The story behind Vyasa
Most models activate their entire network for every token. Vyasa is different: a Mixture-of-Experts architecture routes each token only to the expert networks that are relevant—so you get the capacity of a far larger model while paying for a fraction of the compute.
Vyasa ships in two tiers. Flash is tuned for speed: sub-100ms first tokens, high throughput, and ideal for real-time assistants, agents, and high-volume workloads. Pro spends the compute budget on depth: longer reasoning chains, stronger math and code, and more reliable answers on the problems that matter most.
Both tiers expose a single, clean OpenAI-compatible API—so your application can choose Flash or Pro per request and switch the moment the task changes its mind about what matters: latency or depth.
Outcomes that compound
The measurable difference Vyasa makes to your operations.
Frontier quality, sparse compute
MoE routing delivers large-model intelligence while activating only a fraction of the network per token.
Pick your trade-off
Flash when latency rules, Pro when depth matters—both through one API, switchable per request.
Cost that scales with you
Efficient serving keeps cost per token low, so you can ship AI at real scale.
From input to insight
Connect
Create an API key and point your app at the Vyasa endpoint—OpenAI-compatible, so existing clients work as-is.
Compose
Send a request with the model set to vyasa-flash or vyasa-pro; Vyasa routes each token through the right experts.
Act
Stream the response into your app, or batch high-volume workloads at a fraction of the cost of dense models.
Backed by the Nexelligence engine
The infrastructure Vyasa runs on, at scale.
Active Agents
Data Volume
Decision Speed
System Uptime
Core Capabilities
Everything Vyasa brings to your workflow.
Mixture-of-Experts Architecture
Sparse expert routing activates only the relevant subnetworks per token, delivering large-model quality at a fraction of the compute.
Vyasa Flash Tier
Sub-100ms first-token latency and high throughput, tuned for real-time, agentic, and high-volume workloads.
Vyasa Pro Tier
Deeper reasoning chains with stronger math, code, and long-context performance for the problems that demand depth.
Unified API, Either Tier
One OpenAI-compatible endpoint; select vyasa-flash or vyasa-pro per request and switch as the task demands.
Long-Context Mastery
Handles very long documents and conversations with coherent, grounded reasoning across the full window.
Tool Use & Structured Output
Heavily tuned for function calling, structured JSON, and multi-step agentic reasoning.
Streaming & Batch Support
Stream tokens in real time or run high-throughput batch jobs with per-request tier selection.
Efficient Serving at Scale
Shared, optimized inference keeps cost per token low, so quality no longer has to mean a big bill.
AI Technologies
The models and methods powering Vyasa.
Where Vyasa shines
Real-Time Assistants
Power chatbots and voice agents with Flash's sub-100ms first-token latency.
Deep Reasoning Tasks
Tackle hard math, code, and analysis problems with Pro's extended reasoning chains.
High-Volume AI Apps
Serve millions of requests at a low cost per token with efficient MoE inference.
Built for your world
Where Vyasa fits across teams and industries.
Trust, by default
Enterprise-grade protections built into every Vyasa deployment.
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The expertise behind Vyasa, available as engagements.
Agentic AI
We build goal-oriented autonomous agents that reason, plan, and execute complex workflows with minimal human intervention. From customer assistant chatbots that resolve real issues to research assistants that synthesize knowledge across your enterprise—our agents don't just chat, they act.
Retrieval Augmented Generation (RAG)
Ground your AI responses in your own data. We architect RAG pipelines that combine the fluency of large language models with the accuracy of your documents, databases, and knowledge sources—eliminating hallucinations and ensuring every answer is sourced and verifiable.
Natural Language Processing (NLP)
Deploy language intelligence that understands context, sentiment, and intent across your organization. From multilingual text analysis to intelligent search and entity extraction, our NLP systems transform unstructured language into structured, actionable insight.
Questions, answered
What is a Mixture-of-Experts model?
MoE models route each token to only the expert subnetworks that are relevant, activating a fraction of the total network—so you get large-model capability at a fraction of the compute cost.
When should I use Flash vs Pro?
Flash is tuned for speed and throughput—ideal for real-time assistants and high-volume workloads. Pro spends more compute on reasoning depth—best for hard math, code, and analysis.
Is the API OpenAI-compatible?
Yes. Point your existing OpenAI client at the Vyasa endpoint and select vyasa-flash or vyasa-pro per request.
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