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What is a Custom Extractor?

Octave’s analytics pipeline extracts a fixed set of finding types from every event: objections, pain points, competitor mentions, use cases, and the rest. A Custom Extractor adds your own. You describe what to look for in plain language, pick which events it runs on, and Octave produces findings for it alongside the built-in ones. Use one when the question is specific to your business: which calls mention a security review, how many prospects bring up a particular integration, what budget range buyers state on discovery calls, whether the rep ran the qualification framework your team uses. Custom Extractors require the custom-extractors entitlement.

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What an extractor defines

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Output modes

When you create an extractor, Octave runs a one-time mapping that proposes which Library entities its findings relate to. You can adjust those anchors afterwards.

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Lifecycle

An extractor is created ACTIVE by default, which means it runs on every newly ingested event that matches. Create it as DRAFT to hold it for review and backtesting first. PAUSED stops it temporarily, and ARCHIVED stops it for good while keeping its findings. Deleting an extractor also retires every finding it produced, along with any Insight that reports on that extractor alone.

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Test, then run on history

A new extractor only sees events that arrive after it is active. The recommended path to cover history:
  1. Backtest. Run the saved extractor, or an unsaved draft, against up to 10 real events without saving any findings. Use it to tune the prompt.
  2. Estimate. Count the historical events the extractor would select in a time window and estimate the credits.
  3. Backfill. Start a durable background job over that window. It saves progress, resumes after interruptions, skips events that already have findings from this extractor, and can be paused, resumed, or cancelled.
  4. Purge if needed. If a backfill ran with the wrong criteria, purge the extractor’s findings, fix the definition, and backfill again.
Every event an extractor processes, in a backtest or a backfill, is a credit-charged LLM call.

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Reading the results

Custom findings are ordinary findings. Search them with Search Findings, filtering by customExtractorOIds, and aggregate them with the event analytics endpoints.

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Managing Custom Extractors via API

  • GET /api/v2/custom-extractor/list: list extractors with their full definitions
  • POST /api/v2/custom-extractor/create: create an extractor
  • POST /api/v2/custom-extractor/update: change its definition, anchors, or status
  • DELETE /api/v2/custom-extractor/delete: delete it and retire its findings
  • POST /api/v2/custom-extractor/backtest: try it on up to 10 events without saving findings
  • POST /api/v2/custom-extractor/backfill/estimate: count events and estimate credits for a backfill
  • POST /api/v2/custom-extractor/backfill/start: start a historical backfill
  • GET /api/v2/custom-extractor/backfill/get: check a backfill’s progress
  • POST /api/v2/custom-extractor/backfill/control: pause, resume, or cancel a backfill
  • POST /api/v2/custom-extractor/purge-findings: retire its findings but keep the extractor