LLM solutions

Multilingual retrieval & safety

Grounded generation, language-aware retrieval, policy evaluation, and safeguards for multilingual AI products.

The challenge

Retrieval and safety systems inherit language asymmetries. The right source may not be found, policy meaning may drift, and safeguards can overblock or miss risk outside English.

We test the full path from multilingual query to retrieved evidence, generated response, citation, policy decision, and user-facing refusal or recovery.

The work connects information architecture, model behavior, language variation, and harm analysis in one product-level view.

How we work

Evidence first. Decisions visible. Knowledge transferred.

We adapt the depth and sequence to your product stage, language scope, and internal team.

Phase 01

Map the control path

Trace queries, language detection, retrieval, reranking, generation, citations, moderation, and fallbacks.

Phase 02

Challenge the system

Build multilingual cases for retrieval gaps, code-switching, obfuscation, policy ambiguity, and cultural context.

Phase 03

Harden and monitor

Improve sources, routing, thresholds, prompts, safeguards, and ongoing market-specific evaluation.

Typical outputs

What your team can use.

  • Multilingual retrieval and safety assessment
  • Adversarial and representative challenge set
  • Control and policy recommendations
  • Monitoring metrics and release gates
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Bring us the brief

Make multilingual retrieval & safety move.

Tell us what you are building, which languages matter, and where progress is blocked.

Start the conversation