Mastera

How we turned the manual reading of scientific papers into an AI-powered analysis platform, the first version of a product that Mastera took forward as a SaaS.

  • Published on September 21, 2026
Segment
B2B
Vertical
Agrotech
Launch
July 2025

The challenge

Mastera came to us with a huge challenge: how to map thousands of scientific papers, one by one, and transcribe what matters — the maturity level of each technology, who developed it and in which country, what the results were, which microorganisms are involved — across dozens or hundreds of papers per project, without it eating up weeks of manual work.

The information already existed. What was missing was a way to read it at the speed the decision demanded.

Mastera needed a platform that did this reading in the researcher's place: take in a batch of papers, always extract the same fields in the same format, and return everything organized and comparable. Not a loose summary, but structured data. They needed a real product, not a script: several users, several projects running in parallel, each with its own separate information, with the original papers kept safe and a catalog that stays useful in later queries.

What we did

We worked from a clear scope: building an AI tool able to read and catalog thousands of files, so they could later be classified, reports could be generated and research could go deeper — bringing the speed Mastera needed to serve its clients.

  1. Projects as the unit of work.

    Multiple users access the platform and create projects with basic data and a detailed description. Several projects run in parallel, and each one keeps its information isolated.

  2. Paper upload and AI reading.

    Users upload all of a project's papers and the artificial intelligence reads and processes them automatically, extracting the fields defined with Mastera: TRL (technology readiness level), DOI, authors and countries of origin, results and microorganisms.

  3. A catalog that lasts.

    Each paper is cataloged and the original file stays stored on the platform. What was uploaded today remains available for future queries and analysis, with the extracted information attached to it.

  4. Project dashboard and report.

    A dashboard brings together the key information for each topic, following the table provided by the Mastera team, and a report shows the accumulated results of what the AI extracted within each project: the view of the whole set, not just one paper.

The result

Delivered in July 2025, the platform became the foundation of a product that now serves large companies and is a reference in R&D intelligence for agribusiness. With it up and running, Mastera raised investment to keep evolving the product.

  • A complete platform, from upload to reportMultiple users and projects, AI analysis, a paper catalog, a dashboard and an accumulated report: the entire flow set out in the proposal.
  • From manual reading to automated extractionThe starting point was weeks of manual work; the platform was designed to bring that down to a few minutes.
  • Knowledge that accumulatesEvery uploaded paper is cataloged, with the original stored. A project stops being a folder of PDFs and becomes a knowledge base that can be consulted.
  • The foundation for the SaaS that followedMastera kept evolving the platform and today runs it as an R&D intelligence SaaS for agribusiness, with specialized AI agents and a 14-day free trial.
  • Up to 70% lower R&D costsAccording to Mastera, its methodology cuts the cost of mapping new technologies by up to 70%, and the company already has more than 10 active projects in the agricultural sector.
  • Major agribusiness companies on boardVitales (UbyGroup), MicroGene, AQUi9 and Elytron Biotech are among the companies working with Mastera.

What the product became after our delivery is Mastera's work, and it is worth seeing up close.

Where to see Mastera

Why this case matters

The best first product proves the business thesis and leaves room for everything else to grow.

Mastera came with an ambitious idea, using AI to speed up scientific research, and a table of the fields that really mattered. We designed the scope around that: a handful of fields, extracted consistently, inside a platform already ready for real users and real projects.

A first version doesn't have to be the whole vision. It has to be its foundation.

What came next, the evolution into a SaaS and a multi-agent platform, was Mastera building on that base. That's the kind of delivery we aim for: with code, design and documentation in the client's hands, so they can go far beyond what we delivered.

Capabilities demonstrated

  • Multi-user SaaS platforms
  • Applied AI
  • Structured data extraction
  • Dashboards and reports
  • MVPs designed to become products

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