Hey, I'm Kai.
I specialize in architecting Agentic AI systems
and LLM-powered applications
to drive business impact.
Python
C++
Rust
Go
PyTorch
JAX
OpenAI
Hugging Face
NVIDIA
Anthropic
vLLM
DeepSpeed
ONNX
LangChain
LlamaIndexPythonC++RustGoPyTorchJAXOpenAIHugging FaceNVIDIAAnthropicvLLMDeepSpeedONNXLangChainLlamaIndex
Kafka
PostgreSQL
Kubernetes
Docker
Terraform
Neo4j
Redis
AWS
Prometheus
ClickHouse
Milvus
Pinecone
PySpark
Flink
ArgoCD
IstioKafkaPostgreSQLKubernetesDockerTerraformNeo4jRedisAWSPrometheusClickHouseMilvusPineconePySparkFlinkArgoCDIstioCUDA
FlashAttention-2
Triton
eBPF
gRPC
MQTT
OpenTelemetry
SNMP v3
NetFlow
OPC-UA
NETCONF
perf
SPARQLCUDAFlashAttention-2TritoneBPFgRPCMQTTOpenTelemetrySNMP v3NetFlowOPC-UANETCONFperfSPARQL
Selected works
23-25Proviz: Hyperpersonalised learning system powered by Adaptive AI
shipped
Astrix: Fullstack Observability and Autonomous Optimization Tool
shipped
Shared Success:
Stories of Impact
& Collaboration
Dilip Verma
CEO, Keyspark Technology Pvt. Ltd.
Kai's architectural approach to our network automation tool was game-changing. He didn't just build a tool; he designed a scalable ecosystem that reduced our manual overhead by 70%. His ability to bridge complex IT protocols with intuitive automation is rare.
Girija Sankar
CEO, Trainx Technology Pvt. Ltd.
Building a high-fidelity drone simulation environment required both physics-based precision and AI-driven adaptability. Kai delivered on both fronts, creating a robust runtime that has become the backbone of our training protocols.
Swaroop Singh
CEO, Alkapure
Kai's insights into operational optimization and GTM strategy were invaluable. He has a unique talent for translating technical AI capabilities into clear business value, helping us streamline our entire product launch cycle.
Raj
COO, JD Developer
Transitioning JD Developer to a fully digital, AI-integrated platform was a massive undertaking. Kai guided us through every step, ensuring our online presence is not just 'active' but intelligently automated to capture leads.
S Mantri
CTO, Gargi Automation
Work on our robotic arm control systems required extreme low-latency and precise computer vision. Kai's expertise in edge AI and real-time processing allowed us to hit our performance targets months ahead of schedule.
K.A. Venkatesh
Registrar, Alliance University
Kai's contributions to our research into quantum-classical hybrid models have been groundbreaking. His technical depth and ability to simplify complex quantum logic into functional neural architectures is truly impressive.
I don't follow a rigid framework, my process adapts to the problem, moving from understanding to shipping through collaboration
Research
Gaining an understanding of the problem and our customers, gathering relevant data and context
Problem definition
After getting more context, going a step further to properly frame the problem that I'm trying to solve
User journey mapping
Before getting into the design exploration, taking the time to map out the user journeys & stories
Design explorations
Exploring various possible design solutions and seeking feedback from relevant stakeholders
Usability testing
After settling on some design directions, carry out usability tests with users to test ease of use
Handoff and monitoring
Handing off all design-related assets to developers as well as monitoring relevant performance
Research & Experiments
Impact goes beyond the model. Exploring the frontiers of Agentic AI: from 1-bit quantization to quantum-classical hybrids and universal multimodal encodings.
1bit-LLM: Extreme Quantization
Implementing BitNet b1.58 for high-performance, low-cost LLM inference on edge devices.
Efficiency Frontier
A deep dive into ternary weights and the elimination of traditional multiplication in transformer blocks.
Q-Logic: Quantum Hybrid models
Merging qubit-based logic gates with classical neural architectures for complex reasoning.
Quantum Supremacy
Exploring how variational quantum circuits can provide exponential speedups for optimization tasks.
OmniSync: Universal Encoding
Propelling all data modalities into a single, unified latent space for seamless cross-domain reasoning.
The Unified Space
Architecting a shared encoding platform that treats text, vision, and audio as a single continuous signal.
Sparse-X: Infinite Context
Optimizing attention kernels to handle million-token context windows with linear scaling.
Linear Scaling
Implementing Flash-Attention-3 and sparse-matrix optimizations for long-range dependency modeling.
Neuro-Symbolic Reasoning
Combining LLMs with formal logic for zero-shot mathematical proofs and software verification.
Formal Proofs
Bridging the gap between neural intuition and symbolic rigor for high-stakes AI applications.
Agent-Zero: Recursive Loop
Developing autonomous agents that continuously self-optimize their own code and tool usage.
Self-Optimization
Architecting a feedback loop where agents learn to build their own tools and refine strategies.
Real-Time Latent Diffusion
Accelerating video generation to 60fps through optimized latent space denoisers.
Instant Vision
Leveraging TensorRT and custom CUDA kernels for sub-millisecond generation times.
Bio-Synthetic Synapses
Simulating biological synaptic plasticity in silicon to achieve extreme learning efficiency.
Synaptic Efficiency
Modeling Hebbian learning rules within standard neural network training frameworks.
Differentiable Search Index
Transforming Retrieval Augmented Generation (RAG) into internal model weight memory.
Neural Retrieval
Eliminating external databases by teaching models to navigate their own parameter space as an index.
Start a Conversation
No gatekeepers here just open channels. Whether you want to discuss the future of Agentic AI, book an AI strategy session, or simply critique my latest LLM fine-tuning, I'm always up for a chat.