New to neural APIs?
Start with the model, the interface, and the application around it.
Understand the foundations
THE NEURAL API FIELD GUIDE
One neuraluniverse.
From language models to intelligent agents. Explore the interfaces, patterns, and possibilities connecting AI to your next idea.
Open learning Practical patterns No API key needed
IDEAS → INTERFACES
neural://command-console6 CONNECTED TRACKS
LLM Neural APIText → intelligence01Agentic Neural APIIntent → action02Chat Agent Neural APIMessages → context03Robot Neural APILanguage → motion04Brain Neural APISignals → data05AI Trading Neural APIResearch → evidence06
One starting point. Many directions.EXPLORE ↗
The ecosystem
Six ways to connect
with what comes next.
Choose a field. Understand its boundaries. Find a useful place to begin.
View the ecosystem01 / EXPLORE
Language models
Explore text generation, structured outputs, embeddings, and the contracts that connect models to applications.
Text → intelligence
02 / EXPLORE
Agentic systems
Understand tool calling, task planning, and permission checks without confusing a model proposal with authority.
Intent → action
03 / EXPLORE
Chat agents
Design chat experiences with purposeful memory, evidence-based retrieval, and a clear path back to a human.
Messages → context
04 / EXPLORE
Robotics
Study the boundary between model-generated plans and physical control, starting with supervised simulation.
Language → motion
05 / EXPLORE
Brain & biosignals
Explore brain-signal data interfaces through channel metadata, timing, research consent, and reproducible processing.
Signals → data
06 / EXPLORE
Trading research
Explore AI-assisted market research with point-in-time data, reproducible experiments, and no live order execution.
Research → evidence
Better instructions. Better starting points.
Prompt templates, evaluation habits, and the craft behind clear requests.
A little less abstract
Meet your next
building block.
A good interface starts with a clear contract. Peek inside a reference pattern, switch perspectives, and take the useful pieces with you.
01
Choose a pattern
Text, tools, schemas—and the boundary between them.
02
Read the contract
Understand what goes in, what comes out, and what needs review.
03
Make it your starting point
Copy the JSON. Use the guide to plan your own integration.
text-request.jsonJSON
{
"task": "summarize",
"input": {
"text": "A neural API connects an application to a model."
},
"output": {
"format": "plain_text",
"max_words": 40
},
"review": {
"required": true
}
}{
"task": "lookup_document",
"tool": {
"name": "read_approved_document",
"arguments": {
"document_id": "guide-001"
}
},
"policy": {
"mode": "read_only",
"max_steps": 3,
"authorization": "application_required"
}
}{
"type": "object",
"properties": {
"summary": {
"type": "string"
},
"needs_review": {
"type": "boolean"
}
},
"required": [
"summary",
"needs_review"
],
"additionalProperties": false
}REFERENCE ONLY · LOCAL
Clear contracts. No black box.
Describe the input, the output boundary, and the required review before choosing a provider.
Local reference examples. No live inference or API requests.
Find your direction
Big possibilities.
A sensible first step.
You don’t need to learn everything at once. Start with the question in front of you.
Ready to build an agent?
Explore tool proposals, permissions, and the point where a plan becomes an action.
Follow the agentic trackThinking beyond text?
Bring the right questions to robotics, biosignals, and research workflows.
Explore applied AINeural Notes
Good questions.
Deeper understanding.
Field guides for the details that make a difference.
Read all 10 guides
Tool calling without handing over the keys.
Give agents useful tools while keeping permissions, approvals, and execution in your application.
Read the guide
Structured outputs: valid JSON is just the beginning.
Design output contracts that represent uncertainty, preserve evidence, and survive real inputs.
Read the guide
When language meets motion, boundaries matter.
Separate language-based task proposals from the controller that owns physical execution.
Read the guideBefore you dive in
A few things
worth knowing.
What this project is, what the examples do, and where to begin.
All your starting questionsWhat is a neural API?
A neural API is an interface to a neural-network capability or a system built around one. The important contract is the input, output, evidence, and failure behavior. Begin with the neural API foundations guide.
Is NeuralAPI.com an inference provider?
NeuralAPI.com is an independent learning resource, not a hosted inference service. The guides and Pattern Lab help you explore interfaces and design decisions. The lab copies local reference patterns and does not send requests to a model.
How are LLM APIs and agentic APIs different?
The LLM track focuses on model inputs and outputs. The agentic track adds tool proposals and action workflows. In the architecture described here, your application checks permissions and controls execution rather than treating model output as authority.
Can I try the examples without an API key?
Yes. The Pattern Lab lets you switch examples, copy JSON, inspect labelled example results, and download the pattern pack without an account or API key. Connecting an actual provider is a separate implementation step.
Does “brain neural API” mean mind reading?
No. Our brain neural API track concerns research biosignal measurements, metadata, and data processing. It does not claim to read thoughts, diagnose conditions, or provide medical guidance.