Agentic AI · LLM Systems · Graph Analytics · C++ / Python
01 — 🧠 AgentWeave
Route before you reason.
Pre-inference routing and secure execution for tool-rich LLM and multi-agent systems. AgentWeave reduces the action space shown to a model before inference while keeping authorization, provenance and recovery explicit.
Project benchmark: 70.18% fewer tools exposed · 61.70% fewer input tokens · 50.95% lower mean local-model latency
MCP · A2A · LangGraph · AutoGen · Python
Repository · Project site · Paper
02 — ⚙️ MemVanta
Run quantized LLMs with less resident memory.
A memory-first C++20 runtime for quantized GGUF models on CPU, built around mmap-backed model access, paged KV cache, compact kernels and reproducible benchmarking.
7B benchmark: 3.80 GiB peak RSS · 47.54% lower peak RSS than the pinned comparison runtime
C++20 · GGUF · CPU Inference · Systems
Repository · Docs · Benchmark
03 — 🕸️ VeloGraphX
High-performance analytics for continuously evolving graphs.
A C++20 + Python engine for dynamic graph analytics with adaptive repair vs recomputation across BFS/SSSP, connected components, triangle counting, k-core and PageRank.
Retained exactness stress result: 2,000,000 updates · 0 BFS mismatches · 0 triangle mismatches
C++20 · Python · Dynamic Graphs · Graph Analytics · PyPI
Repository · Docs · PyPI
I try to make projects useful beyond a demo: benchmarks, reproducible evidence, tests, releases, documentation and explicit claim boundaries alongside the code.
If you work on agent systems, efficient inference, graph analytics or production ML, I’m happy to compare notes and collaborate.
Google Scholar · IEEE Xplore · ORCID · DBLP · OpenReview · ACM DL
Book: Machine Learning for Finance · Course: Data Analysis for Business and Finance · Technical writing: Towards Data Science, HackerNoon and KDnuggets
Research highlights · Research impact · Open-source contributions · Industry recognition
Follow @sauravsingla for new releases, benchmarks and open-source experiments.



