AI data and systems studio

We turn raw signal into data and systems you can build on.

Brontes builds training and evaluation data, the pipelines that keep it clean, and the AI systems that run on it in production.

Start a project What we build
Fig. 1 · Thunder, recorded and structured
Input4.20 s · 44.1 kHz
Samples185,220
Output84 windows × 50 ms
Labels3 classes
Βροντή is Greek for thunder. On the left, the raw recording. On the right of the cursor line, the same signal as structured, labelled data: one loudness value per window, ready to train or test on. Hover to inspect a window.

What we build

Most AI projects stall on the data, not the model. We build the data first, then the system around it, and leave you with both.

Training data

01

Datasets collected, cleaned and labelled to a written spec, with the guidelines and quality checks that make the labels trustworthy.

  • collection
  • labelling
  • synthetic data
  • QA audits

Evaluation

02

Test sets and scoring that tell you whether a model or prompt change made things better, before your users find out.

  • eval suites
  • golden sets
  • regression tests
  • error analysis

Data pipelines

03

The ingestion, transformation and versioning that keep data fresh and traceable as it moves from source to model.

  • ingestion
  • transformation
  • versioning
  • lineage

AI systems

04

Retrieval, agents and model integrations, built as dependable tools for your team and monitored once they are live.

  • retrieval
  • agents
  • integrations
  • monitoring

How we work

Six stages, named for the forge the original Brontes worked in. The temperatures beside each are the real ones a smith would use.

  1. 01

    SourceOre

    We audit the data you have, the data you need and where the gaps are.

    A data audit and a written plan

    20 °C
  2. 02

    PilotHeat

    A small dataset and schema, labelled and tested, so decisions rest on real examples.

    A pilot dataset and labelling guide

    800 °C
  3. 03

    BuildStrike

    The full pipeline and dataset, delivered in versioned increments you can inspect.

    Versioned data and working pipelines

    1,100 °C
  4. 04

    EvaluateQuench

    Evals, audits and failure testing. The work has to hold up under pressure.

    An eval suite and quality report

    1,100 → 60 °C
  5. 05

    RefineTemper

    Error analysis and fixes where the evals point, until the numbers are stable.

    Measured improvements, documented

    220 °C
  6. 06

    Hand overWield

    Deployed, documented and owned by your team, with monitoring in place.

    The code, the data and the keys

    37 °C

ΒΡΟΝΤΗΣ

Say it
BRON-teez
Means
Thunder
Source
Hesiod, Theogony 139–146

Why Brontes

In Hesiod's Theogony, Brontes and his brothers Steropes and Arges were the smiths who forged Zeus's thunderbolt. They didn't wield it. They made the instrument that others relied on.

That is the work we do. We make the data and systems other teams build on, then hand them over.

Contact

Tell us about your data.

What you have, what you're trying to build and where it's stuck. Rough notes are fine.

hello@brontes.dev