How to build a multilingual AI agent is more than translating prompts. You need language detection, locale-aware tools, evaluation per language and brand tone that survives Hindi, Gujarati, English code-mixing — common in India.
Design choices that matter
- Auto-detect vs user-selected language
- Code-mixing tolerance in speech/text
- Locale for dates, currency and addresses
- Which languages are in v1 vs later
Voice vs chat complexity
Voice adds ASR/TTS quality variance by language. Budget more eval and telephony testing for calling agents. See AI calling agents and AI agents.
Knowledge and RAG considerations
Store documents per language or use translation layers carefully. Citations should match the user’s language when possible — RAG for business assistants.
Evaluation per locale
- Build golden transcripts/chat logs per language
- Measure contain rate separately
- Test escalation phrases locals actually use
- Review cultural tone with native speakers
Rollout tip
Launch two languages well before adding ten. Quality beats coverage. Pair with AI guardrails for policy consistency across languages.
Scope multilingual v1 properly
Contact Altron Technologies with your language list and channels for a phased plan.
