{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_wallet-ai","slug":"wallet-ai","name":"Wallet.AI","type":"product","url":"https://wallet.ai","page_url":"https://unfragile.ai/wallet-ai","categories":["data-analysis"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_wallet-ai__cap_0","uri":"capability://data.processing.analysis.multi.source.financial.data.aggregation.and.normalization","name":"multi-source financial data aggregation and normalization","description":"Wallet.AI ingests financial data from multiple sources (bank accounts, credit cards, investment accounts, transaction histories) through secure API integrations or direct uploads, normalizing heterogeneous data formats into a unified schema for downstream analysis. The system likely uses standardized financial data connectors (Plaid, Yodlee, or proprietary integrations) to handle authentication, data fetching, and transformation into common transaction and account models, enabling cross-institution analysis without manual data entry.","intents":["I want to connect all my financial accounts in one place without manually entering transactions","I need my spending data from multiple banks analyzed together to see my complete financial picture","I want to automatically sync my latest transactions and account balances without manual updates"],"best_for":["individuals with multiple bank accounts and credit cards seeking unified financial visibility","users who want automated data collection without manual CSV uploads or spreadsheet maintenance"],"limitations":["API coverage limited to supported institutions — regional banks or international accounts may not be connectable","Data sync latency typically 24-48 hours depending on bank API refresh rates","Requires secure credential storage and OAuth/API key management, introducing potential security surface"],"requires":["Active bank accounts or credit cards with API access (Plaid, Yodlee, or direct bank APIs)","Internet connection for real-time or scheduled data syncs","User authentication credentials or OAuth tokens for connected institutions"],"input_types":["bank account credentials (OAuth or API keys)","CSV/OFX file uploads","transaction history exports"],"output_types":["normalized transaction records (date, amount, category, merchant, account)","aggregated account balances and holdings","unified transaction ledger across all connected sources"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_1","uri":"capability://data.processing.analysis.spending.pattern.recognition.and.behavioral.clustering","name":"spending pattern recognition and behavioral clustering","description":"Wallet.AI applies machine learning clustering and classification algorithms to transaction data to identify recurring spending patterns, categorize transactions beyond standard merchant categories, and segment spending into behavioral clusters (e.g., discretionary vs. essential, impulse vs. planned). The system likely uses unsupervised learning (k-means, DBSCAN) on transaction embeddings or supervised classification on merchant/amount/frequency features to detect patterns humans miss, enabling personalized insights into spending habits.","intents":["I want to understand where my money actually goes beyond standard budget categories","I need to identify hidden spending patterns or recurring subscriptions I've forgotten about","I want to see which spending categories are growing or shrinking over time"],"best_for":["individuals seeking behavioral insights into their spending without manual categorization","users wanting to identify subscription leakage or discretionary spending they can optimize"],"limitations":["Accuracy depends on transaction data quality and merchant naming consistency — ambiguous merchant names reduce pattern detection","Requires 3-6 months of transaction history for meaningful pattern detection; new users see limited insights","Behavioral clustering may misclassify edge-case transactions or one-time purchases as recurring patterns"],"requires":["Minimum 30-90 days of transaction history for initial pattern detection","Consistent merchant naming and transaction categorization from source institutions","Sufficient transaction volume (typically 50+ transactions/month) for statistical significance"],"input_types":["normalized transaction records (merchant, amount, date, category)","account type metadata (checking, savings, credit card)"],"output_types":["spending category breakdowns (percentage of income by category)","recurring transaction identification (subscriptions, regular bills)","behavioral clusters (essential vs. discretionary, impulse vs. planned)","trend analysis (month-over-month or year-over-year spending changes)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_2","uri":"capability://planning.reasoning.personalized.spending.recommendations.with.contextual.reasoning","name":"personalized spending recommendations with contextual reasoning","description":"Wallet.AI generates actionable spending recommendations by analyzing detected patterns, comparing user behavior to anonymized cohort benchmarks, and applying financial heuristics (e.g., 50/30/20 rule, emergency fund targets). The system likely uses a recommendation engine that scores potential optimizations (e.g., 'reduce dining out by $X to reach savings goal') by impact, feasibility, and alignment with user-stated financial goals, then ranks and surfaces top recommendations via the UI.","intents":["I want specific, actionable suggestions for where to cut spending to reach my savings goals","I want to see how my spending compares to people like me and where I'm overspending","I want recommendations tailored to my financial situation, not generic advice"],"best_for":["individuals seeking personalized financial guidance without paying for a human advisor","users wanting data-driven optimization suggestions based on their actual spending patterns"],"limitations":["Recommendations are only as good as underlying pattern detection — garbage in, garbage out if categorization is poor","Cohort benchmarking requires sufficient anonymized user data; early-stage platforms may lack representative benchmarks","Recommendations don't account for life context (job loss, medical emergency, relocation) — purely data-driven without human judgment","No feedback loop mentioned — unclear if recommendations improve based on user acceptance/rejection"],"requires":["User-defined financial goals (savings target, debt payoff, investment amount)","Sufficient spending history and pattern data (90+ days recommended)","Anonymized cohort data for benchmarking (requires critical mass of users)"],"input_types":["spending patterns and behavioral clusters","user financial goals and constraints","account balances and income data"],"output_types":["ranked list of spending optimization recommendations","estimated impact of each recommendation (e.g., 'save $X/month')","cohort comparison metrics (e.g., 'you spend 40% more on dining than similar users')","priority-ordered action items"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_3","uri":"capability://planning.reasoning.financial.goal.tracking.and.progress.visualization","name":"financial goal tracking and progress visualization","description":"Wallet.AI enables users to define financial goals (savings targets, debt payoff, investment milestones) and tracks progress against these goals by monitoring relevant account balances, transaction flows, and spending categories over time. The system likely calculates goal completion percentage, projects time-to-completion based on current savings rate, and visualizes progress through charts and alerts, updating metrics as new transaction data arrives.","intents":["I want to set a savings goal and see my progress toward it in real-time","I want to know if I'm on track to pay off my credit card debt by a target date","I want to see how my spending changes are affecting my ability to reach my financial goals"],"best_for":["goal-oriented individuals who benefit from visual progress tracking and accountability","users managing multiple financial objectives (emergency fund, vacation savings, debt payoff)"],"limitations":["Goal tracking is passive — no enforcement or behavioral nudges if user goes off track","Projections assume linear savings rate; don't account for seasonal variation or income changes","No integration with external goal-setting frameworks (SMART goals, behavioral economics techniques)"],"requires":["User-defined goals with target amounts and dates","Ongoing transaction data to calculate progress","Account balance data for net worth tracking"],"input_types":["goal definition (target amount, deadline, category)","transaction and account balance data","user-specified goal priority or weighting"],"output_types":["goal progress percentage and visual indicators","projected completion date based on current savings rate","alerts when off-track or when milestones are reached","historical progress charts and trend lines"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_4","uri":"capability://data.processing.analysis.subscription.and.recurring.transaction.detection","name":"subscription and recurring transaction detection","description":"Wallet.AI automatically identifies recurring transactions (subscriptions, memberships, regular bills) by analyzing transaction frequency, amount consistency, and merchant patterns over time. The system likely uses time-series analysis or pattern matching to detect transactions that repeat at regular intervals (weekly, monthly, annual) and flags them for user review, enabling identification of forgotten or unwanted subscriptions.","intents":["I want to find all my subscriptions and recurring charges in one place","I want to identify subscriptions I've forgotten about and no longer use","I want to see how much I'm spending on subscriptions annually"],"best_for":["users with multiple subscriptions seeking visibility into recurring spending","individuals wanting to audit and reduce subscription bloat"],"limitations":["Detection accuracy depends on transaction consistency — variable-amount subscriptions (usage-based) may be missed","Requires multiple months of history to establish recurrence patterns; new users see limited detection","Merchant name variations (e.g., 'NETFLIX.COM' vs 'NETFLIX INC') can cause duplicate or missed detections"],"requires":["Minimum 3-6 months of transaction history for reliable pattern detection","Consistent merchant naming and transaction amounts for recurring charges"],"input_types":["normalized transaction records (merchant, amount, date, frequency)"],"output_types":["list of detected recurring transactions with frequency and amount","annual cost estimates for subscriptions","confidence scores for recurrence detection","alerts for new recurring transactions detected"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_5","uri":"capability://data.processing.analysis.savings.rate.and.financial.health.scoring","name":"savings rate and financial health scoring","description":"Wallet.AI calculates aggregate financial health metrics (savings rate, debt-to-income ratio, emergency fund adequacy, net worth trajectory) and generates a composite health score that summarizes overall financial well-being. The system likely normalizes multiple metrics into a 0-100 scale, benchmarks against cohort averages, and identifies the top factors limiting the user's score, enabling users to understand their financial position at a glance.","intents":["I want a simple score that tells me how healthy my finances are","I want to understand which factors are most limiting my financial health","I want to see how my financial health compares to people in my demographic"],"best_for":["users seeking a simple, holistic view of financial well-being without deep analysis","individuals wanting benchmarking against peers to contextualize their financial position"],"limitations":["Composite scoring is inherently reductive — single score obscures nuanced financial situations","Benchmarking requires representative cohort data; early-stage platforms may lack sufficient users for accurate comparisons","Score doesn't account for life stage, risk tolerance, or personal financial priorities — one-size-fits-all metric","No guidance on how to improve score beyond identifying limiting factors"],"requires":["Complete financial data (income, expenses, assets, liabilities, savings)","Sufficient transaction history (90+ days) for rate calculations","Anonymized cohort data for benchmarking"],"input_types":["income and expense data","account balances and net worth","debt amounts and interest rates","savings and investment data"],"output_types":["composite financial health score (0-100)","component scores (savings rate, debt ratio, emergency fund, net worth growth)","cohort percentile ranking","top 3-5 factors limiting the score","historical score trends"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_6","uri":"capability://data.processing.analysis.income.and.expense.forecasting.with.seasonal.adjustment","name":"income and expense forecasting with seasonal adjustment","description":"Wallet.AI projects future income and expenses by analyzing historical transaction patterns, applying time-series forecasting models (ARIMA, exponential smoothing, or ML-based approaches), and adjusting for seasonality and trends. The system likely decomposes spending into trend, seasonal, and irregular components, enabling more accurate projections than simple averages, and surfaces confidence intervals to indicate forecast uncertainty.","intents":["I want to forecast my cash flow for the next 3-6 months to plan for large expenses","I want to account for seasonal spending variations (holiday shopping, summer travel) in my budget","I want to see if my income is growing or declining over time"],"best_for":["individuals with variable income or seasonal spending patterns seeking better cash flow visibility","users planning for future expenses and wanting data-driven projections"],"limitations":["Forecasts are only as good as historical data — major life changes (job loss, relocation) invalidate projections","Seasonal adjustment requires 12+ months of data; newer users see less accurate forecasts","Doesn't account for planned future changes (known raises, planned large purchases, life events)","Confidence intervals widen significantly beyond 3-6 months, reducing forecast utility"],"requires":["Minimum 12 months of transaction history for reliable seasonal decomposition","Consistent income and expense patterns (high variability reduces forecast accuracy)","Regular transaction data (gaps or irregular patterns degrade forecasts)"],"input_types":["historical income and expense transactions (12+ months)","account balance data","user-specified known future changes (optional)"],"output_types":["projected income and expense for next 1-12 months","confidence intervals for projections","seasonal adjustment factors","trend analysis (growing/declining income or spending)","cash flow charts with historical and projected data"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_7","uri":"capability://data.processing.analysis.investment.performance.tracking.and.asset.allocation.analysis","name":"investment performance tracking and asset allocation analysis","description":"Wallet.AI aggregates investment account data (stocks, bonds, mutual funds, ETFs, crypto) and calculates performance metrics (total return, annualized return, cost basis, unrealized gains/losses) while analyzing asset allocation against user-defined targets or standard models (e.g., 60/40 stocks/bonds). The system likely tracks individual holdings, calculates portfolio-level metrics, and alerts when allocation drifts beyond tolerance thresholds.","intents":["I want to see all my investments in one place and track their performance","I want to know if my portfolio is properly diversified and aligned with my risk tolerance","I want to see how much I'm paying in fees across all my investment accounts"],"best_for":["investors with multiple brokerage accounts seeking unified portfolio visibility","individuals wanting to monitor asset allocation without manual spreadsheet tracking"],"limitations":["Investment data aggregation depends on broker API support — some brokers or account types may not be connectable","Performance calculations require accurate cost basis data; missing or incorrect cost basis reduces accuracy","Asset allocation analysis is static — doesn't provide rebalancing recommendations or tax-loss harvesting opportunities","Crypto holdings may have limited support depending on exchange integrations"],"requires":["Connected investment accounts (brokerage, retirement accounts, crypto exchanges)","Accurate cost basis and transaction history for performance calculations","User-defined asset allocation targets (or use of standard models)"],"input_types":["investment account data (holdings, quantities, prices)","transaction history (buys, sells, dividends, fees)","cost basis data","user-defined allocation targets"],"output_types":["portfolio summary (total value, asset allocation, diversification metrics)","individual holding performance (return %, gain/loss, cost basis)","portfolio-level metrics (total return, annualized return, volatility)","allocation drift alerts","fee analysis across accounts"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_8","uri":"capability://planning.reasoning.debt.payoff.planning.with.interest.optimization","name":"debt payoff planning with interest optimization","description":"Wallet.AI identifies all user debts (credit cards, loans, mortgages) from connected accounts and generates payoff strategies using algorithms like debt snowball (smallest balance first) or avalanche (highest interest first). The system calculates payoff timelines, total interest paid, and monthly payment requirements for each strategy, enabling users to compare approaches and understand the financial impact of different payoff sequences.","intents":["I want a plan to pay off my credit card debt as quickly as possible","I want to see how much interest I'll pay under different payoff strategies","I want to understand the trade-offs between paying off high-interest debt vs. building savings"],"best_for":["individuals with multiple debts seeking structured payoff strategies","users wanting to optimize debt payoff without financial advisor consultation"],"limitations":["Payoff plans assume consistent monthly payments and don't account for variable interest rates or promotional periods","Doesn't optimize for credit score impact or balance transfer opportunities","No integration with actual payment processing — recommendations aren't actionable without manual setup","Assumes user can sustain recommended payment amounts; doesn't adapt if income changes"],"requires":["Connected debt accounts (credit cards, loans) with balance and interest rate data","User-specified monthly payment budget or target payoff date","Accurate interest rate and minimum payment information"],"input_types":["debt account data (balance, interest rate, minimum payment, type)","user-specified payment budget or payoff timeline","income data (for feasibility analysis)"],"output_types":["payoff strategy recommendations (snowball vs. avalanche)","payoff timeline and completion date for each strategy","total interest paid under each strategy","monthly payment schedule","interest savings comparison"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wallet-ai__cap_9","uri":"capability://data.processing.analysis.privacy.preserving.cohort.benchmarking.with.differential.privacy","name":"privacy-preserving cohort benchmarking with differential privacy","description":"Wallet.AI enables spending and financial metric comparisons against anonymized user cohorts (segmented by income, age, location, family size) while protecting individual privacy through aggregation and differential privacy techniques. The system likely computes cohort statistics (median spending by category, average savings rate, typical debt levels) from anonymized user data and surfaces these benchmarks without exposing individual user information, enabling users to contextualize their financial position.","intents":["I want to see how my spending compares to people like me without revealing my personal data","I want to understand if my financial metrics are typical for my income and demographics","I want to see spending benchmarks by category for my peer group"],"best_for":["users seeking peer comparison without privacy concerns","individuals wanting to contextualize their financial position against representative cohorts"],"limitations":["Benchmarking accuracy depends on sufficient cohort size — small cohorts (e.g., high-income earners in rural areas) may lack representative data","Cohort segmentation is coarse-grained (income brackets, age ranges) — doesn't account for nuanced life circumstances","Differential privacy adds noise to statistics, reducing precision of benchmarks","Early-stage platform may lack sufficient user data for meaningful cohort statistics"],"requires":["Sufficient anonymized user data to compute representative cohort statistics (typically 100+ users per cohort)","User demographic data (income, age, location, family size) for cohort segmentation","Aggregation infrastructure to compute and serve cohort statistics without exposing individual data"],"input_types":["anonymized spending and financial metric data from user cohorts","user demographic data for cohort assignment","user financial data for comparison"],"output_types":["cohort spending benchmarks by category (median, percentile ranges)","cohort financial metrics (average savings rate, debt-to-income, net worth)","user percentile ranking within cohort","demographic-specific insights (e.g., 'people your age spend X% more on dining')"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":38,"verified":false,"data_access_risk":"high","permissions":["Active bank accounts or credit cards with API access (Plaid, Yodlee, or direct bank APIs)","Internet connection for real-time or scheduled data syncs","User authentication credentials or OAuth tokens for connected institutions","Minimum 30-90 days of transaction history for initial pattern detection","Consistent merchant naming and transaction categorization from source institutions","Sufficient transaction volume (typically 50+ transactions/month) for statistical significance","User-defined financial goals (savings target, debt payoff, investment amount)","Sufficient spending history and pattern data (90+ days recommended)","Anonymized cohort data for benchmarking (requires critical mass of users)","User-defined goals with target amounts and dates"],"failure_modes":["API coverage limited to supported institutions — regional banks or international accounts may not be connectable","Data sync latency typically 24-48 hours depending on bank API refresh rates","Requires secure credential storage and OAuth/API key management, introducing potential security surface","Accuracy depends on transaction data quality and merchant naming consistency — ambiguous merchant names reduce pattern detection","Requires 3-6 months of transaction history for meaningful pattern detection; new users see limited insights","Behavioral clustering may misclassify edge-case transactions or one-time purchases as recurring patterns","Recommendations are only as good as underlying pattern detection — garbage in, garbage out if categorization is poor","Cohort benchmarking requires sufficient anonymized user data; early-stage platforms may lack representative benchmarks","Recommendations don't account for life context (job loss, medical emergency, relocation) — purely data-driven without human judgment","No feedback loop mentioned — unclear if recommendations improve based on user acceptance/rejection","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.2833333333333333,"quality":0.6799999999999999,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.117Z","last_scraped_at":"2026-04-05T13:23:42.562Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=wallet-ai","compare_url":"https://unfragile.ai/compare?artifact=wallet-ai"}},"signature":"BpvmURHVVSP6CLl/3+Ks2/uq5SFqPVXthy6/UFdblfRTEYhF/vrSIF3Vr5o7deiGjuYJaIQHvwKzEjXaVpNADw==","signedAt":"2026-06-21T10:42:48.900Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/wallet-ai","artifact":"https://unfragile.ai/wallet-ai","verify":"https://unfragile.ai/api/v1/verify?slug=wallet-ai","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}