
Delivery system
Blueprints and procedures for running it as a service.
- Client Reporting Automation Retainer Build (7-12 days)Implementation Blueprint
A productized engagement that benchmarks an agency's existing client reporting cycle, wires the chosen analytics platform into the live data sources, and hands over a governed dashboard and narrative template the delivery team can run without analyst babysitting.
- Reporting Baseline Audit (Onboarding)Operating Procedure
- Source Coverage and Freshness Check (QA)Operating Procedure
- Dashboard Narrative Review (Delivery)Operating Procedure
13 modules selected for Sentralis
Frequently Asked Questions
Answers about pricing, setup, implementation
Sentralis turns crypto holdings from wallets, exchanges, and manual entries into risk metrics, scenario results, and AI-assisted reports. It runs nine scenario engines (Monte Carlo, historical replay, liquidity, macro sensitivity, correlation regime, counterparty analysis, and others) on client portfolios without requiring custody or signing access. The platform also exposes these engines over REST API and MCP endpoints so agencies can embed risk analysis into custom workflows or dashboards.
Pro plan is $29 USD per month and includes 5 real portfolios (15 holdings each), 5 hypothetical portfolios (20 positions each), all six workbench modules, 2,000 AI credits per month, and REST API and MCP access (25 MCP analyses per day). Premium plan is $49 USD per month and includes unlimited portfolios and holdings, daily alerts (20) and scheduled reports (10), all six workbench modules, 10,000 AI credits per month, and REST API and MCP access (100 MCP analyses per day). A free tier is available with 2 real portfolios (10 holdings each), 2 hypothetical portfolios (5 positions each), all nine scenario engines, 150 AI credits per month, and weekly alerts and scheduled reports.
Account Executives use Sentralis to run real-time portfolio stress tests and scenario analysis during client calls, replacing manual spreadsheet modeling. Strategists use the workbench modules (Portfolio Teardown, Event Decomposition, Pre-Mortem) to decompose counterparty exposure and concentration risk, compressing multi-day investigations into single sessions. Operations teams use scheduled alerts and reports to monitor client portfolios passively and flag risk escalations. Founders or advisory leads use AI-assisted report generation to draft client-facing commentary without hiring dedicated crypto analysts.
For an Account Executive running 3+ client portfolio stress tests per week, Sentralis saves 2-4 hours per week by eliminating manual scenario modeling and spreadsheet building. For a Strategist decomposing counterparty exposure or concentration risk across multiple client portfolios, the workbench modules save 4-6 hours per week compared to manual analysis. For Operations teams monitoring alerts and reports, passive monitoring saves 1-2 hours per week versus daily manual portfolio review. Aggregate savings per seat range from 3-8 hours per week depending on role and portfolio volume.
Sentralis connects to Binance, Kraken, Coinbase, Bybit, and Gate.io via read-only API import. It also accepts manual portfolio entries for holdings not on these exchanges or stored in self-custody wallets. All imports are non-custodial; Sentralis never requests private keys or signing capability.
Yes. Sentralis exposes all nine scenario engines and risk metrics over REST API and MCP endpoints. The Pro plan includes 25 MCP analyses per day; the Premium plan includes 100 per day. Agencies can embed these endpoints into custom dashboards, advisory platforms, or reporting workflows without rebuilding the underlying risk math.
Sentralis is read-only and non-custodial; it does not hold client assets or private keys. Upon cancellation, your team loses access to the platform and its analysis outputs, but client holdings remain in their original wallets and exchanges. You can export portfolio data and reports before cancellation if needed.
Initial setup takes 30-60 minutes per team member: connecting exchange APIs or manually entering holdings, and running one scenario to familiarize with the interface. Full productivity (using all workbench modules and interpreting scenario results) typically takes 1-2 weeks of hands-on use. Teams already familiar with crypto risk terminology (VaR, Monte Carlo, correlation regime) onboard faster.