The data
How we know it works
168 experiments. 10 codebases. Multiple agents. Not a demo. Not a cherry-picked example. A controlled study.
89%
higher quality output
+2.3 avg point improvement
2x
rule compliance
8.5 vs 4.6 out of 10
+
consistent quality scores
no degradation as complexity increases
31%
median time savings
faster in 61% of runs
22%
median cost savings
cheaper in 53% of runs
88%
fewer structural violations
duplications, misplacements, dep errors
How the study worked
We ran controlled experiments comparing agent output with and without gjalla context.
10
Codebases
Real-world projects across multiple domains and languages
168
Experiments
Each task run twice: once with gjalla context, once without
Multiple
Agents tested
Claude, GPT-4, and others across different task types
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