Zero cost. Zero cloud. Zero GPU. NC includes NC AI — your own AI that runs locally on your CPU. $0/month, no API keys, no subscriptions, no cloud dependency. Describe what you want in plain English, get a complete NC application. Train in hours on your laptop, not months on GPU clusters. You own your AI.
Three steps from idea to running application.
Write what you want in plain English or hand it a spec document.
NC AI creates the backend, frontend, and test files automatically.
Working NC backend + NC UI frontend, ready to deploy.
Watch NC AI generate a complete application from a single sentence.
A complete pipeline from natural language to executable NC code.
Everything you need to generate NC applications, in one self-contained tool.
Purpose-built AI model integrated into the NC binary. Optimized for speed and accuracy. Hardware accelerated. Cross-platform.
Pure C11. No Python, no pip, no npm. Compiles anywhere a C compiler exists. Dead simple.
Connect to any AI provider, or run fully standalone. Your model, your rules.
Give it a spec document and get a complete project back: backend, frontend, tests, all wired together.
Train on your NC codebase with hardware acceleration on any platform. Checkpointing built in.
Fast generation, compact models, high-quality output, parallel processing.
Apache 2.0 license. Built by DevHeal Labs AI. Free to use, modify, and distribute — forever.
NC AI powers NC agents natively. Structured JSON tool-calling ({"action": "tool_name", "input": {...}}), Plan-Act-Observe conversation loop, trained on 40+ agentic tool-calling pairs.
NC AI can fetch data from the web for grounding. Real-time information retrieval via gather data from URL syntax. Ground your AI responses in live data.
Describe your app in plain English. The current v1 binary is validated to generate the full NC Lang + NC UI scaffold: backend, frontend, tests, docs, and a compiled frontend bundle.
# Validated on the current v1 release binary
$ nc ai create "multi-tenant operations dashboard with role based access analytics alert center approvals and dark theme"
NC AI — Creating Full Project (AI-Driven)
Engine: Built-in AI (loaded)
Features: dark-theme dashboard alerts
Created: service.nc — backend scaffold
Created: app.ncui — dark NC UI page scaffold
Created: test_app.nc — generated test scaffold
Created: README.md
Self-learn: saved to training corpus
Validation: generated files passed AI structural checks
Frontend: dist/app.html compiled successfully
$ nc serve service.nc
Server starts from the generated backend scaffold
One command produces the backend service, NC UI frontend, tests, README, and compiled frontend bundle that the current v1 binary can validate end to end.
Every project you create teaches the AI. Generated code is automatically added to the training corpus. The more you use it, the smarter it gets.
NC AI validates generated files against project contracts and repairs structural problems before the frontend bundle is built.
Complex prompts are accepted today. The current v1 binary reliably preserves the scaffold contract and high-signal features such as dashboard, dark theme, and alerts while deeper domain coverage keeps improving.
A logic-first reasoning engine built in NC. Classifies questions, builds step-by-step reasoning chains, and returns answers with confidence scores. Runs on your CPU at zero cost — structured reasoning, not token generation.
# Run the Reason AI demo
$ nc run nc-ai/reason-ai/reason.nc -b demo
Reason AI v2.0 — Demo
Q1: "If a train travels 60 km in 1 hour, how long for 180 km?"
Type: mathematical | Confidence: 0.85
Detected: travel/distance problem
Formula: time = distance / speed
Q2: "Why does the server crash at 90% memory?"
Type: debugging | Confidence: 0.80
Step 1: Identify symptom → Step 6: Verify fix
Q3: "Write a function that validates user input"
Type: code_generation | Confidence: 0.70
Parse requirements → Design → Implement → Self-review
6/6 questions classified & reasoned
Mathematical, causal, debugging, planning, comparison, code generation, and general reasoning — auto-detected from the question.
Every answer includes a full reasoning chain: parse question, identify knowns, apply strategy, verify answer. Transparent and auditable.
Each answer returns a confidence score (0.0 – 1.0). Mathematical: 0.85, debugging: 0.80, planning: 0.75. Know when to trust the answer.
POST /reason, POST /classify, GET /demo, GET /health. Run as a standalone microservice or embed in any NC project.
NC AI is the only tool that gives you full, local, NC-native intelligence.
| Feature | NC AI | Copilot | Cloud AI ($20/mo) | Tabnine |
|---|---|---|---|---|
| Runs offline | ✓ | ✕ | ✕ | ✕ |
| Own model | ✓ | ✕ | ✕ | ✕ |
| NC-native | ✓ | ✕ | ✕ | ✕ |
| Free forever ($0/month) | ✓ | $10/mo | $20/mo | $12/mo |
| Runs on CPU (no GPU) | ✓ | Cloud GPU | Cloud GPU | Cloud GPU |
| Model size | 20MB | Cloud | Cloud | Cloud |
| Full project generation | ✓ | ✕ | Partial | ✕ |
| Built-in reasoning engine | ✓ | ✕ | ✕ | ✕ |
| Confidence scoring | ✓ | ✕ | ✕ | ✕ |
| Knowledge graph | ✓ | ✕ | ✕ | ✕ |
| Decision engine (Q-learning) | ✓ | ✕ | ✕ | ✕ |
| Swarm intelligence | ✓ | ✕ | ✕ | ✕ |
| Energy-based scoring | ✓ | ✕ | ✕ | ✕ |
| Agentic AI (tool-calling) | ✓ | ✕ | ✕ | ✕ |
| Web data fetching | ✓ | ✕ | ✕ | ✕ |
Clone, build, generate. That's it.
# Install NC (includes AI engine)
$ curl -sSL https://raw.githubusercontent.com/nc-lang/nc/main/install.sh | bash
# Create your first full app
$ nc ai create "a todo app with auth and dark theme"
# Or generate a code snippet
$ nc ai generate "a REST API for users"
# Check AI status
$ nc ai status
NC AI can distill knowledge from any external model into its built-in 5M parameter model. After distillation, it works offline on your CPU — no API keys, no cloud, no recurring cost.
Send NC code prompts to any external teacher model. The teacher generates high-quality code. NC AI's student model trains on it and absorbs the teacher's patterns — then runs free on your CPU forever.
Once distilled, NC AI runs completely offline on any CPU. No API keys, no cloud, no internet, no GPU required. The knowledge is baked into the binary. Ship it anywhere — zero recurring cost.
Every project created with nc ai create feeds back into the training corpus. Every deployment teaches the model. It gets smarter with every use.
# Distill from any local AI server
$ nc ai distill --url http://localhost:11434/v1/chat/completions --model my-model
NC AI — Knowledge Distillation
Teacher: my-model | Prompts: 40
[1/40] Distilled: simple rest api for users (loss: 2.31)
[2/40] Distilled: todo app with login (loss: 1.87)
[3/40] Distilled: stock market app with predictions (loss: 1.54)
...
Distillation complete — 40/40 prompts
Model saved: nc_ai_model_distilled.bin
# Now NC AI works offline with distilled knowledge
$ nc ai create "blog with search" — no internet needed
NC AI is not a C program. It's an NC application. Only the inference engine is in C — everything else (generation, training, error-fix, review, export) is pure NC code. By DevHeal Labs AI.
AI-powered code review. Best practices, security checks, performance tips. Get a quality score for any NC file.
Validate and auto-fix NC code. Detects missing declarations, wrong syntax, and repairs them automatically.
Export your project as a standalone binary, Docker container, ZIP archive, or NC package. Ship to users instantly.
Logic-first reasoning engine. 7 types: mathematical, causal, debugging, planning, comparison, code generation. Step-by-step chains with confidence scores.
Self-learning AI that scans codebases, counts 94K+ patterns, detects query modes, and applies Hebbian learning from every interaction. Zero config.
# Review your code
$ nc ai review service.nc
[i] Add health_check endpoint
[i] Add middleware (cors, logging)
Code Quality Score: 85/100
# Auto-fix errors
$ nc ai check my-app/
Fixed: missing service declaration
Fixed: added api routes block
# Export for distribution
$ nc ai export my-app docker
Created: Dockerfile, docker-compose.yml
Run: docker compose up --build
Ten modules. One language. Complete operational intelligence from plain English.
Backend APIs in plain English. The simplest way to build servers, REST APIs, and microservices.
Frontend in plain English. Build complete dashboards, forms, and interactive UIs effortlessly.
Generates both, intelligently. Describe your app and get working backend + frontend code instantly.
Logic-first reasoning engine. 7 reasoning types, step-by-step chains, confidence scores. Runs on your CPU at $0 cost.
Neural Optimized Vector Architecture. Self-learning AI with knowledge graph and adaptive memory. 100% local inference on your CPU. Zero cost, zero cloud, zero GPU. You own your AI.
NC-native NC AI runtime. Full inference pipeline written in NC. Runs on any CPU — no GPU clusters needed. Manages model loading, tokenization, and generation natively.
Graph-based knowledge system. Connects concepts, traverses relationships, and scores reasoning paths. Learns from every query.
Classifies system states, evaluates actions by reward and risk, and learns the best response over time.
Multiple AI agents with different strategies vote on the best action. Agents evolve and improve from feedback.
Scores actions using energy minimization. Automatically balances exploration vs exploitation based on uncertainty.