Concept demo

Watch the JetinAI “jet” think through problems.

This page is a visual concept — not a product UI — showing how JetinAI decomposes a question, explores evidence, and connects everything back into decisions and infrastructure.

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Reasoning flight path

A high-level view of how JetinAI moves from an open question to structured reasoning, research, and actions — while keeping humans in the loop.

1. Understand & frame 2. Explore & gather 3. Synthesize & simulate 4. Decide & integrate

1. Understand & frame the problem

JetinAI starts by clarifying the question, surfacing assumptions, and mapping out sub-problems. It proposes alternative framings and lets humans choose the most useful direction.

  • Highlight hidden constraints and missing context.
  • Suggest multiple frames, from tactical to strategic.
  • Create an initial reasoning plan instead of jumping to an answer.

2. Explore & gather evidence

JetinAI branches into research mode, pulling in information from documents, data sources, and tools you connect — while keeping track of where each piece of evidence comes from.

  • Traverse papers, docs, and APIs with traceable citations.
  • Contrast competing hypotheses, not just collect facts.
  • Keep a live graph of “what we know so far”.

3. Synthesize, simulate & compare paths

JetinAI turns raw evidence into structured reasoning. It compares scenarios, runs simulations or thought experiments, and exposes trade-offs so teams can choose with clarity.

  • Generate multiple candidate plans with pros & cons.
  • Simulate how changes ripple through your system or product.
  • Surface surprising connections that would be easy to miss manually.

4. Decide, integrate & monitor

Once a direction is chosen, JetinAI helps translate reasoning into actions — tickets, API calls, dashboards, or documentation — and keeps a feedback loop open as reality changes.

  • Push decisions into tools like issue trackers or internal systems.
  • Set up monitors and alerts driven by the reasoning process.
  • Continuously refine the model of your problem space over time.

Platform layers working together

The same reasoning flow is backed by three core layers of the JetinAI platform. This concept view shows how they line up.

Layer 1 · Jet models

Reasoning engines

Specialized models tuned for step-by-step thinking, planning, and explanation — not just next-token prediction.

  • Chain-of-thought and planning first.
  • Configurable depth, style, and safety.
  • Designed to expose intermediate traces by default.

Layer 2 · Research OS

Research & investigations

A workspace where questions, notes, evidence, and agents live together in evolving reasoning threads.

  • Long-lived investigations across weeks or months.
  • Shared context between humans and agents.
  • Re-runnable reasoning with versioned histories.

Layer 3 · Infrastructure

APIs, tools & monitoring

The plumbing that connects JetinAI to your stack — data sources, APIs, metrics, and control surfaces.

  • Typed connectors with observability.
  • Policy and guardrail layer for real environments.
  • Usage-aware reporting and cost control.