Tell us the companies, instruments, funds or assets to cover, the fields to collect and how often you need the data updated. We source it from public disclosures, structure it and deliver it into your workflow.
Structured output
Ready for analysis
A custom dataset is defined across two dimensions: what it covers and what it collects. Together, they give you precise control over the universe and level of detail of each dataset.
What your dataset can cover
Listed or private companies, parents, subsidiaries, SPVs and other legal entities.
Equities, bonds, loans, structured products and other issued instruments.
Funds, ETFs, investment vehicles and their publicly disclosed holdings.
Plants, mines, properties, infrastructure and financed or operated projects.
What your dataset can include
Identifiers, classifications, parents, subsidiaries, issuers, holdings and counterparties.
Coupons, maturities, seniority, covenants, share classes, debt and corporate actions.
Statements, segments, capital allocation, operational KPIs, transactions and guidance.
Capacity, production, locations, products, customers, markets and supply chains.
Emissions, resources, targets, headcount, diversity, safety and remuneration.
Boards, policies, litigation, incidents, regulatory events and strategic changes.
Mandatory company, fund and instrument submissions.
Corporate, ownership, licensing, permit and other public-record data.
Listings, issuer notices, security data and corporate actions.
First-party reports, factsheets, holdings and operational updates.
Attributable announcements, publications and public web material.
Taxonomies, methodologies, benchmarks and sector or project data.
Share your use case, target universe and any initial requirements. We assess feasibility, suggest field definitions and structure, review expected coverage and agree a practical specification with you.
Download CSV or XLSX files, or retrieve the dataset through an API.
Receive updates through SFTP, cloud bucket sync or a data warehouse such as Snowflake.
Set the update lag your workflow requires, from minutes or hours to daily or quarterly refreshes. We adapt monitoring and maintenance accordingly.
Illustrative maintained datasets
Each dataset is refreshed according to its agreed update lag
| Dataset example | Coverage | Example field | Example value | Period | Last updated | Public source |
|---|---|---|---|---|---|---|
| Financial performance | Companies | Capital expenditure | USD 1.7bn | FY2025 | 2 months ago | Annual report · p.96 |
| Fixed-income terms | Bonds | Coupon rate | 4.25% | At issuance | 47 minutes ago | Final terms · p.2 |
| Fund holdings | Funds | Holding weight | 4.8% | 30 Jun 2025 | 8 hours ago | Fund report · p.41 |
| Asset operations | Solar assets | Installed capacity | 312 MW | FY2025 | 1 day ago | Asset register · p.14 |
| Workforce diversity | Companies | Women in management | 38.4% | FY2025 | 6 weeks ago | Sustainability report · p.65 |
| Governance events | Issuers | Board appointment | Independent director | 18 Apr 2025 | 3 minutes ago | Exchange notice · p.1 |
We guide the process at every step, from shaping the brief and assessing feasibility to validating delivery and managing updates.
Tell us the workflow and outcome you need. We help translate them into a workable data brief.
We assess sources, definitions, coverage, history and edge cases, then propose a clear scope.
We build the dataset, share early outputs and refine the schema and quality rules with your feedback.
We deliver through your preferred channel and maintain the agreed freshness as new data is published.
Tell us what you need covered, which fields you need and how you want the data delivered. We’ll review feasibility and come back with a clear proposed scope.
Useful details to share with us