Building the performance layer for the AI agent economy

Neul Labs is a UK-based infrastructure company building Rust-accelerated tooling for AI agents. We identify the bottlenecks in production AI systems and ship drop-in replacements that are orders of magnitude faster.

Our Thesis

The AI industry is moving from chatbots to autonomous agents. These agents need to call APIs, manage state, checkpoint progress, coordinate with other agents, and interact with databases — all at production scale.

The Python libraries powering this stack were never designed for production concurrency. LiteLLM's connection pooling, LangGraph's checkpointing, CrewAI's serialization — they all become bottlenecks under real workloads.

We fix this by profiling these libraries, isolating the hot paths, and rewriting them in Rust using PyO3. The result: drop-in replacements that deliver 3x to 700x speedups with zero code changes.

Our Approach

1

Profile

Identify performance bottlenecks in widely-used Python AI libraries using production workload profiles.

2

Rewrite in Rust

Rebuild hot paths using Rust and PyO3 for zero-overhead Python interop with thread-safe, lock-free data structures.

3

Ship as Drop-In

Package as pip-installable wheels with prebuilt binaries. One import, no config, no code changes.

4

Expand the Stack

From accelerators, expand into orchestration (brat), workflows (m9m), and data access (ormai) — the full agent infrastructure layer.

Open Source First

All 23+ projects are MIT licensed. We believe open source is the fastest path to adoption, the best way to build trust, and the right foundation for enterprise relationships.

Zero CAC

Open source drives organic adoption. Developers discover us through GitHub, PyPI, and word of mouth.

Battle-Tested

Community usage surfaces edge cases faster than any QA team. Every bug report makes the product better.

Trust by Default

Enterprises can audit every line. Security teams can verify claims. The code speaks for itself.

Ecosystem Gravity

Each project strengthens the ecosystem. Users of fast-litellm discover brat. Users of brat discover ormai.

Contribution Pipeline

Open contributions attract Rust+AI talent. Contributors become advocates. Advocates become customers.

Enterprise Path

Open core model: MIT foundation with enterprise features for teams that need SLAs, support, and managed deployments.

Technology Stack

Rust

Core performance engine. Memory safety, zero-cost abstractions, fearless concurrency.

Python

PyO3 integration layer. Seamless interop with the AI ecosystem.

Go

Workflow automation. Single-binary deployments, native concurrency.

PyO3

The bridge. Zero-overhead Rust-Python bindings for drop-in compatibility.

For Investors

Market Opportunity

The AI agent market is projected to grow to $47B by 2030. Every AI company building agents needs infrastructure that works at scale. We're building the performance layer that makes production AI viable — the picks and shovels of the agent economy.

Competitive Moat

Deep Rust+PyO3 expertise at the intersection of systems programming and AI infrastructure is exceptionally rare. Our approach of profiling real production workloads and shipping verified benchmarks creates compounding technical advantages that are difficult to replicate.

Business Model

Open-core model: MIT-licensed foundations drive adoption, with enterprise tiers offering managed deployments, SLA-backed support, advanced monitoring, and team features. The transition from open-source user to paying customer is seamless.

Traction

23+ public repositories across the full agent infrastructure stack. Active GitHub community. Verified benchmarks showing 3x to 700x improvements. Growing adoption across the LangGraph, LiteLLM, and CrewAI ecosystems.

Get in Touch

Interested in investing, partnering, or contributing? We'd love to hear from you.