Stop shipping answers you can't stand behind
Answer-first capsule: AI and RAG builders do not need another plausible paragraph. They need a dated public-records answer that names the government source, carries the limitation, is signed and attested, and can be re-checked after the user sees it. Fonteum turns the same question an LLM might answer from memory into a source-backed answer across .
Published June 24, 2026 · Last reviewed June 2026 · Capability comparison — public facts only
From plausible text to a signed, re-checkable public-records answer
| Capability | Ungrounded LLM answer | Fonteum |
|---|---|---|
| Same question | Which public records show whether a provider or vendor appears on an exclusion list? | Which public records show whether a provider or vendor appears on an exclusion list? |
| Example answer | A plausible paragraph says the organization is probably clear, cites no source, gives no checked date, and may be stale by the time it is read. | The OIG LEIE snapshot contains aggregate exclusion records. Fonteum answers name the source, snapshot date, limitation, and evidence artifact; no individual record is named in this aggregate example. |
| Source | May blend training data, web memory, or retrieval snippets without a field-level citation. | Government record first — OIG, SAM.gov, CMS, HRSA, or another registered source family named in the answer. |
| Date | Often no as-of date, or a generic phrase like recently. | Snapshot-dated and last-checked at the field level, so the answer says when it was checked. |
| Signature | No signed evidence package travels with the text. | Signed, attested, and chained to the snapshot digest so the answer can be checked again later. |
| Time-machine edge | Answers the present-tense question only, and may not know what changed since training or retrieval. | As-of history: ask what the public record said on a past date, not only what the current page says now. |
| Re-check line | A user can rerun the prompt, but cannot re-create the exact upstream record behind the sentence. | Re-fetch the government file, compare the digest, and re-check the evidence at /verify. |
| RAG handoff | The answer is a text blob the application has to defend after the fact. | The answer ships with source, date, limitation, and evidence pointers that a RAG app can show to the user. |
| Failure mode | Confident, unsourced, and possibly stale output that sounds useful until someone asks for the record. | A dated public-record answer that can be quoted, audited, and re-checked without naming nonessential individuals. |
This comparison is aggregate and FCRA-safe. The worked example cites an OIG LEIE aggregate count and names no individuals; it compares answer mechanics, not any provider, contractor, or person.
The evidence path is the product
Answer-first capsule
Stop shipping answers you can't stand behind. If an AI product answers a compliance, credentialing, diligence, or sourcing question, the answer needs a source, an as-of date, a limitation, and an evidence trail at the moment it leaves the model.
The time-machine edge
Most LLM answers collapse time into now. Public-records products need a different question: what did the government record say on the date the decision was made? Fonteum keeps dated snapshots so an answer can be reconstructed as of a past date.
The re-check line
A Fonteum answer is designed to be re-checked: source family, snapshot date, SHA-256 digest, and attestation chain point back to the file. The user can inspect the evidence path at /verify instead of accepting a sentence on faith.
Compare other data capabilities
Provider data vs raw public files →
NPI-resolved, provenance-tracked records vs parsing bulk CSVs yourself.
Live provider data vs annual snapshots →
Continuously refreshed, per-field-dated federal data vs yearly editions.
Federal exclusion screening vs checking SAM.gov by hand →
Award-time, point-in-time SAM.gov exclusion evidence vs a manual lookup.
Common questions
- Why is an ungrounded LLM answer a problem for public-records data?
- The problem is not fluency; it is accountability. A public-records answer can affect compliance, credentialing, diligence, or user safety. If the answer has no source, checked date, limitation, or evidence trail, the builder cannot show what record supports it when a user, auditor, or customer asks.
- What does Fonteum add to a RAG or agent stack?
- Fonteum adds the evidence layer: with source, date, limitation, digest, and attestation metadata attached to the record. A RAG or agent application can cite the government record instead of asking the model to defend an unsupported answer.
- What is the worked example on this page?
- The example is aggregate and FCRA-safe: the OIG LEIE snapshot carries exclusion records. The point is not to name an individual; it is to show the difference between an unsourced answer and a dated answer that points back to OIG as the government record.
- How does the time-machine edge help AI builders?
- It lets the application answer as-of questions. A present-tense lookup tells you what the list says now; a dated snapshot tells you what the list said on the date a decision, contract, credentialing action, or dataset release occurred. That is the answer a defensible AI workflow needs.
- Can I use this through an API?
- Yes. Fonteum exposes public-records data through API surfaces for builders, plus research downloads for aggregate work. The important distinction is that the data returned to the application carries source and evidence metadata, so the answer can keep its citation path when it moves into a model response.
Ground your next answer in the public record.
Start with /for/rag, connect agents at /for/ai-agents, inspect the API, re-check evidence at /verify, or browse aggregate work at /research.
- /for/rag → How RAG builders ground provider-data answers in source-cited records.
- /for/ai-agents → How agents call Fonteum with evidence metadata intact.
- /api → API entry point for public-records data with source and date metadata.
- /verify → Re-check signed evidence artifacts and snapshot digests.
- /research → Aggregate public-records research with downloads and methodology.