Financial research and market data, structured
ClickSet aggregates stock prices, crypto indicators, SEC filings, real estate listings, commercial property data, and startup funding rounds into structured, refreshing tables. You can run AI anomaly detection and trend analysis across the combined dataset, then pipe results into models and dashboards through the API.
Financial research relies on signals that live in disconnected places — filings, market data, property listings, and funding rounds all update on different schedules in different formats. ClickSet consolidates the collection layer so analysts spend their time on the model, not the data pipeline.
Why financial data pipelines become the bottleneck
The signals that drive investment decisions are scattered across EDGAR, market data feeds, property databases, and venture trackers — each with its own format and update cadence. Stitching them into one analyzable table is more engineering work than analysis.
Stale data corrupts models quietly. When a filing feed lags or a price table stops refreshing, forecasts run on numbers that no longer reflect reality, and the failure is invisible until the prediction is wrong.
How ClickSet does it
- 1
Choose your signals
Select from stock prices, crypto indicators, SEC filings, real estate, commercial property, and startup funding. ClickSet structures them into a unified table.
- 2
Consolidate and deduplicate
Multi-source fusion brings disparate feeds into one clean schema with deduplication so you analyze a single, coherent dataset.
- 3
Detect anomalies and trends
Run AI anomaly detection and trend analysis across the fused dataset to surface the movements worth investigating.
- 4
Keep it current
Schedule refreshes so models and dashboards always run on the latest data, with full history retained for backtesting.
Powering Financial Research & Market Data
Multi-source fusion
Combine market data, filings, property, and funding into one structured table with deduplication.
Scheduled refreshes
Keep datasets current on a cadence so forecasts never run on stale inputs.
AI operations
Apply anomaly detection, trend analysis, and classification across the full dataset.
API access
Feed live datasets into your models and dashboards through one endpoint.
What you get
- One analyzable table instead of disconnected financial feeds.
- Anomaly and trend detection across every signal.
- Scheduled refreshes so models run on current data.
- Full history retained for backtesting and risk work.
From raw signals to a working model
Analysts rarely want raw feeds; they want features. Once sources are fused into one table, teams layer AI operations on top to derive the signals their models actually consume — sentiment scores, filing frequency, hiring momentum, or price momentum. The collection layer and the feature layer live in the same place, which removes a whole class of handoff errors.
Retained history makes the difference between a dashboard and a research tool. Because every refresh is stored, analysts can backtest a hypothesis against months of data, validate that a signal would have predicted past moves, and only then promote it into a live forecast or risk model.
Who uses this?
Frequently asked questions
What financial data sources can I combine? +
Stock prices and indicators, crypto prices and indicators, SEC filings, real estate listings, commercial property listings, and startup funding rounds can all be fused into one structured table.
Can I detect anomalies automatically? +
Yes. You can run AI anomaly detection and trend analysis across your datasets, so unusual movements surface without manual review of every row.
How do I keep the data current? +
Schedule refreshes at the cadence your models need. ClickSet re-gathers the sources and retains history so you can both forecast and backtest.
What does it cost? +
ClickSet starts on a free plan and uses a usage-based model with a prepaid balance and per-key spend caps. See the pricing page for current details.
Further reading
See how ClickSet handles your data workload
Describe the dataset you need, enrich it with hundreds of LLMs, and query the result through one API. Start on the free plan.