Now in Early Access

Your custom AI model,
built end-to-end

Describe what you need. We research, design, build, validate, and document your AI model — automatically.

See How It Works
AI Designer — end-to-end AI model pipeline

Trusted by researchers and engineers at

DeepMind
Stanford AI
Meta FAIR
OpenAI
MIT CSAIL
NVIDIA Research

End-to-End AI Pipeline

Five specialized AI agents work in sequence to deliver a complete, production-ready AI model from a single description.

🔍Stage 1
Research

Understands your use case and surveys the latest techniques across the field

🧠Stage 2
Model Design

Architects a novel model tailored to your specific problem and constraints

💻Stage 3
Code Generation

Writes clean, production-ready PyTorch code with shape annotations and safety

✅Stage 4
Code Validation

Tests, debugs, and benchmarks the implementation with rigorous test suites

📄Stage 5
Documentation

Delivers full technical docs, API references, and usage guides

Everything you need to build AI

From literature review to production deployment — every step is handled with precision.

Custom Architecture Design

Novel model architectures tailored to your specific requirements — not off-the-shelf fine-tuning.

Automated Research Pipeline

Surveys the latest papers, identifies novelty gaps, and recommends the best approach for your problem.

Production-Ready Code

Clean PyTorch with shape comments, bf16 safety, torch.compile compatibility, and smoke tests included.

Rigorous Validation & Testing

Comprehensive pytest suites covering shapes, gradients, causality, numerics, plus synthetic benchmarks.

Full Technical Documentation

README, architecture docs, training guides, benchmark reports, and API references — all generated.

Continuous Model Improvement

Iterate on your model with ablation studies, profiling results, and actionable optimization suggestions.

How It Works

From idea to implementation in three simple steps.

1

Describe your problem

Tell us what you need — a linear-time language model, a vision transformer variant, an efficient SSM hybrid. Natural language is all it takes.

2

AI Designer builds your model

Five specialized agents research the literature, design the architecture, write the code, run validation tests, and generate documentation.

3

Receive code, validation & docs

Download a complete project: production-ready PyTorch model, comprehensive test suites, benchmark results, and full technical documentation.

What researchers are saying

“AI Designer turned what would have been 3 weeks of literature review and prototyping into a 2-hour pipeline run. The generated model outperformed our hand-crafted baseline.”

SC

Dr. Sarah Chen

ML Research Lead, Stanford

“The validation suite alone saved us countless debugging hours. Shape tests, gradient checks, causality verification — all generated automatically with the model.”

MR

Marcus Rivera

Senior ML Engineer, Series B Startup

“We use AI Designer for rapid architecture exploration in our research group. The documentation quality is remarkable — grounded claims, reproduce commands, everything.”

YT

Prof. Yuki Tanaka

AI Lab Director, University of Tokyo

Simple, transparent pricing

Start free, scale as you grow. No hidden fees.

Explorer

Perfect for individual researchers and students

$49/model
  • 3 model builds per month
  • Basic architecture families
  • Standard validation suite
  • Generated documentation
  • Community support
Professional
Most Popular

For teams building production AI systems

$199/month
  • Unlimited model builds
  • All architecture families
  • Full validation + benchmarks
  • Ablation runner & profiler
  • Priority support
  • Custom constraints & configs
Enterprise

For organizations with advanced needs

Custom
  • Everything in Professional
  • Dedicated infrastructure
  • Custom skill development
  • On-premise deployment
  • SLA & dedicated support
  • SSO & team management

Frequently asked questions

How AI Designer compares, what it produces, and how it works.

AI Designer is a multi-agent pipeline that takes a natural-language research goal and produces a complete, runnable machine learning system. It covers 8 domains: Language Models, Computer Vision, Reinforcement Learning, Generative AI, Graph ML, Time Series, Speech/Audio, and Scientific ML. The output is a downloadable ZIP containing literature synthesis, an architecture blueprint, production-ready PyTorch code, a full pytest suite, and publication-grade documentation — all in one automated run.

Ready to build your
AI model?

Join researchers and engineers who are building custom AI architectures in hours, not weeks.