# 📊 Earnings Call Intelligence — Guidance & Risk Signals (`nexgendata/earnings-transcripts`) Actor Derived earnings intelligence for US public companies from SEC 8-K filings: guidance direction, sentiment by segment, key topics, risk flags, and short attributed quotes. SEC-sourced — no third-party transcript resale. - **URL**: https://apify.com/nexgendata/earnings-transcripts.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Business, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $500.00 / 1,000 earnings intelligence records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## 📊 Earnings Call Intelligence — Guidance, Sentiment & Risk Signals Turn US public-company earnings into **structured, analyst-ready intelligence** — sourced from official **SEC 8-K (Item 2.02) earnings filings**, not scraped from anyone else's transcript database. Get the *read* on every quarter — guidance direction, sentiment, key topics, and risk flags — pay-per-result, no terminal seat required. ### ⚡ What you get | Field | What it tells you | |---|---| | `summary` | Derived extractive summary of the earnings release | | `guidance` | Forward-looking / guidance statements pulled from the filing | | `guidance_delta` | Direction (**raised / lowered / maintained / not_stated**) with confidence + method | | `guidance_delta.figure_trend_vs_prior_quarter` | Secondary quarter-over-quarter figure trend (up / down / flat) | | `key_topics` | AI, buybacks, China, margins, supply chain, capex, tariffs, and more | | `sentiment_by_segment` | Tone of the release (and Q&A when a transcript source is available) | | `risk_flags` | litigation, demand weakness, margin pressure, restructuring, going-concern | | `participants` | Named executives mentioned in the release | | `notable_quotes` | Short, attributed executive quotes from the official release | | `qa_tension` / `analyst_pushback` / `management_confidence` | Q&A signals (when a call transcript source is reachable) | | `source_url`, `fiscal_period`, `call_date`, `data_source`, `input_basis` | Full provenance | ### 📊 Sample Output ![Earnings Call Intelligence sample output — SEC-sourced guidance, sentiment, key-topic and risk-flag signals for equity research analysts, NLP/quant funds and IR teams](https://api.apify.com/v2/key-value-stores/8gLgXMBveEI1tTz1z/records/earnings-call-intelligence-output.png) ```json { "symbol": "JPM", "company_name": "JPMorgan Chase & Co.", "fiscal_period": "Q1 2026", "call_date": "2026-04-14", "source_url": "https://www.sec.gov/Archives/edgar/data/19617/.../ex991.htm", "data_source": "sec_8k", "input_basis": "press_release", "summary": "JPMorgan Chase reported first-quarter net income with record revenue across...", "guidance_delta": { "direction": "raised", "confidence": "high", "method": "explicit_company_statement", "figure_trend_vs_prior_quarter": { "trend": "up", "prior_period": "Q4 2025" } }, "key_topics": ["guidance", "buyback", "macro"], "sentiment_by_segment": { "prepared_or_release": { "score": 0.21, "label": "positive" } }, "risk_flags": ["litigation"], "notable_quotes": [{ "quote": "...", "attributed_to": "Jamie Dimon" }], "disclaimer": "Derived analytical signals about a public earnings event. Not investment advice." } ```` ### 🎯 Use cases - **Equity research analysts** — skip the 12,000-word read; get the guidance change, tone, and risk flags per name. - **NLP / quant funds** — clean, structured earnings signals to feed factor models and event studies. - **Investor-relations & corporate strategy** — benchmark how peers framed guidance and which topics they led with. - **Financial media & newsletters** — fast, sourced earnings reads with attributed quotes and a filing link. - **AI agents & dashboards** — drop-in JSON earnings intelligence over MCP or the Apify API. ### 🚀 How to use Provide tickers (or leave empty to run a default large-cap watchlist). Set `max_quarters_per_symbol` to 2+ to compare guidance across consecutive quarters. **Python (apify-client):** ```python from apify_client import ApifyClient client = ApifyClient("") run = client.actor("nexgendata/earnings-transcripts").call(run_input={ "symbols": ["AAPL", "NVDA", "JPM"], "max_quarters_per_symbol": 2 }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["symbol"], item["guidance_delta"]["direction"], item["key_topics"]) ``` **cURL:** ```bash curl -X POST "https://api.apify.com/v2/acts/nexgendata~earnings-transcripts/runs?token=" \ -H "Content-Type: application/json" \ -d '{"symbols":["AAPL","NVDA"],"max_quarters_per_symbol":1}' ``` **MCP:** This Actor is callable from any MCP-compatible client via Apify's Actor MCP server for agentic earnings monitoring. ### ⚖️ Legal & data sources - **Primary source:** US SEC EDGAR — company 8-K filings under **Item 2.02 (Results of Operations)**, Exhibit 99.1 earnings releases. Accessed with a declared User-Agent and SEC rate-limit compliance. - The Actor outputs **derived analysis and short factual extraction** about public earnings events. It does **not** store or reproduce full third-party transcript text. - `notable_quotes` are short, attributed quotes drawn from the company's own earnings press release (text companies publish for redistribution). - This is informational, derived analytics — **not investment advice**. ### ❓ FAQ **Where does the data come from?** Each company's official SEC 8-K (Item 2.02) earnings filing on EDGAR. **Do I get the full call transcript?** No. This Actor produces derived signals and short attributed quotes, not transcript text. A future audio-transcription tier will add owned full-text coverage. **Why is `guidance_delta` sometimes `not_stated`?** Some companies (e.g. Apple) don't issue formal forward guidance in the release. We report what the company actually stated rather than guessing — and add a secondary figure trend where comparable numbers exist. **When do the Q\&A fields populate?** `qa_tension`, `analyst_pushback`, and `management_confidence` populate only when a call-transcript source is reachable; otherwise the record is press-release-based and those fields are null. **How fresh is it?** As fresh as EDGAR — typically minutes-to-hours after a company furnishes its 8-K. Coverage is quarterly by nature. **Can I run it on a watchlist automatically?** Yes — schedule it with any ticker list, or leave `symbols` empty to monitor a default large-cap set. ### 🔗 Related Actors — SEC & Markets Intelligence - [SEC Form 8-K Material Events Scraper](https://apify.com/nexgendata/sec-form-8k-material-events-scraper) — every material 8-K event, not just earnings - [13F Holdings Delta Tracker](https://apify.com/nexgendata/13f-holdings-delta-tracker) — institutional position changes - [SEC Form NPORT-P Mutual Fund & ETF Holdings](https://apify.com/nexgendata/sec-form-nport-p-mutual-fund-holdings) — fund-level holdings - [SEC Form NT Late-Filing Tracker](https://apify.com/nexgendata/sec-form-nt-late-filing-tracker) — forensic early-warning on late filers - [SEC Litigation Releases](https://apify.com/nexgendata/sec-litigation-releases) — enforcement actions - [PR Newswire Releases](https://apify.com/nexgendata/pr-newswire-press-releases-scraper) — corporate press-release firehose ### 🏷️ About NexGenData Official-source business and financial intelligence Actors, built for analysts, funds, and AI agents. Explore the full fleet at [apify.com/nexgendata](https://apify.com/nexgendata). *New to Apify? [Start free](https://www.apify.com/?fpr=2ayu9b).* # Actor input Schema ## `symbols` (type: `array`): US stock tickers (e.g. AAPL, MSFT, NVDA) to generate earnings intelligence for, sourced from each company's most recent SEC 8-K (Item 2.02) earnings filing. Case-insensitive. Leave empty to run a default large-cap watchlist (handy for smoke tests and monitoring — earnings are quarterly, so a given ticker may not have a fresh filing every week). ## `max_quarters_per_symbol` (type: `integer`): How many recent earnings quarters to analyze per ticker (most recent first). 1 = latest quarter only. Use 2+ to compare guidance across consecutive quarters. ## `recent_only` (type: `boolean`): If enabled, skip earnings filings older than ~120 days. Useful for monitoring only the latest reporting season. ## `include_short_quotes` (type: `boolean`): Include up to 2 short, attributed executive quotes drawn from the official earnings press release (the quotes companies publish for redistribution). No long excerpts; no full transcript text is ever included. ## `allow_ephemeral_fallback` (type: `boolean`): Reserved for analyst Q\&A enrichment. When enabled and a transcript source is reachable, its text is read in memory only to compute Q\&A-tension signals and is never stored or output. Off by default. Full owned-transcript coverage ships in a future audio-transcription tier. ## Actor input object example ```json { "symbols": [ "AAPL", "NVDA", "MSFT" ], "max_quarters_per_symbol": 1, "recent_only": false, "include_short_quotes": true, "allow_ephemeral_fallback": false } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "symbols": [ "AAPL", "NVDA", "MSFT" ], "max_quarters_per_symbol": 1, "recent_only": false, "include_short_quotes": true, "allow_ephemeral_fallback": false }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/earnings-transcripts").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "symbols": [ "AAPL", "NVDA", "MSFT", ], "max_quarters_per_symbol": 1, "recent_only": False, "include_short_quotes": True, "allow_ephemeral_fallback": False, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/earnings-transcripts").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "symbols": [ "AAPL", "NVDA", "MSFT" ], "max_quarters_per_symbol": 1, "recent_only": false, "include_short_quotes": true, "allow_ephemeral_fallback": false }' | apify call nexgendata/earnings-transcripts --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/earnings-transcripts", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "📊 Earnings Call Intelligence — Guidance & Risk Signals", "description": "Derived earnings intelligence for US public companies from SEC 8-K filings: guidance direction, sentiment by segment, key topics, risk flags, and short attributed quotes. SEC-sourced — no third-party transcript resale.", "version": "0.0", "x-build-id": "kSHX25Wexhtp7ljUY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~earnings-transcripts/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-earnings-transcripts", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~earnings-transcripts/runs": { "post": { "operationId": "runs-sync-nexgendata-earnings-transcripts", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~earnings-transcripts/run-sync": { "post": { "operationId": "run-sync-nexgendata-earnings-transcripts", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "symbols": { "title": "Ticker symbols", "type": "array", "description": "US stock tickers (e.g. AAPL, MSFT, NVDA) to generate earnings intelligence for, sourced from each company's most recent SEC 8-K (Item 2.02) earnings filing. Case-insensitive. Leave empty to run a default large-cap watchlist (handy for smoke tests and monitoring — earnings are quarterly, so a given ticker may not have a fresh filing every week).", "default": [], "items": { "type": "string" } }, "max_quarters_per_symbol": { "title": "Max quarters per symbol", "minimum": 1, "maximum": 8, "type": "integer", "description": "How many recent earnings quarters to analyze per ticker (most recent first). 1 = latest quarter only. Use 2+ to compare guidance across consecutive quarters.", "default": 1 }, "recent_only": { "title": "Recent filings only", "type": "boolean", "description": "If enabled, skip earnings filings older than ~120 days. Useful for monitoring only the latest reporting season.", "default": false }, "include_short_quotes": { "title": "Include short attributed quotes", "type": "boolean", "description": "Include up to 2 short, attributed executive quotes drawn from the official earnings press release (the quotes companies publish for redistribution). No long excerpts; no full transcript text is ever included.", "default": true }, "allow_ephemeral_fallback": { "title": "Allow ephemeral transcript fallback (advanced)", "type": "boolean", "description": "Reserved for analyst Q&A enrichment. When enabled and a transcript source is reachable, its text is read in memory only to compute Q&A-tension signals and is never stored or output. Off by default. Full owned-transcript coverage ships in a future audio-transcription tier.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```