Why UnisAI
Format conversion + schema validation + side-by-side metrics when you switch AI providers. We convert formats and validate outputs—we don't just route. Use us when you're actually migrating, not when you're only load-balancing.
⚠️The problem
When you switch AI providers (or even model versions), format and schema drift break things: tool schemas, embedding dimensions, output contracts, and instruction-following behavior. Same prompt, new endpoint often means silent regressions.
- Tool-call specs and response schemas differ by provider
- Embedding dimensions don't match across vendors
- Teams need evals and validation before and after migration—not just a new API key
✓What we do
UnisAI gives you format conversion, schema validation, and side-by-side metrics when you switch providers or models. We normalize tool schemas and response constraints and validate output parity so you don't ship broken migrations. Use us when you're actually migrating, not when you're only load-balancing.
UnisAI vs LiteLLM vs MLFlow
We're not a proxy and we're not prompt versioning—we're cross-provider migration with validation.
| Tool | What it does | Use when |
|---|---|---|
| LiteLLM | Unified API / routing to multiple providers | You want one interface to call different providers (load-balancing, routing) |
| MLFlow | Prompt registry, LLM evaluation, compare prompt versions on same dataset | You version prompts and run evals within one workflow |
| UnisAI | Cross-provider migration: format conversion, schema validation, output parity | You're switching providers and need conversion + validation so you don't ship broken migrations |
Ready to try?
Join 10–20 early users. No pitch—just format conversion, schema validation, and side-by-side metrics when you switch providers.