Today, we are introducing Sarvam Studio, a platform designed to help teams move content across languages and formats without losing quality.
Translation moves words. True content transformation carries meaning, structure, and intent intact while moving across languages and mediums.
Sarvam Studio is built to make that movement seamless. It brings together voice, text, and document workflows into a single workspace where multilingual content can be transformed, reviewed, and published without losing what makes it original.
Sarvam Studio gives content teams the ability to:
- Dub videos while preserving speaker identity and voice characteristics
- Translate complex documents while retaining layout, formatting, and structure
- Review, edit, and regenerate content through structured, agent-driven workflows
- Publish multilingual content at scale without duplicating effort
Instead of stitching together separate tools, teams operate within one coordinated environment. From source content to multilingual output, every step lives in the same workspace, with full visibility into edits, iterations, and approvals.
Sarvam Studio is currently being rolled out through a controlled early beta program with a small group of production partners across government, education, media, and publishing.
End-to-End Content Transformation
Studio allows a single piece of information to reach millions in their own language without losing the soul of the message. Built on Sarvam state-of-the-art speech and translation models, Studio handles the full content transformation lifecycle. From uploading source content to generating publication-ready outputs in multiple languages, the entire process lives within one coordinated environment.
What appears complex under the hood is designed to feel simple in practice.
Agentic Document Translation: Upload a book, report, or document of any kind. Studio translates it into multiple Indian languages while retaining tone, style, and contextual integrity in the target language.
AI Video Dubbing: Start with a video in any language. Studio generates high-fidelity dubs in the Indian language of your choice, preserving the speaker’s voice characteristics, intent, and emotional texture.
AI Video Dubbing
A video is uploaded, target languages are selected, and the platform handles transcription, speaker separation, translation, and speech generation. The dubbed voice retains the tone, pacing, and expressiveness of the original speaker, while translations adapt to the context of the content, whether a lecture, podcast, or monologue. Users can edit and regenerate segments directly within the interface, maintain precise audio-visual alignment, and export final outputs in publish-ready formats.
Our AI dubbing output was evaluated through a blind, side-by-side human study designed specifically to assess production-quality dubbing.
In real-world publishing, dubbing systems are not judged by isolated metrics. They are judged by how the final video feels. Does the voice sound natural? Does it resemble the original speaker? Does it remain aligned with the visuals throughout?
Evaluation Framework and Results
The study used a curated dataset of eight source videos spanning real-world categories, including creator content, educational lectures, informational case studies, advertisements, and sports commentary. The content covered multiple Indian languages and speaking styles.
Each source video was dubbed into ten Indian languages using Sarvam Studio and other leading AI dubbing platforms.
For each comparison, domain experts rated outputs across several quality dimensions, including:
- Speaker identity match
- Audio-visual sync
- Linguistic and cultural correctness
- Voice consistency
- Overall production preference
In total, the study involved approximately 280 head-to-head comparisons between Sarvam Studio and commercially available platforms such as ElevenLabs, YouTube Dub, Rask AI.
Highest Approval for Real-World Publishing
Across comparisons, Sarvam received the strongest overall viewer preference relative to other leading platforms. In a majority of pairwise evaluations, domain experts selected Sarvam’s dubbed outputs as the version they would approve for real-world publishing.
This outcome reflects more than isolated strengths. It reflects how the final video holds together as a complete experience.
The preference metric captures the holistic assessment made by evaluators. Voice quality, timing alignment, naturalness, and production readiness are not scored in isolation. They converge into a single decision about which version is ready to publish.
Sarvam emerged as the preferred choice in the final production-readiness judgment.
Preserving Speaker Identity
Speaker identity is what makes a voice feel like it belongs to a specific person. It is the rhythm of how they speak, the way they pause, the tone they carry, the energy behind certain words. When that shifts, the connection breakers.
Preserving that identity during dubbing is technically difficult, especially across languages where sentence structure, phonetics, and prosody change. The system must adapt to a new language without altering the essence of the original voice.
In our evaluation, Sarvam delivered the strongest speaker identity preservation across systems, achieving an average similarity score of 0.88, the highest observed in the study.
Across comparisons, Sarvam consistently scored higher on speaker similarity, particularly in cross-lingual scenarios.
For public communication, education, and creator-led content, this continuity matters. The audience should still feel like they are hearing the same person, even when the language changes.
Agentic Document Translation
Sarvam Studio adapts translations to the nature of the content, whether technical documentation, educational materials, policy texts, creative writing, or spiritual works. Tone, register, and cultural nuance are preserved so that translated documents read naturally for Indian audiences rather than as literal conversions. Legal documents retain formality and precision. Educational materials remain clear and pedagogically accurate. Literary works preserve voice. Public communication stays accessible.
Organizations can define custom glossaries, terminology, and style guidelines to ensure consistency across large document sets. Domain-specific language remains precise and aligned with institutional standards across all target languages.
Document structure is preserved throughout the process. Tables, headings, images, diagrams, and page hierarchy remain intact, allowing PDFs, textbooks, reports, and formatted publications to be translated without manual redesign.
Review and editing are built into the same environment with domain-specific AI agents. AI agents work alongside your team to refine translations. Request edits to specific sections, adjust tone or terminology on the fly, and regenerate content - while the AI maintains formatting integrity and applies your style guidelines consistently.
To evaluate document translation quality in Sarvam Studio, language experts conducted a comparative assessment against state-of-the-art language models and examined translation quality within the Studio environment.
Evaluation Framework and Results
The evaluation used a curated dataset of documents spanning multiple real-world categories, including Legal, Academic, Spiritual, Non-fiction, and Fiction, across several Indian languages. The objective was to validate the capabilities of the Document Translation solution in diverse and production-relevant contexts.
Each source document was translated using Sarvam Studio and leading state-of-the-art models, including Gemini 3 Pro, Claude Opus 4.5, and GPT-5.
To ensure an unbiased assessment, native speakers and domain experts evaluated outputs in a head-to-head format. Translations were rated on semantic accuracy, fluency, and adherence to Indian cultural context.
For each comparison, evaluators assessed both linguistic precision and practical usability metrics, including out-of-the-box readiness and the manual effort required to finalize a document for publishing.
The study compared Sarvam’s output against leading general-purpose models to determine how well translations perform in professional, high-volume workflows.
Leading in Reader Preference
Sarvam achieved the highest reader preference rate across evaluated platforms. In the majority of pairwise comparisons, evaluators selected Sarvam’s translations over alternatives, with 100 percent win rates in Tamil and Malayalam.
Across languages, Sarvam recorded the highest win rate in 8 out of 10 cases, outperforming Gemini Pro, Claude, and GPT-5.
The results indicate a stronger grasp of Indic syntax, idioms, and contextual nuance compared to other leading models in the study.
Consistent Quality Across Domains
Sarvam demonstrated the most consistent quality across complex domains, including academic, fiction, and legal content.
Across languages, Sarvam maintained an average quality score above 4.0 on a 5-point scale. By comparison, the strongest competing model, Gemini Pro, showed greater variance, with average scores ranging between 3.5 and 4.8 depending on language and domain.
More specifically, Sarvam achieved the highest performance across all six content categories, demonstrating consistent quality irrespective of domain complexity.
Translations were rated on a 5-point scale across six quality dimensions, including meaning preservation, readability, localization, terminology adherence, grammatical correctness, and publish readiness.
Scores were weighted to prioritize semantic accuracy and production readiness, ensuring the final metric reflects real-world publishing standards rather than literal translation alone.
This consistency extended to technically demanding domains such as Legal and Academic content, where precision and structural accuracy are critical.
Direct publish readiness measures the share of translated content that can be published as-is, without human edits. On this metric, Sarvam outperformed other leading language models by a clear margin.
For every kind of content team
NCERT and NPTEL: Educational Content at National Scale
NCERT and NPTEL produce foundational educational content for schools and higher education institutions across India. Making this material available in multiple Indian languages expands access for students who learn best in their mother tongue.
Educational content introduces a distinct set of challenges. Technical terminology must remain precise. The instructor’s authority and credibility must carry across languages. Explanations need to remain clear, structured, and pedagogically sound.
Original
NCERT Video Lectures (dubbed)
NAAV AI: Multilingual Book Publishing at Scale
NAAV AI uses Sarvam Studio services to extend the reach of published books across Indian languages while preserving literary quality, formatting integrity, and narrative voice.
In book publishing, translation is not a literal conversion of words. It requires carrying forward tone, rhythm, character voice, and cultural nuance across chapters, dialogue, and descriptive passages. Structural coherence must hold across the full arc of the work.
Original (English)
Sarvam’s agentic document translation has been a game changer for NAAV AI. We’re now translating books two to three times faster, without compromising on literary quality. It has unlocked true scale for our language experts and helped us bring multilingual editions to readers much faster.
-- Dr. Vikram Sampath, Co-founder, NAAV AI
National Commission for Women: Training and Public Communication at Scale
Public institutions such as the National Commission for Women use Sarvam Studio to deliver critical training and awareness content across Indian languages.
When communication concerns rights, safety, and access to services, clarity is essential. Language should not limit reach. Multilingual delivery ensures that information remains accessible to women across regions, without distortion or exclusion.
Prime Minister’s Office: Mann Ki Baat
Mann Ki Baat is the Prime Minister’s monthly address to the nation. Each episode is translated and dubbed into 11 Indian languages and distributed across official broadcast and digital channels.
Sarvam Studio supports this recurring dubbing workflow end to end, delivering broadcast-ready output each month. The output maintains speaker identity, tonal continuity, and natural prosody across all language versions, ensuring that each translation feels consistent with the original address.
Request early access
Sarvam Studio is currently live with a select group of partners. Access is now expanding to additional organizations working with large-scale multilingual content.
If your team produces video or document content across Indian languages and requires infrastructure that can support production use, we would be glad to connect.
Reach out for early access, partnerships, or technical discussions at studio@sarvam.ai.
Curious what else we're building? Explore our APIs and start creating.
Curious what else we're building?
Explore our APIs and start creating.