inFilings
Public Records & Filings alternative data provider · 1 listed dataset
Datasets from inFilings (1)
inFilings is an investment-research platform that turns U.S. Securities and Exchange Commission (SEC) filings into clean, structured data for institutional investors. The product is now delivered as VerityData | inFilings, part of the Verity suite of research solutions; the infilings.com website redirects visitors to Verity's platform.[1][2]
Rather than serving raw filing documents, inFilings focuses on disclosure analysis: redline comparisons across filing versions, alerting on material changes, generative-AI summaries, and differentiated datasets such as executive incentive compensation and SPAC/IPO events. Verity states that its products are trusted by more than 300 funds.[2]
What It Does
inFilings ingests periodic and current SEC filings, including 10-Ks, 10-Qs, proxies, 8-Ks, press releases and earnings transcripts, and restructures their content so analysts can monitor changes across a portfolio instead of reading filings manually. Alerts and heatmaps surface events such as newly disclosed legal proceedings or governance changes, while side-by-side redlines compare any section of a filing against prior versions over roughly five years of history.[2]
The service differs from working directly with EDGAR by filtering, tagging and structuring disclosures, then layering analytics such as summaries, sentiment-oriented transcript reports and watchlist tracking on top.[2]
Coverage and Datasets
Covered document types include annual and quarterly reports, proxy statements, press releases and earnings transcripts enhanced with AI-generated summaries of transcripts and of the MD&A sections of 10-K/10-Q filings.[2]
Beyond filings text, the product maintains proprietary datasets: an executive incentive-compensation dataset built from proxies, SPAC and IPO event data including lockups, peer-group mappings, risk-factor changes and critical audit matters.[2]
Delivery and Integration
Access is provided through the Verity web platform, automated email digests such as daily 8-K and IPO summaries, and programmatic channels including an SEC Filings API for NLP and sentiment workloads and, more recently, an MCP server for connecting AI tools to the data.[2]
The product is sold through demonstration requests handled by Verity's sales team rather than via published pricing.[2]
Buyers and Use Cases
Target customers are hedge funds, asset managers and quantitative teams spanning public equity, fixed income, private equity and hybrid strategies; Verity describes its user base as over 300 funds managing $10 trillion in combined assets.[2]
Most firms pair inFilings with VerityData's companion product InsiderScore, which tracks insider trading and buyback activity, combining disclosure context with corporate insider dynamics in a single workflow.[2]
History
inFilings originated as an independent SEC filings service at infilings.com. That domain now displays a notice stating that "inFilings is now part of the Verity family of integrated financial research solutions" and directs users to Verity's site.[1]
Verity presents itself on its website as "now a TMX company".[2]
More datasets from inFilings
inFilings lists 1 datasets on this encyclopedia. The most representative listings:
More about Public Records & Filings
Public Records & Filings is one of the signal families covered by The Alternative Data Encyclopedia, with 28 providers and 396 datasets listed in the register. For how the signal is generated, its caveats and the compliance considerations, and the full provider list, see the category article.
Further reading
- Open vs commercial alternative dataWhat free and open datasets can and cannot do: where public data rivals paid panels, where it cannot compete, and how open sources fit a professional research workflow.
- Free alternative data sourcesThe practical list of free alternative-data sources for investors: public filings, official statistics, satellite and earth observation, on-chain data, web archives and open registries, what each covers, what it costs in engineering effort, and where free data falls short.