Intelligence,
thoughtfully built.

AI FROM INDIA. FOR THE WORLD.

An independent multimodal research studio. We build intelligent systems that perceive, understand, retrieve, reason, and interact with the physical and digital world.

80M Suzune Speech
120M Kaori Spatial OCR
100% Sovereign Studio
Royal Indian Heritage Palace Pavilion — Sorika Studio

Meet Sorise.

An autonomous agentic AI assistant equipped with multimodal reasoning, creation, and execution capabilities.

Designed for seamless creation.

A distraction-free, canvas-driven intelligence workspace. Multimodal reasoning, live sandboxes, and autonomous workflows in one unified view.

https://sorise.vercel.app
Sorise Workspace App full screenshot
Sorise Agentic Engine — Full-Stack Sandboxes & Multimodal ReasoningOpen Fullscreen Workspace
166/2000·33
LianMale
Conversational · Friendly
EliaFemale
News · Authoritative

Want to use this API?

Try Text to Speech

Frontier scientific research &
hybrid edge intelligence foundations.

Sorika is grounded in fundamental mathematical inquiry. Architected by Darsh Yadav, we engineer lightweight, ultra-fast neural models and publish open peer-grade technical reports.

Hybrid Gated ConvolutionsTest-Time Metacognitive Reasoning128k Native ContextLinear Complexity GQASub-15ms TTFTGSM8K 88.4%HumanEval 76.2%Non-Autoregressive TTSFast iSTFTNet VocoderO(1) Memory Footprint
PRIMARY REPORT #0021.17B HYBRID CONV-ATTENTIONSEPTEMBER 2026

Swen 1.1 Technical Report: Efficient Edge Intelligence via Hybrid Double-Gated Convolutions and Test-Time Metacognitive Reasoning

Darsh Yadav (Founder & Chief AI Architect) with the Sorika Labs Research Team

Engineered for sub-15ms time-to-first-token execution on consumer workstations and edge silicon. Formulates hybrid causal double-gated convolutions fused with linear grouped-query attention (GQA) and autonomous test-time metacognitive reasoning <think> scratchpads. Eliminates quadratic KV-cache memory explosion while outperforming traditional discrete models on HumanEval (66.0%) and GSM8K (54.0%) at 1.17B parameters with 128k native context.

Swen 1.1 Official TelemetrySORIKA-TR-2026-002
HumanEval Pass@166.0% 🥇
GSM8K (Math)54.0% 🥇
MultiArith (350M)85.0% 🥇
Time-to-First-Token<15ms
Context Window128,000
Parameters1.17B / 350M
Memory Footprint: O(1) Cache ~708MB - 2.3GB (Zero KV Cache Bottleneck)
Under Development