What parts of SAM.gov screening can be automated?
Collection, filtering, first-pass scoring, and routing can be automated. The final qualify decision and any judgment about customer intent should stay with a person.
| Step | Automate? | Notes |
|---|---|---|
| Pull new notices | Yes | Scheduled pull using saved criteria or the SAM.gov public API |
| Hard filters | Yes | NAICS, set-aside, agency, notice type, response date |
| Fit scoring | Partly | Rules or AI scoring against your capabilities, with reasons shown |
| Summarize documents | Partly | Only when attachments are accessible and readable |
| Qualify decision | No | Capture owner decides |
How should the automated workflow be structured?
Treat it as an intake pipeline: every notice lands in one place with a status, a score, the reasons behind it, and an owner for anything that passes. Rejections should be logged so the rules can be tuned.
- 1. Scheduled pull of new and updated notices
- 2. Hard-filter rejects, logged with the reason
- 3. Fit score with a short written rationale
- 4. Create a task for passing notices, assigned to the capture owner
- 5. Flag notices whose attachments could not be retrieved
- 6. Weekly review of scores against actual decisions
What happens when a notice has no readable attachments?
It should go to a review path, not get a confident score. A title and short description are rarely enough to establish fit.
This is the most common failure we see in screening tools: a strong-looking score based only on a notice title, while the actual scope sits in an attachment nobody opened.
Should SAM.gov screening use AI or simple rules?
Use rules for anything objective, such as NAICS, set-asides, and dates. AI is useful for reading unstructured descriptions and attachments and drafting a fit summary, with a person reviewing the result.