Question 1

Is WeProject.ai one product or several?

Accepted Answer

Both, and the distinction matters. WeProject.ai is the platform; WeProject is its flagship application, the graph-native requirements and programme governance tool. Alongside it run SMAT-AI for space mission analysis, Academy for training, Data Domain as the shared reference-data source of truth, and Supremacy for market and competitive intelligence. They share one sign-in and read the same reference data, and you licence only the ones you need.

Question 2

Can it run air-gapped, with no outbound connection?

Accepted Answer

Yes, and this is the capability the platform is built around rather than a bolt-on. The AI layer routes to whichever model provider you configure, and two of the supported options — Ollama and vLLM — run entirely on hardware you own, so no prompt or document leaves your network. The data stores are self-hostable, and each product ships an offline reference bundle so it still works when the shared data service is unreachable.

Question 3

Which AI models does it use? Can we bring our own?

Accepted Answer

The model provider is a configuration choice, not a fixed dependency. The AI service routes to OpenAI, Anthropic, Google Gemini and DeepSeek for hosted inference, or to Ollama and vLLM for self-hosted models. You can point it at your own deployment, and switching providers does not change the product surface.

Question 4

Do we have to buy all five products?

Accepted Answer

No. Each product is licensed separately and the navigation adapts to what you own — a product you have not licensed simply does not appear. A space operator might take SMAT-AI, Data Domain and Academy; a programme office might take only WeProject and Data Domain.

Question 5

How do people sign in across the products?

Accepted Answer

One central authentication service issues a session that every product accepts, so a user signs in once and moves between products without signing in again. It supports password sign-in, Google and Microsoft SSO, and multi-factor authentication. Permissions resolve on two axes: what the person is allowed to do, and which application is asking.

Question 6

If several products hold the same data, which one is authoritative?

Accepted Answer

Data Domain is. It is a single Postgres source of truth for the shared reference data — missions, platforms, subsystems and the KPI registry — and it is the only service that writes to it. Every other product reads from it. Applications that hold read-only access can still propose a change, which an operator reviews and approves rather than editing in parallel. It carries 329 KPIs, 1,300+ platforms and 90+ reference APIs.

Question 7

How do our engineers learn the platform and the domain?

Accepted Answer

Academy is a full product rather than a documentation site: 94 interactive simulators and over 500 assessments covering orbital mechanics, satellite operations, electronic warfare, model-based systems engineering and leadership. It is licensed like the others and shares the same sign-in.

Question 8

Can we bring in requirements and data we already have?

Accepted Answer

Yes. The platform ingests Word documents, Excel workbooks and legacy databases, and exports finished documents server-side as Markdown, PDF, DOCX and PPTX. The export pipeline versions what it produces, so a document you issued can be reproduced later exactly as it was issued.

Question 9

Does the platform make us compliant with DO-178C, ISO 14971 or DFARS?

Accepted Answer

No tool can. What the platform does is support the engineering workflow those standards require: bidirectional requirement traceability, immutable baselines, an audit history of every change, verification and validation evidence linked back to the requirements it satisfies, and documents generated from that record rather than maintained beside it. Certification remains an assessment of your organisation and your evidence, by your auditor. We can show how the platform produces the evidence; we cannot and do not certify you.

Question 10

Where does our data physically live?

Accepted Answer

Wherever you choose. The hosted deployment runs on Google Cloud Run in the europe-west1 region. The self-hosted and air-gapped deployments run entirely on your infrastructure, in which case no data reaches us at all — including prompts, if you use a self-hosted model.

Question 11

How do we get access, and what does it cost?

Accepted Answer

The platform is in beta and access is granted from the waiting list rather than by self-service signup. Commercial terms depend on which products you licence and whether you deploy hosted or air-gapped, so pricing is quoted rather than published. Join the waiting list below and tell us which products and which deployment model you need — that is enough for us to come back with a straight answer.

Question 12

What happens to our data if we stop using the platform?

Accepted Answer

It comes with you. Requirements, baselines and the document record export to open formats — Markdown, PDF, DOCX, PPTX and structured data. The reference data model is documented rather than proprietary, and the self-hosted deployment means you can already be holding your own database.

Figure	Derived from	By	Source last changed
122ontology classes graded against ISBEGO Each grading also records the rule or model that produced it and a confidence level. where it appears	apps/data-domain/seed-data/ontology-class-dimensions.json	apps/site/scripts/gen-isbego.mjs	2026-07-18 `24e03871f`
516class–dimension gradings in total Across every classification dimension, not only ISBEGO. where it appears	apps/data-domain/seed-data/ontology-class-dimensions.json	apps/site/scripts/gen-isbego.mjs	2026-07-18 `24e03871f`
30classification dimensions Carrying 325 facet values between them. ISBEGO is one of the 30. where it appears	apps/data-domain/seed-data/dimensions.json	apps/site/scripts/gen-isbego.mjs	2026-08-16 `37e51aa5b`
382entity types across the estate Spanning 7 applications. where it appears	apps/data-domain/seed-data/entity-types.json	apps/site/scripts/gen-isbego.mjs	2026-08-23 `db804b520`
129ontology schema rules With 36 relationship types — what may connect to what is declared, not conventional. where it appears	apps/data-domain/seed-data/ontology-schema.json	apps/site/scripts/gen-isbego.mjs	2026-08-23 `8b54cad26`
36relationship typeswhere it appears	apps/data-domain/seed-data/relationship-types.json	apps/site/scripts/gen-isbego.mjs	2026-07-14 `8539d6ce1`
2,236terms in the public engineering reference Projected from the estate’s acronym catalogue; the site holds no second copy. where it appears	apps/site/client/src/config/reference.generated.json	apps/site/scripts/gen-reference.mjs	2026-08-24 `617f60d73`

Every number here, and what re-derives it

What is deliberately not here