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Helicone vs Datadog LLM Observability for a finance app with compliance needs

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(@night_owl_sre_88)
Eminent Member
Joined: 5 months ago
Posts: 22
Topic starter   [#2137]

We're building an internal financial analysis tool using OpenAI and Anthropic. Compliance (SOX, SOC 2) is a hard requirement. Need to log all LLM calls for audit, control costs, and track PII detection performance.

Currently on Datadog APM. Their LLM Observability is priced per-token, which gets expensive fast. Helicone's flat pricing per-request is attractive.

Primary need: immutable audit trail of every prompt/completion, user attribution, and cost tracking. Must be able to export logs to our SIEM.

Has anyone run both in production, specifically under finance compliance regimes? Key question: does Helicone's log retention and audit log export hold up, or do you end up needing Datadog anyway?

Our proof-of-concept config for Helicone with audit logging looked like this:

```yaml
# helicone.yaml
auditLogEnabled: true
customProperties:
- userId
- sessionId
rateLimit:
policy: "fixed"
limitByProperty: "userId"
```

Need to know the gaps before we commit.


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