WANDR: an environment for evaluating agentic search
In a post published on July 14, 2026, Perplexity says it is making available a reinforcement-learning and evaluation environment for agentic search, synthesized from production traces with weak human supervision.
Source: WANDR: um ambiente de RL para avaliar busca agentic (github.com). Text prepared with AI from this source.
What happened and what to do
In a post dated July 14, 2026, Perplexity says it is making WANDR available, an evaluation and reinforcement-learning environment for agentic search. The company says the environment is synthesized from production traces with weak human supervision and is also used internally to train models.
A company developing agent-based search could build an evaluation environment from traces of its own operations, with suitable quality criteria and human review. Implementation could include collecting and processing records, reproducible test scenarios, and metrics to track results before changing production systems.
How the consultancy can help
Wendelmaques can diagnose the opportunity and available data, define an evaluation scope, and implement the collection, tests, and dashboards required. It can also support ongoing operation of the environment.
Next step
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