Margin-aware AI SaaS
Map user credits to real inference cost. Route cheap models for bulk tasks, premium models for quality-critical steps.
Helicone excels at LLM observability — logging, tracing, and cost visibility across providers. ozDNA is vertical AI infrastructure: observability plus RAG operating layer, routing policy, and margin controls for production workflows.
Fair comparison — choose Helicone when routing and proxy fit is enough. Choose ozDNA when RAG reliability, token economics, and live vertical proof matter. Live proof: TezMakale.
| Capability | Helicone | ozDNA |
|---|---|---|
| Multi-provider LLM routing | Yes | Yes |
| Fallback / retry across models | Yes | Yes |
| Cost per request / workflow | Basic logging | First-class cost engine |
| Usage economics (credits → real LLM spend) | — | Yes |
| Production RAG (chunk, ingest, hybrid retrieval) | — | RAG operating layer |
| Vertical modes (academic, legal, financial) | — | Prompt + corpus per mode |
| Live production vertical AI proof | Varies | TezMakale (live) |
| Deployment model | SaaS / self-host | Managed PaaS (private beta) |
Map user credits to real inference cost. Route cheap models for bulk tasks, premium models for quality-critical steps.
Chunking, freshness, hybrid retrieval, and eval hooks — not just vector search bolted onto a gateway.
Academic AI at TezMakale. RegTech at ComplyDNA. Same stack, different corpora.
TezMakale handles real student traffic in Turkey: AI detection, detailed reports, token limits, peak-season spikes.
Join early access — mention Helicone on the waitlist. We will map your workflows onto ozDNA.
Get Early AccessHelicone is a separate project; this page compares product fit, not affiliation.