AI × Quant × TradingFoundations US$99 · Signals US$1,299 · AI Live US$5,980 · interest registration openView →

AI Research Transformation

Turn fragmented information work into traceable research workflows for family offices, asset managers, banks and insurers.

Who reviews the information after ingestion?

The challenge is to define trusted sources, merge repeated events, link research objects, identify material changes and assign a reviewer.

Anonymised project descriptions · supplied by the founder

Quant research: an AI intelligence radar

Sources → event weighting and deduplication → research-object links → material-change assessment → research tasks. Sources, objects and criteria are tailored to the institution.

Our public Quant Radar illustrates the workflow. Client identity and project outcomes are not independently verified; the public example is not proof of a client engagement.

View the public radar (Chinese)

Insurance workflow: AI reputation alerts

The described workflow monitors target-institution mentions across channels such as Xiaohongshu, Weibo, Douyin and WeChat, classifies them and routes rule-based responses or human-review tasks.

Around-the-clock operation is a design goal. Channel coverage depends on lawful access, permissions and platform limits; unrestricted real-time coverage is not promised.

Acceptance criteria

  • A source and permission inventory with coverage and failures.
  • Traceable events and recorded deduplication/weighting rules.
  • Human review, severity routing, tasks and withdrawal procedures.
  • Assess missed events, false alerts, review effort and adoption without inventing improvement percentages.

Start with one concrete workflow.

Tell us your institution type, current workflow and the outcome you need. Scope, timing and pricing follow discovery.

Discuss your requirements