Multilingual Assessments for Indian Languages
Assess candidates and employees in Hindi, Tamil, Telugu, Kannada, and Malayalam — with AI Voice Interviews live in Hindi (formal शुद्ध हिन्दी or conversational Hinglish, your choice of Devanagari or Roman script).
Key Features
5 Indian Languages Supported
Hindi, Tamil, Telugu, Kannada, and Malayalam. Native script for every language, with Roman transliteration available for Hindi — candidates choose how they want to read.
AI-Powered Translation
Production-grade AI translation that adapts tone to the script. Formal phrasing for native script, conversational phrasing for Roman script — matching how candidates actually communicate.
Transliteration & Roman Script
Candidates choose native script, Roman script, or both. Hindi in Devanagari or Roman letters — same content, candidate's preferred reading format.
Mixed-Language Scoring
AI evaluates content quality regardless of language. Hinglish, code-switching, and mixed-language responses are scored without penalty or back-translation.
Translation Glossary Management
Org-level glossary with per-language term overrides. Mark terms to keep in English. Ensures domain-specific vocabulary stays consistent across translations.
Per-Assessment Language Config
Configure language availability per assessment. Set script preferences, enable transliteration, and let candidates pick their language on the welcome screen.
From English content to multilingual assessment in three steps
Author once in English. AI handles the rest.
Build in English
Create your assessment content in English as usual — case studies, SJT scenarios, and MCQ questions. No changes to your content workflow.
AI Translates
In the Translations step, select target languages. AI translates content with register-appropriate phrasing — formal for native script, colloquial for Roman. Review and edit translations before publishing.
Candidates Choose
On the assessment welcome screen, candidates pick their language and script preference. The full assessment — questions, instructions, and UI — appears in their chosen language.
Why language accessibility matters for fair assessment
India's workforce is multilingual by default. Most candidates think in their regional language even if they can read English. When assessments are English-only, you're measuring English proficiency as a confounding variable — not the job competencies you actually care about.
The challenge is deeper than translation. The same concept reads differently in formal Devanagari Hindi versus colloquial Roman Hindi. A direct translation can feel stilted and unnatural — creating cognitive friction that disadvantages candidates who would otherwise perform well. Kaairo handles all three dimensions — language, script, and tone — so every candidate gets content that feels natural to read.
Mixed-language responses are the norm, not the exception. In Indian workplaces, professionals routinely code-switch between English and their regional language — especially for technical concepts. Kaairo's scoring evaluates the quality of thinking, not linguistic purity. A candidate who answers a case study in Hinglish is scored on problem framing, creative breadth, and solution feasibility — not on whether they wrote in pure Hindi or pure English.
The result: assessments that measure what candidates can actually do, in the language they think best in, without compromising scoring rigour.
Kaaira now speaks Hindi — formal or Hinglish, your choice
AI Voice Interviews ship today in Hindi, in two registers: formal शुद्ध हिन्दी (with Hindi vocabulary throughout) and conversational workplace Hinglish (with common English loanwords preserved). On-screen text can be Devanagari or Roman script, and candidates can respond in Hindi, English, or any mix without scoring penalty.
Frequently asked questions
Which languages are supported?
Currently: Hindi, Tamil, Telugu, Kannada, and Malayalam. Each language ships in native script; Hindi additionally offers Roman transliteration. Bengali and additional Indian languages are on the roadmap.
Does translation affect scoring accuracy?
No. The AI evaluates content quality regardless of which language a candidate writes in. For MCQs and SJTs, scoring is based on which option the candidate selected — language has zero impact on scores.
Can candidates mix languages in their responses?
Yes. Mixed-language responses (e.g., Hinglish — Hindi and English together) are scored without penalty. The AI evaluates the quality of thinking, not linguistic purity.
How does the translation glossary work?
Organisations can define per-language term overrides. For example, you can mark 'machine learning' to stay in English rather than being translated. This ensures domain-specific vocabulary remains consistent across all translations.
Do AI Voice Interviews support Indian languages?
Yes — Hindi voice interviews ship today, in both formal (शुद्ध हिन्दी) and conversational Hinglish registers. Candidates can read the interviewer's intro, questions, and transitions in Devanagari or Roman script. Tamil, Telugu, Kannada, and Malayalam voice support is on the roadmap. Written assessments (Case Study, SJT, MCQ) fully support all 5 Indian languages today.
Ready to assess in local languages?
Reach candidates who think best in their native language. Request a demo to see multilingual assessments in action.
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