fast-litellm
Drop-in Rust acceleration for LiteLLM. Faster connection pooling, rate limiting, and dramatically lower memory use.
We help teams launch production AI, automate demanding workflows, and solve the integration, performance and control problems that hold delivery back.
Most enquiries fit one of four situations. Each leads to a defined first step with a published price, and sometimes to the honest answer that an existing product or no project is the better choice.
A prototype that cannot launch, or a pilot that is losing confidence. We define readiness, measure the gap and close it without rebuilding what works.
Production AI and project rescue ↗A recurring process that takes days, mostly waiting and re-keying. We connect the systems, validate early and measure the new turnaround.
Workflow automation ↗Latency or cost blocking growth, a missing connector delaying a contract, or a security review your AI system cannot yet pass.
Compare specialist routes ↗A hands-on AI engineer or architect inside your team for a defined term, with explicit ownership, priorities and a planned handover.
Embedded AI engineering ↗Anonymised, client-approved results from Neul Labs engagements. Each figure is elapsed turnaround, measured the same way before and after the change.
All case studies ↗48 hours → 40 minutes
How automated input collection and validation cut payroll preparation turnaround from 48 hours to 40 minutes for a UK employer with 250–1,000 staff.
Read the case study ↗ An independent animation studio with under 50 staff20 days → 1 week
Connecting production tracking and tools cut workflow turnaround from 20 days to one week for an independent animation studio with under 50 staff.
Read the case study ↗Every engagement has a defined deliverable and a price you can see before the first call. Uncertain problems start with a review; well-defined ones are quoted directly as a sprint.
Compare engagements and pricingIs this viable, and what is stopping it? Findings, a baseline and acceptance criteria in 1–2 weeks.
Can you fix or deliver this particular boundary? Working code, tests and measured results in 2–6 weeks.
Can you own this defined system outcome? A deployed, accepted system, staffed only with capacity we can commit.
Can you maintain the system and help us improve it? Upgrades, evaluation runs and reserved change capacity, scoped to what we can genuinely cover.
Neul Labs publishes its own infrastructure in the open. It shows how we engineer. It is not a client case study, and you never have to adopt it to work with us.
View the complete catalogue ↗Drop-in Rust acceleration for LiteLLM. Faster connection pooling, rate limiting, and dramatically lower memory use.
Multi-agent harness for AI coding tools. Crash-safe state, parallel execution, one CLI.
Give your AI agents database access without the risk. Policy-enforced ORM tools for Python and TypeScript.
10–100× faster, Rust-based drop-in replacement for Homebrew.
This site is the hub. Each catalogue entry publishes its own
marketing site at <project>.neullabs.com, its
reference documentation under docs.neullabs.com, and
its source in the neul-labs GitHub organisation. The
table below is the full map, so a reader — or a retrieval engine —
can get from this page to any project in one hop.
Drop-in Rust replacements that speed up the Python AI libraries you already use.
| Project | Language | Use it to | Project site |
|---|---|---|---|
| fast-litellm | Rust + Python | speed up LiteLLM without changing your code | fast-litellm.neullabs.com |
| fast-langgraph | Rust + Python | accelerate LangGraph checkpoints and state | fast-langgraph.neullabs.com |
| fast-crewai | Rust + Python | make an existing CrewAI crew faster | fast-crewai.neullabs.com |
| fast-axolotl | Rust + Python | fix Axolotl data-loading RAM/OOM at scale | fast-axolotl.neullabs.com |
| agentmatic | Rust + Python | run LangGraph-style agents on a Rust engine (source status pending) | agentmatic.neullabs.com |
The runtime layer agents need: orchestration, memory, sandboxes, data access, payments, governance.
| Project | Language | Use it to | Project site |
|---|---|---|---|
| brat | Rust | run several coding agents in parallel, safely | brat.neullabs.com |
| fastagentic | Python | ship a local agent to production as an API | fastagentic.neullabs.com |
| fastworker | Python | run a task queue without Redis or RabbitMQ | fastworker.neullabs.com |
| m9m | Go | automate workflows from one Go binary | m9m.neullabs.com |
| ringlet | Rust | manage many coding-agent CLIs and their costs | ringlet.neullabs.com |
| ormai | Python | let an agent query a database, safely | ormai.neullabs.com |
| mcp-pay | Rust | charge for MCP tools across payment rails | mcp-pay.neullabs.com |
| memorg | Python | add durable memory to an LLM chat app | memorg.neullabs.com |
| agentvfs | Rust | sandbox an agent’s files and shell | agentvfs.neullabs.com |
| openclawOS | TypeScript | self-host a multi-channel agent gateway | openclawos.neullabs.com |
| openclawMU | TypeScript | share one agent gateway across tenants | openclawmu.neullabs.com |
| openclaw-rs | Rust | embed a fast, sandboxed OpenClaw runtime | openclaw-rs.neullabs.com |
| stratafs | TypeScript | make your files an AI-searchable knowledge base | stratafs.neullabs.com |
| regulus | Java | make a Google ADK agent regulator-ready | regulus.neullabs.com |
| closegate | Python | gate finance agents behind approval policy | closegate.neullabs.com |
Frameworks for building agents — on the phone, in the browser, in a C ABI, or on a governed desk.
| Project | Language | Use it to | Project site |
|---|---|---|---|
| agentlib | Dart | build AI agents inside a Flutter app (source status pending) | agentlib.neullabs.com |
| linda | TypeScript | run AI agents in the browser (source status pending) | linda.neullabs.com |
| onto | TypeScript | build agents with humans driving the state (source status pending) | onto.neullabs.com |
| tokenworm | Zig | embed a tiny native agent via a C ABI (source status pending) | tokenworm.neullabs.com |
| BondFoundry | Python | run a governed AI assistant on a bond desk (source status pending) | bondfoundry.neullabs.com |
| ukkin | Dart | automate phone tasks with an on-device agent | ukkin.neullabs.com |
Faster tests, builds, git, packaging and networking for agent-era engineering.
| Project | Language | Use it to | Project site |
|---|---|---|---|
| rjest | Rust | run your Jest suite far faster, unchanged | rjest.neullabs.com |
| rpytest | Rust | cut pytest startup and collection overhead | rpytest.neullabs.com |
| gity | Rust | make a huge git monorepo feel instant | gity.neullabs.com |
| grite | Rust | track issues in-repo with no server | grite.neullabs.com |
| skillterm | Rust | get AI-generated help at your shell Tab key (source status pending) | skillterm.neullabs.com |
| rninja | Rust | cut warm Ninja/CMake build times | rninja.neullabs.com |
| stout | Rust | install Homebrew packages, much faster | stout.neullabs.com |
| stkd | Rust | manage stacked pull requests on GitHub/GitLab | stkd.neullabs.com |
| recurl | Rust | fix curl 403s without rewriting anything | recurl.neullabs.com |
| rewget | Rust | download from sites that block wget | rewget.neullabs.com |
Source status is audited separately from the catalogue. Seven entries — agentmatic, agentlib, linda, onto, tokenworm, BondFoundry, skillterm — had a configured source URL that did not resolve at the last audit, so their repository link is withheld until it is restored or the entry is revised. Their project sites and catalogue records remain published, and every benchmark claim on this network is workload- and version-specific: the linked method is the authority, not the headline number.
For consultancies and platform vendors with a named customer engagement: integrations, production hardening, evaluation and performance work, delivered with explicit acceptance and handover.
Tell us what has to work, what is failing today and what evidence would make the next decision easier.
Start with the problemNeul Labs helps teams put AI into production, automate demanding workflows, and fix the performance, integration and control problems that block adoption. Work is sold as bounded engagements — fixed-fee reviews, fixed-scope sprints, delivery projects, embedded engineering and ongoing support.
Yes. An engagement begins with the existing workflow, stack and failure cases. The first step is to establish a baseline and identify the limiting components; the implementation then targets those components, with agreed tests, rollback and handover requirements.
Indicatively, a readiness or feasibility review is £3,000–£6,000 and a focused engineering sprint is £15,000–£35,000, excluding VAT where applicable. Larger delivery projects are quoted after discovery. The fee for each engagement is fixed in writing.
No. The open-source work is evidence of how we engineer and a set of options to assess on their merits. Many engagements use none of it, and the best answer is sometimes an existing platform, a small integration or no project at all.
Neul Labs Limited is registered in Scotland (SC767862) and works remotely with organisations in the United Kingdom and internationally.
No. Neul Labs Limited is a UK software engineering company. Neuland Laboratories Ltd. is a separate Indian pharmaceutical manufacturer. The two companies have no connection.