Can you take over a Streamlit, Shiny, or Streamlit-on-localhost prototype?

Yes — this is one of the most common closeout patterns. We typically rebuild the prototype's working logic into a deployable, documented service (FastAPI / Next.js / your preferred stack) with a stable URL and a README that passes a fresh-laptop test. The science behind the prototype stays; the engineering becomes maintainable.

What does 'evaluator-ready' actually mean for digital deliverables?

For Horizon Europe and most national funders: a public artefact reachable from outside your VPN, documentation that explains what the deliverable is and how to use it, data archived with a citable identifier, and a clear handover statement. We work to those standards by default. If your funder has specific requirements (e.g., MDR-related, IRB-related, data-protection-specific), tell us in the scope review.

What if we need more than 6 weeks of work?

Larger closeouts (multi-site consortia, complex ML deployments, regulatory contexts) sometimes need 8–10 weeks. We'll be honest in the scope review about how long your situation realistically needs. We won't promise 6 weeks for work that's actually 10.

Service · Closeout takeover

Digital closeout for grant-funded research projects

We deliver the dashboards, datasets, repositories, documentation, and ML outputs your closeout package needs — finished, documented, evaluator-ready. Most teams come to us 6–10 weeks before deadline; we ship in 3–6.

Request a Scope Review See delivery examples

If any of these sound familiar, you need closeout help

These are the patterns we see almost every time a research project comes to us in the last quarter before its grant closeout deadline.

The data analysis isn't finished. PhD students are still cleaning data the week before the report is due.

The promised platform exists in fragments. A Streamlit prototype, a Figma mockup, a Shiny app on someone's localhost — none of it is a real digital deliverable.

The handover documentation doesn't exist. Without it, the next team can't continue the work and your FAIR-data commitments don't hold up at review.

Your team is brilliant at research, not engineering. Asking PhD students to ship the platform on top of writing their thesis was always a stretch.

You tried a generic agency. They didn't understand the Annex, the deliverable format, or what evaluators actually look for.

What the closeout package includes

Each engagement is scoped to your specific Annex 1 and the gap between current state and what evaluators expect. Most closeout packages include some or all of:

Reproducible data-to-report pipeline

Cleaning, structuring, analysis, and figure generation as code. Final report figures sourced from the pipeline — not screenshotted from Excel. Re-runnable when the next dataset arrives.

Public-facing digital artefact

A runnable, accessible, documented version of the platform your work plan promised. Stable URL, README that passes a fresh-laptop test, credentials documented if auth-gated.

FAIR-aligned data archive

Deposition to Zenodo, your institutional repository, or domain-specific archives. Citable DOI, structured metadata, stated reuse licence. The FAIR commitment from your DMP, made real.

Evaluator-ready handover documentation

Data dictionary, deployment guide, runbook, decision log, FAIR-alignment notes. The pack that lets your evaluator verify and the next consortium continue.

Closeout-meeting demo prep

Walkthrough script, demo dataset, fallback plan if the live demo fails. No surprises in front of the funder.

How the engagement runs

Three phases compressed into the time you have left. Audit on day one, deliver from week two onward.

Step 01

Audit (week 1)

We read your Annex 1, list every committed digital output, and inventory what already exists. No new build yet. Output: a single document showing the gap between commitment and current state, with an honest readiness score per deliverable.

Step 02

Scope (week 1–2)

We define the minimum-viable version of each gap deliverable that meets evaluator expectations within the time available. Trade-offs are documented explicitly so the funder isn't surprised at review.

Step 03

Deliver (weeks 2–6)

We build, document, and hand over. Public artefact deployed early and iterated. Documentation written as the work happens, not at the end. Each deliverable gets a clear 'done' marker tied to your Annex.

What this typically costs vs alternatives

Closeout consultancies running three-month engagements: €15–30K. A senior data manager hire: €40–55K/year plus three months of recruiting plus ongoing supervision. A Pragma scoped 3–6 week closeout: a fraction of either, with a defined ceiling and a deliverable bundle the funder actually verifies. Pricing is project-specific — the scope review tells you the exact number for your project, before any commitment.

What 'doing nothing' looks like: six weeks before the deadline, the data analysis isn't finished, the platform isn't deployable, the documentation doesn't exist. The closeout meeting becomes defensive. Dissemination, exploitation, and impact scores drop. The cost of the status quo is invisible until the review meeting — by then it's expensive to recover. The cost of acting now: 60 minutes for a free scope review.

Closeout questions teams ask before they engage

We've taken on closeout engagements as close as 4 weeks before the deadline. Below that, the honest answer is usually 'request a 1-month extension from the funder, then engage us'. We'll tell you on the scope review whether your timeline is genuinely workable or whether the realistic move is an extension request.

Closeout deadline approaching?

Send us your Annex 1 and a short note on what's outstanding. We'll reply within 2 business days with either a scope proposal or clarifying questions — no commitment.

Request a Scope Review

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