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Creopus Documentation

Video transcript

00:00 — Creopus.ai

Creopus.ai. The AI-native platform for hardware engineering.

00:07 — One connected model

Hardware development runs on disconnected tools and tribal knowledge — requirements in one document, analysis in another, sourcing in a spreadsheet, and nothing connecting them. Creopus replaces all of it with a single model of the product. This is a real flight-control system, broken down the way engineers actually think — system, subsystem, board, component — and every piece of engineering work hangs off this one tree.

00:41 — Requirements, generated and traceable

From any node, the platform generates a complete, structured requirement set in seconds — here, the flight-control MCU board. Every requirement carries a stable, traceable ID from the moment it is written, and is checked against aerospace design-input standards. What used to take an engineer a day is now a ninety-second draft that a reviewer refines.

01:10 — Decisions, defended

Every real design decision is a trade-off, and reviewers and auditors want to see it was made deliberately. The platform runs the trade study for you — here, three microcontroller options scored against weighted criteria like functional-safety suitability, real-time performance and cost — so choosing the lockstep processor is a defensible decision, not just an assertion.

01:39 — Risk, surfaced

Beyond what the design must do, the platform analyses how it can fail. A design FMEA identifies each failure mode, rates its severity, and records the mitigation — every entry scored so the highest-risk items rise to the top. This is the safety analysis critical programs are required to produce, generated from the same grounded understanding of the board.

02:10 — Architecture and interfaces

Architecture is captured as a living block diagram — here the whole flight-control computer, from power conditioning through the sensor module and the dual-core processor out to the servo drives. Power, data and control connections are typed and labelled, and an interface control document is derived straight from it — so the connections between blocks are specified, not left to a photo of a whiteboard.

02:41 — The design, judged

This is where Creopus does something no document tool can. Upload the actual schematic, simulation or PCB, and the platform reviews the implementation — grounded in this node's requirements, FMEA and bill of materials — and returns real engineering findings, graded by severity and by discipline. It judges the design; it does not just store it.

03:10 — Verification, planned

Every requirement has to be verified, and the design verification plan lays out exactly how — test by test — closing the loop from what the product must do to the evidence that it does it.

03:27 — One live picture of the whole program

And because it is all one model, the platform rolls it up into a single live picture of the program. Verification at ninety percent, validation complete, interfaces largely closed, every requirement traced — with a requirements-traceability matrix and a verification-and-validation record you can export for an audit, and AI-surfaced insights flagging exactly what still needs attention. This is the systems-engineering view that normally takes a dedicated tool and a team to maintain.

04:05 — From design to purchasable parts

A design only ships if the parts are real. The procurement workspace turns a part into purchasable options — comparing suppliers on price, lead time and fit — and writes the decision straight back to the bill of materials, with full sourcing provenance.

04:26 — One agent, every tool

And every one of those tools is driven by an autonomous agent. Ask it once — audit these requirements, raise a DFMEA for the gaps — and it chains the tools together, grounded in the same model. Every change it makes comes back as a proposal you review and merge, never a silent edit. And the same tools reach your other AI clients through an open protocol, so Creopus works from Claude or Cursor too.

04:59 — creopus.ai

One product. One connected model. From the first requirement to a sourced, verified, audit-ready design — with AI doing the heavy lifting and engineers in control of every decision. That is Creopus. See it at creopus dot A I.

Creopus is an AI-native platform for hardware product development — requirements, architecture, FMEA, verification planning, BOM, procurement, and design review in one change-controlled system of record, with AI that drafts and a workflow that keeps engineers in control.

Start here​

  • Why Creopus — what the platform replaces and why teams switch.
  • Features — deep-dives on the tools and workflows, including the two authoring paths (AI generation and hand-authoring) behind every document.
  • FAQ — pricing, data security, and the AI providers behind the tools.
  • Changelog — what shipped, newest first.

Explore the tools​

  • Requirements (ReqGen) — structured, level-aware requirements with deterministic quality checks and traceability.
  • DFMEA and PFMEA — design and process failure-mode analysis, feeding the Risk Register and CAPA.
  • ConOps, ICD, Risk Register, SEMP — the systems-engineering documents that make requirements defensible.
  • Implementation Workspace — upload your schematic, layout or SPICE deck and get structured findings against your own requirements.
  • Procurement — search, curate, RFQ and compare parts, then push to BOM.
  • System hierarchy — the change-controlled tree everything else hangs from.
  • Review workflow — submit, comment, disposition, approve, baseline.
  • MCP server — use Creopus tools from Claude, Cursor and other AI clients.

Using the app?​

In-app help lives under Documentation in the creopus.ai footer: written Tool Guides for every tool, and in-page tours behind each page's ? button.

Ready to try it? Open the app — the Free plan gives you one AI generation per tool so you can judge the output on your own product. The AI agent and the remote MCP server are on paid plans; see pricing for generation limits per plan.