AI & RAG
Agentic Control-Gap Researcher Across the Evidence Corpus
Given a control framework requirement, an agent searches the frozen evidence corpus for supporting clauses, judges whether the control is fully, partially, or not evidenced.
How it runs
The automated pipeline, trigger to output.
- TriggerFramework or control list submitted for gap analysis
- ActionRetrieve candidate evidence clauses per control from pgvectorPostgres
- ActionJudge coverage (full/partial/none) and capture citing clausesOpenAI
- LogicSeparate evidenced controls from gaps and partials
- OutputPublish cited control-gap memo to ConfluenceConfluence
What it does
Runs an agentic readiness pass over a control framework. For each requirement, the agent queries the frozen evidence corpus, gathers candidate clauses, and reasons about whether they fully satisfy the control, only partially cover it, or leave a gap. It produces a cited gap memo summarizing coverage per control and publishes it to Confluence for the compliance owner.
When to use it
When prepping for a new framework or audit and you need an honest, cited coverage map of where evidence exists, where it's thin, and where it's missing, rather than a manual control-by-control spreadsheet crawl.
How it works
- 1A requested framework or control list triggers the run.
- 2The agent iterates controls, retrieving candidate evidence clauses from the corpus in pgvector for each.
- 3OpenAI judges coverage per control (full, partial, none) and captures the citing clauses.
- 4A branch separates evidenced controls from gaps and partial-coverage items.
- 5The agent assembles a cited gap memo with coverage status per control.
- 6The memo is published to the compliance space in Confluence.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect ConfluenceSpaces, pages, blueprints.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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