Better retrieval begins
with better evaluation.
Build controlled query and document scenarios to test the search and retrieval systems your organization depends on.
Discuss search evaluationFind the gaps
before your users do.
Enterprise knowledge is varied, messy, and often sensitive. Synthetic evaluation datasets can help explore retrieval behavior without distributing real internal documents across every development environment.
Query diversity
Explore paraphrases, ambiguous questions, and specialist language across a defined knowledge domain.
Document scenarios
Design structured document examples with useful relationships, confusing overlaps, or missing context.
Retrieval evaluation
Compare results against an agreed relevance rubric and check how behavior changes across system versions.
A search test set
with a purpose.
A team defines a fictional internal knowledge domain, document relationships, and the questions it should answer. It reviews generated query and document pairs, assigns relevance judgments, and uses the approved set to compare retrieval configurations. Domain review and real world evaluation remain essential.
Data for evaluation.
Context for improvement.
RoboSynth supports the dataset workflow around enterprise search. Bring your existing retrieval architecture and evaluation goals so we can scope the data you need.
- Define the knowledge domain and user intents
- Include ambiguous and difficult queries
- Review document consistency and relevance
- Keep training and evaluation material separate
- Confirm supported text generation requirements
Test the questions your users will ask.
Bring your toughest data problem.
Let’s work out what comes next.