Product system
Video intelligence built as a product workflow, not a single demo prompt.
Ayneye turns footage into durable World-State, evidence bundles, timelines, cost reports, dashboard workflows, REST APIs, and agent-readable artifacts. Teams can evaluate one narrow workflow, inspect the generated files, ask evidence-grounded questions, and understand limits before expanding usage.
Product operating model
The product is organized around a repeatable sequence: add a video source, run bounded CPU-first processing, materialize World-State artifacts, inspect evidence, ask grounded questions, and decide whether the workflow is ready for a larger beta allocation. This makes the product understandable to engineering, security, operations, and finance teams.
| Layer | What the user sees | What the system creates |
|---|---|---|
| Workspace | Tenant dashboard, video list, sandbox limits | Account, tenant, plan, usage ledger |
| Processing | Bounded execution button and status | capture report, detector report, timeline, scene graph |
| Evidence | Inspectable spans and review notes | evidence_bundle.json and answer_trace records |
| Ask Video | Questions answered from evidence | citations, confidence, review_required state |
| Cost | Visible processing and query context | cost.json and usage counters |
Choose the right product path
How it works
Understand the full video-to-World-State pipeline and where evidence is produced.
Open ->ArtifactWorld-State
Learn why scene state is the stable interface between video and software.
Open ->TrustEvidence
See how answers stay traceable instead of becoming unsupported summaries.
Open ->WorkflowAsk Video
Ask questions with evidence-required guardrails and review states.
Open ->WorkspaceDashboard
Evaluate the product from signup to demo workspace and artifact inspection.
Open ->EconomicsCost control
Understand video-hour economics, cost.json, and repeated-query planning.
Open ->What makes this a product
A product page should show more than a promise. Ayneye exposes the state files, the dashboard workflow, the API contract, the cost model, the limits, and the safety boundary. Buyers can ask whether the artifact quality is good enough, whether the evidence covers their workflow, whether the cost is predictable, and whether risky actions stay under human control.
Product boundaries are part of the product, not footnotes. Ayneye is not presented as a replacement for every GPU video foundation model, not a free-infinite-query engine, and not an autonomous surveillance decision system. The current beta path is controlled signup, dashboard, REST API, bounded processing, evidence artifacts, visible limits, and read-only agent/MCP-style evaluation. Hard scenes, identity-sensitive workflows, emergency response, physical access, discipline, and destructive actions require human review or remain blocked.