From a vanilla CRM to a EUR 4.3M qualified pipeline
- Client
- Allyfe
- Sector
- Health-tech
- Capabilities
- CRMAutomation & AI
- Stack
- HubSpot · ClinicalTrials.gov · EU CTIS · GlobalData · Firecrawl · Apollo.io · Dropcontact · Webflow
A Belgian clinical-trial software company needed commercial foundations it could put in front of investors: a lead engine, a qualification framework, and a CRM configured to run it. 3 months later, all 3 were live, with 70+ qualified deals in the pipeline.
Allyfe is a Belgian platform that streamlines clinical trial document management (eTMF, e-Archive, eISF, plus connectors). Its ideal customers are biotech sponsors running clinical trials in Europe, a market tracked in public registries.
At the start of the engagement, the commercial layer had not been built yet. HubSpot was in place but vanilla: no pipeline, no products, and no properties to record what mattered about a lead. Pricing logic lived in the business plan, not in the CRM, so no deal carried a value. The website was not yet instrumented for analytics.
With no structured lead database and no qualification framework, there was no defensible answer to the first commercial question: which companies to call, and in what order. Allyfe’s ideal customer profile had not yet been mapped to identifiable target companies.
The market had not been sized in the terms an investor asks for: no total addressable market, no funnel benchmarks from lead to first meeting to signed deal, no traffic data, no attribution, and no shared dashboard for the CEO or the commercial team.
Those gaps blocked both fronts at once: investor confidence and any structured path to running a sales pipeline.
The build started from one insight: every company filing a clinical trial in Europe needs document management, and the registries that track those trials are public. We consolidated 8 sources (ClinicalTrials.gov, the EU CTIS registry, industry collaborators, and medtech directories) into a master list of 2,600+ unique sponsors, deduplicated by fuzzy matching and ranked for enrichment.
On top of it we built a 10-step qualification machine, backed by Python and SQLite with Datasette giving the team queryable access to every layer. Companies are researched with Firecrawl and GlobalData, contacts enriched through Apollo.io and Dropcontact, then scored through a 7-gate model run by 4 coordinated AI agents. A human reviews every qualification before anything moves downstream. 140+ companies went through the full pipeline, with 900+ contacts enriched and 1,000+ compounds and 1,150+ trials tracked behind them.
HubSpot was configured end to end: 43 custom properties, a sales pipeline with stage probabilities, 7 saved views, a 25+ SKU pricing model, card layouts, and creation forms. The live import filled the CRM with the machine’s output: researched companies, enriched contacts, and 70+ qualified deals with computed deal values.
The 10 steps are documented end to end, and the team runs them.
The result is a EUR 4.3M qualified pipeline where there was none, with a sales brief on every qualified company so the CEO walks into any meeting prepared.
The market intelligence behind it (Eurostat data across 27 EU countries, a country ranking built on 5 explicit dimensions, and a source authority audit) was used directly in investor presentations.
"Our CRM was empty. Vanilla, nothing in it. A few months later: a qualified pipeline worth millions, full of companies we actually want to win. Each one comes with a brief, who they are, why they fit us. I walk into every meeting prepared now. Every single one."
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