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Solutions

The intelligence layer for frontier AI.

Four ways to work with Synthium Labs: Data, Train, Agents and Red Team. All four run on one shared foundation of expert network, data operations and evaluation infrastructure. Each is a workforce, a workflow and a quality system — expertise is the product, not the headcount. Quality arbitrage, not labour arbitrage.

DATA

Synthium Data

Data acquisition, licensing, curation and expert-led annotation

We acquire or license eligible company-owned data, and turn raw data and domain-specific tasks into expert-reviewed datasets through curation, annotation, quality assurance and adjudication.

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How it runs

  1. Data or Task
  2. Rights & Provenance
  3. Guidelines
  4. Expert Annotation
  5. Audit & Adjudication
  6. Expert-reviewed Dataset

TRAIN

Synthium Train

RL environments and expert-generated post-training datasets

Production-grade RL environments for training frontier agents on real engineering work: runnable tasks with explicit completion criteria and independent verification. Plus SFT, preference and reasoning datasets written and verified by domain experts.

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How it runs

  1. Prompt
  2. Expert
  3. Response
  4. Critique
  5. Preference
  6. Training Data

AGENTS

Synthium Agents

Agent and model evaluation

Coding and reasoning agents assessed by engineers across correctness, architecture, security and failure modes, and model outputs judged by experts against documented, calibrated rubrics. Each failure comes with an expert diagnosis, not just a score.

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How it runs

  1. Agent or Model
  2. Task
  3. Execution
  4. Expert Eval
  5. Score
  6. Failure Analysis

RED TEAM

Synthium Red Team

Adversarial testing and safety assessment

Domain experts probe safety boundaries, attempt jailbreaks and surface policy violations. Every finding is severity-rated and ships with reproduction steps, so your team can verify it.

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How it runs

  1. Threat Model
  2. Adversarial Tasks
  3. Expert Red Team
  4. Severity
  5. Report

Shared foundation

Three shared capabilities power all four products.

The Data Foundry, the Expert Network and Evaluation Infrastructure are built once and shared. They are not separate offerings: every product draws on the same standard of judgement.

How we scope a solution

Scope, pilot, validate, scale.

Prove it small. Then scale it. Every engagement follows the same path, so the standard is checked on your work before capacity grows.

  1. Scope

    We define the task, the expertise it requires and the quality bar your deliverable must meet.

  2. Pilot

    A scoped pilot runs on real work. Experts are qualified and calibrated against your rubric before production.

  3. Validate

    Output passes independent review and is checked against the criteria agreed up front. Disagreements are adjudicated.

  4. Scale

    Capacity expands only after the standard has held on your work.

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Bring us your hardest data problem.