Building Next-Gen Autonomous AI & Multi-Agent Swarms
AKWebs is actively developing hardware-accelerated intelligence: proprietary multi-agent orchestration, ultra-low latency RAG pipelines, and deterministic enterprise AI workflows.
Preview the NeuroFlow Multi-Agent Engine
Explore a simulation of our autonomous multi-agent architecture currently under development. See how specialized agent nodes are designed to collaborate, traverse RAG indices, and synthesize outputs.
24/7 JEE/NEET AI Doubt Solver Swarm
"A solid cylinder of mass M and radius R rolls without slipping down an incline of angle θ. Derive the acceleration of the center of mass in LaTeX, verify with torque about contact point, and generate 2 follow-up practice numericals."
Decomposed problem into constraint kinematics, torque about instantaneous axis, and LaTeX synthesis.
Retrieved NCERT Class 11 Physics Ch 7 (Rotational Motion) and cross-referenced JEE Advanced 2022 Paper 1.
Derived a_{cm} = (2/3)g sin(θ). Identified student common pitfall: misidentifying torque about center vs contact point.
Audited against official JEE Advanced syllabus. Verified 100% mathematical consistency without hallucinations.
Autonomous Intelligence Platforms
We are engineering scalable, GPU-accelerated software platforms designed for mission-critical enterprise workflows.
NeuroFlow AgentOS (EdTech Edition)
Currently in active development: An autonomous academic execution runtime that coordinates Socratic doubt-solving agents, LaTeX mathematical derivers, and pedagogy auditors with sub-20ms latency for coaching institutes.
NexusRAG Curriculum Engine
Architecture in development: Combining dense vector embeddings and hierarchical knowledge graphs of NCERT textbooks, JEE/NEET PYQs, and institute module booklets with zero out-of-syllabus hallucination.
VisionPulse Multimodal OCR
Model pipeline in development: High-throughput optical vision models trained to parse mobile photos of student notebook pages, complex circuit diagrams, and organic chemistry mechanisms with error localization.
AgentOps Curriculum Guardrails
Tooling in development: Strict guardrail runtime enforcing NTA / JEE / NEET syllabus boundaries, ensuring AI tutors never answer with confusing out-of-scope concepts or incorrect mathematical shortcuts.
Hardware-Aware AI Optimization
AKWebs architectures are optimized down to the bare-metal GPU layer. By leveraging NVIDIA NIM microservices, TensorRT-LLM compilation, and custom CUDA pipelines, our platforms deliver up to 4x higher token throughput with predictable sub-second latency.
NVIDIA TensorRT-LLM & CUDA
Low-level FP8/INT4 kernel optimizations and custom CUDA memory allocators reducing inference latency by up to 4.2x.
NVIDIA NIM Microservices
Containerized, enterprise-grade model endpoints deployed seamlessly on AWS GPU instances with auto-scaling elasticity.
NeMo Guardrails & Zero-Trust
Deterministic safety filters intercepting prompt injections, jailbreaks, and sensitive data exfiltration in real-time.
Multi-Agent Consensus Protocol
Decentralized state-machine enabling fault-tolerant voting and multi-round verification between specialized agent nodes.
The Enterprise AI Blueprint
From proprietary data ingestion to containerized GPU deployment, our pipeline enforces mathematical rigor at every stage.
Domain Vectorization
Ingestion of enterprise data into hybrid vector-graph indices with contextual chunking and dense embeddings.
Agent Swarm Topology
Configuring multi-agent roles, tool capabilities, and consensus logic for specialized business workflows.
Hardware Compilation
Quantizing weights and compiling models via TensorRT-LLM and NVIDIA NIM for optimal GPU utilization.
Guardrail Validation
Integrating NeMo safety policies, real-time observability telemetry, and zero-trust audit trails.
Engineering AI for EdTech & Coaching Giants
Founded and led by Anil Kumar Jangid in Kota, Rajasthan, AKWebs is building specialized AI infrastructure to solve the massive real-time doubt resolution, test generation, and optical grading bottlenecks for national coaching institutions like Allen Career Institute, Physics Wallah (PW), and Motion Education.
Join the Development Waitlist
We are actively developing our platform and working with select early design partners. Submit your technical brief to request early access or participate in our private alpha.