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 → tickerThe Nasdaq 100 is coiling in a tight symmetrical triangle pattern, making it primed for a sharp directional breakout driven by the …
Rising oil prices from the Strait of Hormuz closure reignite inflation fears, pushing markets to reprice the likelihood of a December Fed …
Crude tanker companies with high exposure to Middle East routes will face operational paralysis as insurers stop writing cover and traffic drops …
Oil and gas producers outside the Middle East will capture outsized margins as global crude prices surge while they avoid the direct …
Surging energy and feedstock costs from the Hormuz toll will severely compress margins for energy-intensive sectors like fertilizer, chemicals, and plastics, which …
The new energy toll acts as a broad tax on global energy, driving up costs for diesel, fertilizer, plastics, and electricity, which …
Higher factory utilization, AirTech restructuring, and increased production capacity will drive capital-efficient earnings growth and margin expansion without proportionate CapEx increases.
The Data Center Technologies (DCT) segment is poised to become the largest segment, reflecting strong underlying demand for data center cooling that …
A potential divestment of the FoodTech segment could unlock $180-370M for M&A and sharpen strategic focus on higher-growth areas, driving a re-rating.
The Molex business acquisition is successfully augmenting HMS Networks' top-line growth, contributing to an 18% total net sales increase and a 20% …
HMS Networks is experiencing strong underlying demand, evidenced by 15% organic order intake growth and 12% organic net sales growth, with Q2 …
HMS Networks achieved significant operational leverage in Q2 2026, with EBITDA growing 59% YoY to SEK 266 million and margins exceeding company …
US Treasury yields, particularly the 2-year note, will remain elevated as money markets price in a higher-for-longer interest rate scenario with tightening …
Renewed U.S.-Iran tensions are driving oil prices higher, creating a macro tailwind for energy commodities and headwinds for broad equities. Renewed geopolitical …
De-anchored inflation expectations ahead of the June CPI release and Fed Chair testimony are likely to keep US rate expectations elevated, supporting …
Surging oil prices driven by geopolitical tensions are crushing Japan's terms of trade, pushing USD/JPY toward fresh multi-decade highs as the Yen …
The substantial 275 bps interest rate gap between the Bank of England (3.75%) and the Bank of Japan (1%), combined with fading …
Upcoming US core CPI data takes on heightened importance as an upside surprise will explicitly trigger further Fed rate hike pricing, given …
Canada's wider-than-expected trade surplus and higher oil prices provide fundamental support to the Canadian Dollar, limiting its downside against the USD despite …
EUR/CHF is challenging ascending triangle resistance above its 200-DMA, indicating potential for further Euro appreciation and Swiss Franc weakness toward the 0.9320-0.9400 …
The USD/CHF pair is extending its rally towards 0.8125, driven by broad US Dollar strength and risk-off flows, despite overbought technical indicators …
Surging oil prices driven by geopolitical conflict reignite inflation fears, forcing central banks to abandon monetary accommodation and driving weak results in …
High-stakes quarterly reports from major Wall Street lenders will act as a defining catalyst for the financial sector's near-term direction.
Surging expectations for a September Fed rate hike, driven by sticky core inflation and energy price fears, will provide a floor for …
The convergence of Middle East conflicts disrupting oil shipments, regional instability affecting production, and geopolitical tensions creating risk premiums positions oil to …
US military strikes on Iranian targets elevate geopolitical risk and threaten Middle Eastern oil supply, driving crude oil prices higher. Escalating military …
Massive AI investments driving semiconductor stocks higher may be approaching a bubble peak, creating downside risk akin to the 2000-2002 dot-com bust …
The fragile US-Iran ceasefire and renewed military strikes in July are causing crude oil prices to edge higher again, threatening the sustainability …
Strong demand for AI infrastructure will sustain upward pressure on prices for technology products and electricity, benefiting providers in these supply chains. …
Estimates of cooling US CPI to 3.8% YoY support the thesis that easing inflation will drive dovish Fed expectations, lifting non-yielding Silver. …
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 192715 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.
192715 impulses ingested 947177 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.
39375 active scenarios 83046 long 20908 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.
82917 tracked tickers 114775 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 315007 nodes and 1061952 edges — or begin adding your own content sources.