Data Extraction
001They train on your code.
Every prompt. Every file. Every fix. It flows through infrastructure you don't control, improving systems they want to use to replace you.
CleonlabOn-device AI coding.
No cloud. No limits.
A complete coding agent that executes entirely on your machine. No API calls. No usage caps.
Your hardware, your rulesNo tokens, no limitsSpecialized SLMUnbounded contextZero telemetryNative inference100% offlineYour hardware, your rulesNo tokens, no limitsSpecialized SLMUnbounded contextZero telemetryNative inference100% offline
The Problem
You don't own your AI.
And you're being watched.
Monitoring active
Artificial Scarcity
002They meter your ambition.
Slowdowns, overages, caps. Right when you're deep in a sprint, the meter decides you've had enough.
Silent Downgrades
003They change the model.
They silently downgrade to cheaper models during peak load. Full price, degraded experience.
Cloud Dependency
004They control your flow.
Every completion makes a round trip across the internet. Thousands of tiny interruptions, every single day.
Introducing RIG
Everything local.
Own your AI.
A complete AI coding agent running entirely on your own hardware. No usage limits. No cloud dependency.
Cloud
Your Machine
Your Code
Keystrokes · Files
RIG
Local Inference
GPUIndexModel
Response
<300ms · On Device
Telemetry
Cloud Servers
Severed
Your Machine
RIG Model Active
Severed
Nothing Leaves
Offline
Work offline
Flights. Spotty Wi-Fi. Network outages. Nothing stops your flow.
Unlimited
Remove the meter
Refactor the whole codebase. Riff on an idea all day. Run agent loops without thinking about cost.
Privacy
Sever the connection
Your code, keystrokes, and files never leave your machine. Not anonymized. Not aggregated. Not sent.
Latency
Stop waiting
No round-trip to a data center. Inference happens on your machine, in single-digit milliseconds.
Our Approach
Purpose beats scale.
Rig is a closed system, model, context, tools, and inference, engineered together for one job: real coding work.
Step 01
A focused model, trained specifically for coding.
Step 02
Full intelligence, compressed to fit your machine.
The model is compressed to run efficiently on consumer machines, carefully preserving the reasoning patterns that matter most.
The result is an 8 GB model that fits comfortably in memory on a MacBook. Full reasoning. Local execution. Zero cost per token.
Step 03
A custom runtime, engineered for Apple Silicon.
Model Size
Model size (memory required)
Cloud models200+ GB
Open source28-140 GB
Rig8 GB
Fits in 16 GB unified memory.
Accuracy loss: <0.3%
Capabilities
Your machine, unleashed.
[ 01 ]
Understands your architecture.
Builds a connected model of modules, dependencies, and relationships so reasoning happens across files and aligns with your architecture.
[ 02 ]
Tracks relationships, prevents breakage.
Edits that respect function contracts, type boundaries, and dependency graphs, reducing bugs and regressions.
[ 03 ]
Strategizes before acting.
Explore -> Plan -> Execute workflows ensure multiple steps are reasoned out before changes occur.
[ 04 ]
Executes complex coding workflows.
From refactors to test generation to feature builds, coordinate tools, code edits, web search, and commands as needed.
[ 05 ]
Isolates agent sandboxes.
Each agent runs in its own workspace so experiments are safe, parallel workflows don't clash, and code changes stay isolated until you merge them.
[ 06 ]
Runs at full speed.
Custom Rust inference engine optimized for CUDA and Metal, delivering up to 144 tokens per second on consumer hardware.
Latency
0ms
No round-trip required
Privacy
100%
Air-gapped by design
Cost / Token
$0
Your GPU, your tokens
Uptime
Local
No dependency on cloud
Engineered Intelligence
Built for control freaks
Custom Model
Optimized for consumer hardware
Inference
Cross-OS using Rust
Context Graph
Repo-wide code understanding
Terminal UI
Built in Rust and blazing fast
Heavily Tuned
Consistent tool calls and plan use
Opinionated
Focused on code correctness
rig://localhost · offline
λ rig init
RIG
> Scanning hardware...
> Found M4 · 16GB RAM
> Loading RIG Model OK
> Indexing 2,418 files · 87,102 symbols
✓ Ready. Network OFF Telemetry OFF
λ find the memory
Neural EngineRG-800Local Ops
Custom Model
Optimized for consumer hardware
Inference
Cross-OS using Rust
Context Graph
Repo-wide code understanding
Terminal UI
Built in Rust and blazing fast
Heavily Tuned
Consistent tool calls and plan use
Opinionated
Focused on code correctness
Early Access
Rig is almost ready.
We're inviting engineers to run it on real code and help shape what ships.