InFinder structures market intelligence into an interconnected graph of content signals, investment theses, and ticker positions — with typed relationships, cascade detection, and full audit trails.
Investment theses moved in the last weeks by breaking or high-impact market signals — and the impulses that excited them.
View by impulse → tickerExpanded US Treasury long-term bond buyback programs undermine confidence in fiscal management and debt control, driving flows into scarce assets (Bitcoin, gold) …
Spot Bitcoin ETFs are recording their highest weekly inflow of 2025 at $1.61B through Thursday, signaling renewed institutional demand that provides structural …
Bitcoin extends its 3-month high rally if Fed Chair Warsh signals tolerance for above-target inflation or Treasury market intervention at Jackson Hole, …
XRP's RSI at 72 following a vertical advance creates elevated probability of near-term consolidation or pullback, with $1.50-$1.55 as immediate resistance before …
Systematic burning of transaction fees creates persistent deflationary pressure on XRP's fixed 100 billion supply, supporting scarcity-based value appreciation as network activity …
Venezuela's potential OPEC exit following the UAE's departure erodes the cartel's market influence and could weaken supply discipline, pressuring crude prices over …
PayPal buyout consortium walk collapses take-private thesis, removing M&A floor and forcing repricing on fintech multiple compression and competitive pressure narrative.
Japan PM Takaichi's plan to cap new JGB issuance at ¥40T/year signals fiscal consolidation commitment, supporting JGB prices and yen while reducing …
France Q2 growth revised to stagnation with above-target CPI, Spain inflation doubling ECB target, and activity weakness across retail sales confirms stagflationary …
Google, Microsoft and Amazon's echoed concerns about returns on mounting AI investment create a valuation ceiling for Nvidia even with strong near-term …
Nvidia's $7.8B investment gains and explicit defense of 'circular financing' (investing in customers who buy its chips) raises regulatory and accounting risk, …
Fed Chairman Warsh's Jackson Hole speech on Friday could provide clarity on the Fed's reaction function to inflation and rising yields; clear …
The ETH/BTC ratio breaking above its 200-day SMA suggests capital rotation from Bitcoin into Ethereum and broader altcoins, potentially sparking an altcoin …
Spot Ethereum ETFs attracted $179.80 million in daily inflows with BlackRock's ETHA capturing bulk of volume, demonstrating sustained institutional demand for ETH …
The discovery of an explosive drone at a key NATO logistics hub underscores the escalating hybrid warfare threat in Europe, reinforcing demand …
Severe manpower attrition and collapsing voluntary recruitment force Russia toward politically risky mass conscription, tightening labor markets and accelerating capital flight and …
Rising risk of Gaza conflict resumption and broader Middle East instability supports the outlook for US defense contractors as potential ceasefire breakdown …
Tokyo headline CPI at 1.9% and services inflation at nearly one-year high confirm Japan has sustainably reached the BoJ's 2% inflation target, …
The Japanese Yen remains structurally weak against the US Dollar due to persistent rate differentials and a historically dovish BoJ. Accelerating Japanese …
Escalating US-Iran tensions and Strait of Hormuz closure risk drive oil prices higher, supporting commodity-linked CAD against EUR amid diverging regional growth …
Germany's likely 2026 climate target miss and political backsliding under Chancellor Merz weakens the investment case for European green energy transition leaders, …
The current macro backdrop (higher rates, no Fed QE, no fiscal stimulus) differs fundamentally from 2020-2021, making historical pattern analogies unreliable and …
A fortuitous timing of an oil cargo sale at high prices yielded a $112M post-tax cash injection for PetroNor, strengthening its balance …
Crinetics acquisition will successfully offset Vertex's cystic fibrosis patent cliff losses (2026-2028) through successful clinical development, FDA approvals, and revenue generation from …
As digital wallet commoditization squeezes standalone players like PayPal, the真正的 winner emerges at the infrastructure layer - Stripe, Adyen, and network rails …
MRVL faces short-term margin pressure from unfavorable product mix shifts and ramp-up costs, potentially weighing on near-term profitability despite long-term growth prospects. …
Marvell Technology beat Q2 expectations on both the top and bottom lines, reflecting solid demand for its semiconductors. MRVL is positioned as …
Federal court ruling that Pentagon's supply chain risk designation of Anthropic was unlawful removes regulatory overhang on the AI safety leader, validating …
PayPal's slower TPV growth compared to Stripe's ~34% YoY pace makes it a less attractive standalone investment, pressuring its independent valuation and …
PayPal's rejection of the Stripe/Advent bid prevents the formation of a $3.7T online payments behemoth, relieving competitive pressure on rival payment processors. …
Every market pattern, investment thesis, and ticker position lives in a typed knowledge graph. This isn't a dashboard — it's a reasoning engine that exposes hidden dependencies across your entire investment universe.
Not just a visualisation — a computational structure that enables capabilities impossible with spreadsheets or flat databases.
A knowledge graph isn't just a visualisation — it's a computational structure that enables capabilities impossible with spreadsheets or flat databases.
When "Fed Pivots Dovish" strengthens, the graph traces impact across every linked impulse, scenario, and position — instantly surfacing which theses need revisiting.
The graph explicitly flags when scenarios contradict each other. If "Consumer Spending Weakening" and "Retail Revenue Growing" both exist, InFinder forces intellectual honesty.
If 80% of your positions depend on one scenario and it weakens, the graph makes hidden danger visible — showing exactly how many theses collapse at once.
Signal strength decays through the graph with ML-learned rates. Recent evidence weighs more — the system optimises decay from actual market outcomes.
From raw content to optimised strategy — six building blocks, each feeding the next.
InFinder continuously monitors YouTube channels, Reddit threads, RSS feeds, and news wires. Each new piece of content becomes an impulse — a timestamped, scored record of raw market intelligence. No more scattered notes or lost insights.
Every impulse is automatically parsed, relevance-scored, and queued for AI extraction. The system handles transcript extraction, engagement scoring, and deduplication.
53 active sources 238592 impulses ingestedAI evaluates each impulse and links it directly to the scenarios (investment theses) it supports or challenges. Every link carries a relevance score and a 1536-dimensional vector embedding for semantic matching.
Impulses automatically discover the right theses via cosine similarity. Each edge is typed — an impulse may support or challenge a scenario — building the knowledge graph without manual tagging.
238592 impulses ingested 1129867 impulse→scenario edgesLinked impulses excite scenarios — structured investment theses with long/short ticker positions. Each scenario has a compound state from −1 (fully bearish) to +1 (fully bullish) that shifts in real time as evidence accumulates.
As new impulses arrive and attach to their theses, the scenario state automatically recalculates via graph propagation. Every position traces back to specific content — full audit trail.
41125 active scenarios 222995 long 67240 shortEvery ticker aggregates its complete intelligence picture — all connected scenarios, contributing impulses, and actual price performance. Entry prices are tracked for P&L attribution.
Real-time and end-of-day prices flow in from EODHD, along with fundamentals and news catalysts. The FINAN agent generates deep analysis covering technicals, fundamentals, and sentiment — typically in under 60 seconds.
86147 tracked tickers 322399 ticker-scenario linksDefine portfolio rules in natural language. Set signal thresholds, rebalance schedules, position limits, and sector constraints. The LLM reads the strategy prompt and the current scenario signals at every rebalance point to decide: buy, sell, or hold.
Different prompt → different trades → measurable P&L delta. This is what makes the prompt itself an optimisable parameter.
Run historical backtests against real price data. The engine detects forks — decision points where the strategy made a suboptimal choice — then analyzes root cause, branches the prompt, and re-tests the new version from the fork point forward.
If the evolved prompt outperforms, it gets promoted. The cycle repeats: backtest → detect forks → evolve prompt → branch-backtest → promote. Like gradient descent on the strategy itself.
Anti-overfitting: modifications must be timeless general principles. The LLM self-checks for temporal specificity. Full version tree with unified diffs.
Sharpe 1.90 → 3.39 Alpha −0.9% → +5.7%InFinder structures the full pipeline — every step automated, every decision auditable, every link traceable back to source content.
InFinder doesn't deal in vague sentiment. It structures market knowledge into impulses and scenarios — each scored, linked, and auditable.
An impulse is a structured, directional signal extracted from a single piece of content — not a keyword or sentiment, but a scored, timestamped observation about a market force.
Each carries a relevance score and a vector embedding. The system links it directly to the scenarios it bears on — an impulse may support or challenge a thesis, building the graph automatically.
A scenario is an investment thesis built from multiple supporting impulses — a structured argument for why specific assets should be long or short.
Scenarios are AI-generated or manually curated, tracked with entry prices, and scored against actual outcomes. Every scenario links back to its source impulses — creating a full audit trail from content to trade.
Three specialised agents operate directly on the investment graph — augmenting human judgment, never replacing it.
Runs a 10-node agentic analysis workflow per ticker: technical analysis, fundamental screening, news assessment, graph context, and overall synthesis.
Autonomously manages portfolio construction: proposes position changes, links impulses to scenarios, and deprecates stale theses — with human-in-the-loop approval.
Detects unexplained ticker movements and autonomously searches for information that could explain them — surfacing new impulses the graph doesn't yet contain.
Scenarios hold the investment thesis. Strategies turn theses into executable portfolio rules. The backtesting engine iterates on strategy versions to find the best one — automatically.
Each scenario aggregates excitation from its linked impulses into a compound state ranging −1 to +1. As new impulses arrive and attach to the thesis, the scenario state shifts in real time — giving you a continuous, auditable signal.
Define portfolio rules using natural language prompts. Set signal thresholds, rebalance schedules, position constraints, and risk limits. The strategy consults the graph state and the LLM at every decision point.
Run historical backtests against real price data. The engine detects forks — moments where the strategy made a suboptimal decision — then branches the prompt, re-tests, and promotes the best-performing version.
Free drives adoption. Select unlocks strategy creation. Omni delivers full backtesting evolution.
A complete AI pipeline from raw information to investment action — every step automated, every decision auditable.
Continuously monitor YouTube channels, Reddit, RSS feeds, and manual inputs. Automated polling, transcript extraction, and engagement scoring.
AI turns each content item into a scored, directional impulse. Relevance scoring, vector embeddings, and automatic linking straight to the scenarios it bears on.
Typed relationships (reinforcing, contradicting, validating, invalidating) across all entities. Multi-hop reasoning and cascade detection.
AI-generated or manual investment theses. Clusters related impulses, suggests L/S positions with rationale, and tracks confidence over time.
Every scenario links to source impulses, every impulse to source content. Compliance-grade traceability.
Learns optimal score decay rates from market outcomes. Predicts scenario performance. Source importance scoring based on impulse outcome quality.
From hedge funds and RIAs to independent research analysts — InFinder augments the investment process at every level.
Reduce 200+ daily sources to scored directional patterns. See concentration risk, cascade exposure, and thesis contradictions at a glance. Full compliance audit trail.
Structure your research into linked impulses and scenarios. Surface counter-evidence to your thesis automatically. Track which signals persist vs decay over time.
Every investment decision traces back through scenarios → impulses → source content. Graph-based concentration analysis. Revertible agent actions with full state logging.
Search across 365864 nodes and 1452266 edges — or begin adding your own content sources.