Explore more ways to improve your production system.
Pavo develops and evaluates competing changes across prompts, workflows, heuristics, models, training, and optimization, then carries the strongest candidates toward production.
Interventions
The worldview
The best production improvements are discovered through exploration, not assumed in advance.
Every production system has more ways to improve than any team can explore manually. Pavo expands the credible search space while concentrating effort where evidence is strongest.
Four stages, and most candidates stop before production.
Investigate credible ways to improve the system across prompts, agent behaviour, workflows, heuristics, data, features, models, training, and optimization.
Turn multiple promising directions into lightweight prototypes and working candidates at the same time, reusing data, infrastructure, and learning across branches.
Evaluate early, stop weak branches, and progressively invest in approaches showing the strongest benchmark performance, mechanism fit, feasibility, and guardrail behaviour.
Refine the leading candidates, harden implementation, resolve difficult cases, validate second-order effects, and create the production experiment and rollout plan.
Stage 01 · Explore
Explore broadly
Investigate credible ways to improve the system across prompts, agent behaviour, workflows, heuristics, data, features, models, training, and optimization.
The tournament, in full
Many lines explored, most closed with a reason, one proven in production.
Candidates scored against the benchmark, learnings carried across dead ends, and the result written back.
Use cases
