intrface

Funda

Reads EU funding calls as they publish and matches them to the organizations that fit.

Active buildEU fundingFour rolesThree languagesGeospatial matching
4
Role surfaces
Admin, consultant, corporate, director
3
Languages
Every surface, not just the marketing pages
2
Source pipelines
SEDIA and TED, read by agents

Funding you qualify for, before the deadline

EU funding is public money that is hard to find. Calls land on SEDIA and TED as long documents with their own vocabulary, eligibility rules and deadlines. Most organizations hear about the right one too late.

Funda watches those sources on a schedule, turns each call into a structured record, and puts it in front of the organizations that match. Consultants work a portfolio of clients against the same feed. One dataset, read four ways.

Admin
The people who run the platform
Consultant
Advisors carrying several client organizations
Corporate
The organization applying for the funding
Director
Oversight across an account

From a published call to the right inbox

  1. 1

    Read the sources

    Agents pull calls from SEDIA and TED as they publish, instead of waiting for someone to check a portal.

  2. 2

    Turn documents into fields

    Each call becomes a record: who may apply, for what, in which regions, by when.

  3. 3

    Score against the organization

    An organization's profile is compared field by field — sector, size, and where it actually operates, which is where the geospatial part earns its keep.

  4. 4

    Route it to a person

    Matches land on the surface that role uses, in that user's language.

Same shape, smaller footprint

Voyager is where we built retrieval that stays grounded in a client's own content. On Polis, the hard part was an audit trail that makes a claim checkable. Funda carries both at a smaller scale: ingestion that has to be accurate, matching a user can argue with, and four roles reading one typed dataset.

The stack is deliberately small — Next.js on the front, Convex for data and functions, Clerk for identity and roles. The hard part is keeping an agent pipeline honest when the input is a call document written in institutional language and the output is a decision someone will act on.

Have a system with this shape?

Tell us what it has to read, who has to see the result, and what happens if it is wrong. We will tell you what it takes.

Bring us the system