Compare AI tools

	Figma AI A	GitHub Copilot B	NeuralSet A	Devin A
Tagline	AI features baked into the design tool you already use.	Microsoft/GitHub's autocomplete. Deep VS Code + JetBrains integration.	Meta FAIR's open-source Python library that finally bridges the gap between neuroimaging data (fMRI, EEG, spikes) and modern deep learning pipelines.	Cognition Labs' autonomous coding engineer.
Category	Design	Coding	Research	Agents
Pricing	Included with Figma plans	Free (limited) + $10/mo Pro + $19/mo Business	Free (MIT open source)	$500/mo
Best for	Designers already on Figma.	Teams with GitHub already. Devs who don't want to change IDEs.	Computational neuroscience researchers who want to train deep learning models on brain recordings without building custom data pipelines from scratch.	Engineering teams offloading tickets. Ops/platform work.
Strengths	First drafts with Make Designs Rename/rearrange layers automatically Natural language asset search	Great enterprise story Works in your existing IDE Chat + autocomplete	Unified interface across fMRI, MEG, EEG, iEEG, fNIRS, EMG, and spike trains — no more siloed modality-specific tools Lazy, memory-efficient loading that scales to terabyte-scale OpenNeuro datasets without RAM blowout Native HuggingFace integration for embedding stimuli (text, audio, video) using models like DINOv2, CLIP, Wav2Vec, and more Pydantic-based config validation catches bad BIDS paths or filter settings at init, not after hours of wasted compute Scales from local laptop prototyping to SLURM clusters without rewriting infrastructure code	Works like an engineer — takes Slack tasks, opens PRs Handles multi-hour engineering work Reports back with what it did
Weaknesses	Features vary by plan + region Still rolling out	Less agentic than Cursor/Claude Code Model quality varies	Extremely niche audience — only useful to neuro-AI researchers with Python/PyTorch chops and access to neuroimaging datasets No GUI or managed cloud environment; requires local setup and familiarity with BIDS data formats Still a preprint-stage release with no arXiv paper yet — API stability and long-term maintenance are unproven	Expensive Best for well-scoped tasks Not for solo hobbyists
Kai's verdict	A-tier. No reason not to use it if you're on Figma. Not worth switching for.	B-tier. Solid for autocomplete but the category moved past it. Pick Cursor unless you can't.	If you're doing neuro-AI research, this is the plumbing you've been manually building for years — finally done right by the team that actually runs these experiments at scale. Extremely narrow use case, but within that lane it looks genuinely best-in-class. (Verdict pending Phi's full review.)	A-tier for the right use case. Not for solo devs. If you manage engineers, try one license.
Link	Open →	Open →	Open →	Open →