Institutional data, delivered to your models.
Your models are only as good as what you feed them. Orbit processes 70 million documents per year into clean, structured, source-linked datasets, delivered directly into your pipelines and agentic workflows through MCP and API.
The challenge
The data engineering iceberg sinks most in-house AI builds.
Building a proof of concept on a thin data layer is straightforward. Scaling it across thousands of companies, in multiple languages, with a full audit trail, is a multi-year engineering effort most teams underestimate. The hard part is the substrate, not the model.
Curation is the hidden cost
Most of the effort in any serious financial AI build goes into collecting, parsing, and structuring unstructured documents at scale, not into the model itself.
Coverage gaps break models
A model trained or fed on a partial universe produces partial signals. Reaching every filing, transcript, and exchange that matters is its own engineering problem.
Integration friction
Even good data is useless if it cannot flow cleanly into your existing pipelines, warehouses, and the AI tools your team already runs.
How Orbit helps
MCP-native distribution of the Orbit Knowledge Base.
Orbit's knowledge base is built for machine consumption first. Every dataset, and every agent built on top of it, is automatically exposed as an MCP endpoint, so your team consumes institutional-grade data in the environment it already works in, with no bespoke integration project.
Five curated institutional datasets
Core Filings and Governance, Corporate Events, Earnings Intelligence, Sustainability and Policies, and Regulatory Intelligence, processed and entity-resolved from 70 million documents per year.
MCP as the distribution layer
Connect Orbit directly to Claude, ChatGPT Enterprise, or your own internal copilots. Every Knowledge Base dataset and every Orbit agent is an MCP endpoint your team can query natively, with no additional configuration.
API and direct feed
Where you prefer it, the same structured, source-linked data flows via the Orbit API or as a direct feed into your data warehouse, ready to model on.
Source-linked by design
Every datapoint traces back to the exact paragraph in the source document, so your pipelines carry provenance, not just values.
Distribute the knowledge base wherever your models live.
MCP turns Orbit from a destination into infrastructure. Rather than asking your team to work inside another interface, Orbit exposes its knowledge base and agents as endpoints that connect into the tools and pipelines you already run.
Orbit's distribution reaches established channels too, including the SimCorp One Agent Launchpad, FactSet, and Eagle Alpha, so the same data is available through the rails your firm already uses.
The result is a composable data layer: license the substrate, keep your engineering focused on what is genuinely proprietary, your strategy.
Built on the Orbit platform
What you license is the substrate, not the plumbing. The entity master resolves every document to the right company across markets and languages, the Knowledge Base structures it once for scale, and the Agent Builder lets your team encode logic that is exposed straight back as an MCP endpoint.
Ready-to-run workflows
Where quant and data teams put Orbit to work.
Orbit slots into the data layer of your stack, however you prefer to consume it.
Feature pipelines
Feed structured filings, events, and earnings data into model features without building ingestion and parsing infrastructure yourself.
Agentic workflows via MCP
Let internal copilots and agents query Orbit datasets and Orbit-built agents natively as MCP endpoints.
Warehouse integration
Land clean, source-linked datasets directly in Snowflake or your warehouse via API or direct feed.
Backtesting substrate
Use a deep, historical, multi-market document base as the foundation for systematic research.
China & APAC coverage
Extend systematic coverage into 5,500 China A-share names available in English at scale.
Provenance & audit
Carry paragraph-level source links through your pipeline for explainability and compliance.
License the substrate. Keep your edge proprietary.
See how quant and data teams consume the Orbit Knowledge Base through MCP, API, and direct feed. These are conversations that matter deeply to us at Orbit.