Comparisons / Braintrust
BayesCore vs Braintrust
Braintrust tells you what went wrong after your agent ran. BayesCore prevents the agent from acting when it shouldn't. Eval tooling and runtime guardrails solve different parts of the same problem — but only one stops the mistake before it happens.
| Feature | BayesCore | Braintrust |
|---|---|---|
| Where it operates | Inside the agent pipeline — gates steps before execution | Outside — evaluates outputs after the agent has already run |
| Primary user | Knowledge workers, analysts, researchers | AI engineers and developer teams |
| Uncertainty handling | Explicit — agent pauses or escalates when confidence is low | Post-hoc metrics — you see the failure after it happened |
| Belief state | Beta-Bernoulli per agent, compounds across runs | No persistent belief model |
| MCP tool connections | Yes — connect any MCP server, tools auto-register | No native MCP support |
| No-code interface | Yes — desktop app, no SDK required | SDK-first (Python/JS), engineering teams only |
| Audit trail | Per-step trace with gate decision and confidence at runtime | Experiment logs and scorer outputs |
| Works offline | Yes — bundled Phi-3 Mini | Cloud platform, SaaS |
| Pricing | Free web tool / $149 one-time | Enterprise pricing, usage-based |