Vertical SaaS (legal, fintech, healthcare)

You're building AI into a regulated product: contract review for legal, claim triage for insurance, prior-auth for healthcare. Compliance means every input scanned, every output logged, every request tied to a matter/case/account, and a 90-day retention policy your auditor will read, line by line, the first time something goes wrong. Rolling this yourself on top of OpenAI means owning the moderation queue, the audit schema and the redaction pipeline. All three. Before you ship anything.

Why Ringside

• Moderations endpoint. OpenAI-compat /v1/moderations as a free pre-check step; moderation.flagged webhook fires when content crosses your thresholds.
• FC-Customer + FC-Tag audit trail. Every call tagged with matter, case, patient or account ID; 90-day request log browsable via /v1/requests.
• Webhook fan-out to compliance. Signed deliveries of run lifecycle and moderation events straight into your evidence store or SIEM.

Architecture

In code

# Step 1: moderate input before it touches a frontier model
mod = client.moderations.create(
    input=document_text,
    model="text-moderation-latest",
)
if mod.results[0].flagged:
    raise HTTPException(422, "blocked by policy")

# Step 2: run the actual completion, tagged for audit
resp = client.chat.completions.create(
    model="fc:anthropic/claude-sonnet-4.6",
    messages=[
        {"role": "system", "content": LEGAL_SYSTEM_PROMPT},
        {"role": "user", "content": redacted_text},
    ],
    extra_headers={
        "FC-Customer": matter.customer_id,
        "FC-Tag": f"matter:{matter.id}",
        "FC-Tag": f"doc_class:{doc.classification}",
    },
)

# Step 3: webhook every completion into your compliance log
# (already registered: events=["run.completed","moderation.flagged"])

Cross-links

Examples

Endpoints

Used by

[TODO: real customers]

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