Meet Surge.
MDO's AI Agent.
Turn natural-language investment questions into production-ready Python workflows, powered by MDO's Financial Intelligence Engine on Snowflake.
Surge is built as a Snowflake Native App and is now available in beta for all MDO users. It searches our documentation, understands your licensing, and determines exactly how to build workflows using the datasets, functions, and tools you already have access to.
From Simple Questions to Sophisticated Research
Surge handles the full spectrum of investment workflow requests and outputs clear, readable, fully editable Python code every time.
Signal Research
"Identify securities with positive earnings revision momentum, expanding margins, and attractive relative valuation, then generate a repeatable screen and test the signal against a benchmark."
Portfolio Attribution
"Decompose portfolio returns by sector, region, and factor exposure over the last 12 months. Show what drove performance relative to the benchmark and highlight the top contributors and detractors."
Workflow Assembly
"What datasets do I have access to for building a factor model? Show me how to combine earnings, price momentum, and quality factors using my current MDO license."
Documentation Lookup
"How do I calculate trailing twelve-month revenue using MDO data? Are there look-ahead bias considerations I should know about for point-in-time analysis?"
AI generates answers. MDO ensures they're correct.
What makes Surge especially powerful is that it sits on top of what MDO already provides: a Financial Intelligence Engine for investment workflows.
MDO takes complex raw financial data and curates it into a structured, analysis-ready foundation that is fast, consistent, and built for real statistical and investment workflows.
Surge is effective because it is not working from raw data alone. It is working from an investment-ready framework that MDO has already engineered to produce reliable, reproducible, and auditable outputs.
This distinction is everything
Surge isn't just an AI chatbot on top of raw data. It's AI on top of an infrastructure built for institutional-grade investment work.
Correct
MDO's data framework handles the nuances that matter — date alignment, look-ahead bias prevention, currency translation — so Surge outputs are trustworthy out of the box.
Reproducible
Every workflow Surge generates is point-in-time accurate, ensuring your backtest today matches the model you run in production tomorrow.
Auditable
Outputs are clear, readable, fully editable Python. Your team can review every line, understand every step, and stand behind every result.
Secure
AI inference runs inside your Snowflake environment via Snowflake Cortex — your proprietary data never leaves your perimeter.
The data nuances that make or break a model
MDO has already solved the hard data engineering problems. Surge inherits all of it automatically.
Deploy and scale without the engineering overhead
Because MDO is built on a robust Snowflake-native architecture, the compute environment is already easy to deploy and scale.
Even non-technical users can build, test, and productionize sophisticated models without needing large engineering teams to create every process from scratch.
- Native Snowflake app, no additional infrastructure
- Scales with your data automatically
- Secure within your existing Snowflake environment
- Accessible to quant and non-quant teams alike