Reporting Window Finder

Resolve a domain, ticker, ISIN, LEI, CIK or company name to a listed company identity. Returns 44 fields per input: legal name, primary ticker, ISIN, LEI, CIK, domain, primary exchange, country, currency, sector, security type, public float band, shares outstanding, and the provenance of each. Every input returns exactly one row, including the ones that match nothing, which come back with match_method set to no_match and every other field null. Read matched_on to see which identifier produced the row. Use this when you hold identifiers and need the listed identity behind them; use qualify_company for a yes or no on listed status, get_reporting_timing for dates, and build_company_universe when you hold filters rather than identifiers. The filter inputs (exchange_codes, country_codes, regions, sectors, and the rest) narrow which matched rows come back. Charged per company row returned, including a no_match row, because the lookup ran either way. Requires an APIFY_TOKEN and consumes Apify credits. Read only.

Answer whether a company is publicly listed. Takes the same identifiers as resolve_company and returns a listed status verdict per input. Set listed_only to keep only the companies proven to be listed, or suppress_listed to remove them, which is what you want when selling only into private companies. By default an unmatched company returns is_listed null rather than false, because a non match may mean the company is private OR that the dataset does not hold its domain; set assume_unmatched_is_private to true to opt into reading a non match as private. Use this to split a prospect list into listed and private companies before outreach; use resolve_company when you need the full identity fields. Identify companies with company_domain, company_domains, tickers, isins, leis, ciks, or company_names; every other input is an optional filter shared with resolve_company (exchange, country, region, sector, security type, float band, fiscal year end, cadence, and data quality switches). Charged per company row returned. Requires an APIFY_TOKEN and consumes Apify credits. Read only.

Find when a public company next reports, and when to reach out around it. Returns 75 fields per input: fiscal year end, derived reporting cadence and its confidence, the next reporting event with its type, period and date, days to event, and the open and close of an outreach window you define with window_lead_days and window_lag_days, which default to 70 and 42. window_status is one of open, not_yet, closed_passed or no_event and is the field to filter on. Dates are PREDICTED from filing history, not announced: read next_event_is_estimate and confidence_band, whose thresholds sit at 0.80 and 0.50. TIMING ROWS COVER US COMPANIES ONLY. A non US company resolves fully for identity and returns a stated timing_unavailable_reason rather than a guessed date, and is still charged as a timing row because the work ran. Charged per timing row returned, never additionally as a resolved company. Requires an APIFY_TOKEN and consumes Apify credits. Read only.

Build a list of listed companies from filters rather than from identifiers you already hold. Filter by exchange, country, region, sector, security type, public float band, fiscal year end month, reporting cadence, operating status and foreign private issuer status. Returns 44 fields per company, the same shape resolve_company returns. At least one filter is required, so a bare call cannot pull the whole universe. This tool does NOT accept company identifiers: use resolve_company, qualify_company or get_reporting_timing for specific companies. SET limit EXPLICITLY. It defaults to 1000 and you are charged per company row returned, so an unbounded call is an expensive call. Truncation is always reported, never silent. Requires an APIFY_TOKEN and consumes Apify credits. Read only.

Show how reporting load is distributed over time, so you can find the busy weeks and the quiet ones. Returns aggregate rows per bucket, not per company: period start and end, event count, company count, estimated share and mean confidence. Bucket by week or month with season_group_by, and optionally split by sector, country or exchange with season_split_by. The window defaults to today through 180 days out; set season_from and season_to for another. At least one filter is required and company identifiers are not accepted. Use this to plan campaign timing across a market, not to time one account; for a single company use get_reporting_timing. Narrow the population with the same filters build_company_universe takes (exchange_codes, country_codes, regions, sectors, public_float_bands, cadences). Charged per aggregate row returned, which is far fewer rows than the companies behind them. Requires an APIFY_TOKEN and consumes Apify credits. Read only.