dipankar - Overview

Dipankar Sarkar

Builder · Systems Architect · OSS Researcher

I build high-performance infrastructure tools in Rust and Zig, with a focus on developer tooling, AI agent infrastructure, and blockchain systems. Based in Scotland, I work across three open-source organisations shipping production-grade tools that replace slow incumbents with fast, correct alternatives.

🌐 dipankar.name · 📧 me@dipankar.name · 🐦 @dipankarsarkar · 📚 Publications


Organisations

🔬 Neul Labs — Agent-Focused AI Infrastructure

Neul Labs is where I concentrate my work on high-performance tooling for AI agents and LLM-powered applications. The thesis is simple: the Python-native AI stack is too slow for production agent workloads. These tools provide Rust-accelerated drop-in replacements and novel orchestration primitives for the agentic AI ecosystem.

Tool What it does Lang
brat Multi-agent harness for AI coding tools — crash-safe state, parallel execution, one CLI. Orchestrates Claude, Aider, OpenCode, Codex, and others. Rust
fast-litellm Rust-accelerated drop-in replacement for LiteLLM. 3.2× faster connection pooling via PyO3 with zero config. Rust/Python
fast-langgraph Rust accelerators for LangGraph — up to 700× faster checkpoint operations and 10–50× faster state management. Rust/Python
gity Makes large Git repos feel instant. Daemon-based fsmonitor + warm caching turns 8s git status into milliseconds. Rust
stout Drop-in Homebrew CLI replacement, 10–100× faster. SQLite FTS5 index, parallel downloads, Ed25519 signed updates, CVE auditing. Rust
fastworker Background workers for Python apps in seconds, without the complexity. Python

Why this matters for agents: As AI agents move from demo to production, they need infrastructure that can handle thousands of concurrent LLM calls, checkpoint complex multi-step workflows without losing state, and orchestrate multiple coding engines in parallel. Neul Labs tools are the plumbing that makes this possible — Rust where it counts, Python where it's convenient.


🧪 Skelf Research — Systems Research & Developer Tools

Skelf Research is the broader research org, building tools across systems programming, quantitative finance, AI/ML, and constraint solving.

Tool What it does Lang
sigc The Quant's Compiler — from alpha idea to production trading strategy in minutes. Rust
numaperf NUMA-first runtime for latency-critical Rust applications. Rust
fastC C, but safe and agent-friendly. Rust
polymathy Rust web service transforming traditional search into an answer engine. Rust
zviz Container isolation for code you can't trust but have to run. Zig
route-switch Intelligent LLM routing with automatic prompt optimisation. Go
promptel Declarative prompt engineering — write once, run anywhere. JavaScript
blogus Extract prompts from your codebase, version them like dependencies, keep everything in sync. Python
savanty Natural language to constraint solver — describe optimisation problems in English, get mathematically guaranteed solutions. Python
compere Intelligent pairwise comparisons — better rankings with fewer votes. Python
mullama Drop-in Ollama replacement. All-in-one local LLM toolkit. Python
llamafu Run AI models directly on mobile devices. No cloud, no latency, complete privacy. Dart
liath A programmable database that speaks Lua. Store data, run queries, build AI workflows. Lua

⛓️ Cryptuon Research — Blockchain Infrastructure & Protocols

Research-driven blockchain tooling, from smart contract compilers to cross-chain protocols. Our paper "Towards Universal Atomic Composability" was recognised by a16z's crypto startup school.

Tool What it does Lang
solscript Write Solidity, deploy to Solana. Transpiler with full Anchor compatibility — no Rust required. Rust
zig-evm Experimental EVM implementation in Zig. Zig
stxscript StxScript-to-Clarity transpiler for Stacks smart contract development. Python
tesseract Multi-rollup environments on Ethereum — enabling atomic transactions across rollups.

What I'm Building Towards

The common thread across all three orgs is making fast, correct infrastructure for the next generation of software — whether that's AI agents that need sub-millisecond checkpoint recovery, quant strategies that need NUMA-aware execution, or cross-chain transactions that need formal correctness guarantees.

My current focus at Neul Labs is on the agent infrastructure layer: the tools that sit between LLM providers and production applications, making agentic workflows fast, observable, and crash-safe.


Background

  • M.S. Computer Science, Arizona State University · B.Tech, IIT Delhi
  • Author of Nginx 1 Web Server Implementation Cookbook (Packt)
  • Running Neul Labs · St Andrews, Scotland

Open to research collaborations, advisory roles, and conversations about high-performance AI infrastructure.